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  • 51.
    Islam, Mohammad A.
    et al.
    Florida International University, Miami.
    Ren, Shaolei
    University of California, Riverside, CA.
    Quan, Gang
    Florida International University, Miami.
    Shakir, Muhammad Zeeshan
    Texas A&M University, Qatar.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Water-Constrained Geographic Load Balancing in Data Centers2017In: IEEE Transactions on Cloud Computing, ISSN 2168-7161, Vol. 5, no 2, p. 208-220, article id 7152842Article in journal (Refereed)
    Abstract [en]

    Spreading across many parts of the world and presently hard striking California, extended droughts could even potentially threaten reliable electricity production and local water supplies, both of which are critical for data center operation. While numerous efforts have been dedicated to reducing data centers’ energy consumption, the enormity of data centers’ water footprints is largely neglected and, if still left unchecked, may handicap service availability during droughts. In this paper, we propose a water-aware workload management algorithm, called WATCH (WATer-constrained workload sCHeduling in data centers), which caps data centers’ long-term water consumption by exploiting spatio-temporal diversities of water efficiency and dynamically dispatching workloads among distributed data centers. We demonstrate the effectiveness of WATCH both analytically and empirically using simulations: based on only online information, WATCH can result in a provably-low operational cost while successfully capping water consumption under a desired level. Our results also show that WATCH can cut water consumption by 20 percent while only incurring a negligible cost increase even compared to state-of-the-art cost-minimizing but water-oblivious solution. Sensitivity studies are conducted to validate WATCH under various settings.

  • 52.
    Javaid, Nadeem
    et al.
    COMSATS Institute of Information Technology, Islamabad.
    Shah, Mehreen
    Allama Iqbal Open University, Islamabad.
    Ahmad, Ashfaq
    COMSATS Institute of Information Technology, Islamabad.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Khan, Majid Iqbal
    COMSATS Institute of Information Technology, Islamabad.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Enhanced Energy Balanced Data Transmission Protocol for Underwater Acoustic Sensor Networks2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 4, article id 487Article in journal (Refereed)
    Abstract [en]

    This paper presents two new energy balanced routing protocols for Underwater Acoustic Sensor Networks (UASNs); Efficient and Balanced Energy consumption Technique (EBET) and Enhanced EBET (EEBET). The first proposed protocol avoids direct transmission over long distance to save sufficient amount of energy consumed in the routing process. The second protocol overcomes the deficiencies in both Balanced Transmission Mechanism (BTM) and EBET techniques. EBET selects relay node on the basis of optimal distance threshold which leads to network lifetime prolongation. The initial energy of each sensor node is divided into energy levels for balanced energy consumption. Selection of high energy level node within transmission range avoids long distance direct data transmission. The EEBET incorporates depth threshold to minimize the number of hops between source node and sink while eradicating backward data transmissions. The EBET technique balances energy consumption within successive ring sectors, while, EEBET balances energy consumption of the entire network. In EEBET, optimum number of energy levels are also calculated to further enhance the network lifetime. Effectiveness of the proposed schemes is validated through simulations where these are compared with two existing routing protocols in terms of network lifetime, transmission loss, and throughput. The simulations are conducted under different network radii and varied number of nodes.

  • 53.
    Jiau, Mingkai
    et al.
    Department of Electronic Engineering, National Taipei University of Technology.
    Huang, Shihchia
    Department of Electronic Engineering, National Taipei University of Technology.
    Hwang, Jenqneng
    Department of Electrical Engineering, University of Washington, Seattle.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Multimedia Services in Cloud-Based Vehicular Networks2015In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 7, no 3, p. 62-79, article id 7166430Article in journal (Refereed)
    Abstract [en]

    Research into the requirements for mobile services has seen a growing interest in the fields of cloud technology and vehicular applications. Integrating cloud computing and storage with vehicles is a way to increase accessibility to multimedia services, and inspire myriad potential applications and research topics. This paper presents an overview of the characteristics of cloud computing, and introduces the basic concepts of vehicular networks. An architecture for multimedia cloud computing is proposed to suit subscription service mechanisms. The tendency to equip vehicles with advanced and embedded devices such as diverse sensors increases the capabilities of vehicles to provide computation and collection of multimedia content in the form of the vehicular network. Then, the taxonomy of cloud-based vehicular networks is addressed from the standpoint of the service relationship between the cloud computing and vehicular networks. In this paper, we identify the main considerations and challenges for cloud based vehicular networks regarding multimedia services, and propose potential research directions to make multimedia services achievable. More specifically, we quantitatively evaluate the performance metrics of these researches. For example, in the proposed broadcast storm mitigation scheme for vehicular networks, the packet delivery ratio and the normalized throughput can both achieve about 90%, making the proposed scheme a useful candidate for multimedia data exchange. Moreover, in the video uplinking scenarios, the proposed scheme is favorably compared with two well-known schedulers, M-LWDF and EXP, with the performance much closer to the optimum

  • 54.
    Jindal, Anish
    et al.
    CSE Department, Thapar University.
    Dua, Amit
    Department of Computer Science and Information Systems, BITS Pilani.
    Kumar, Neeraj
    CSE Department, Thapar University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rodrigues, Joel J.P.C.
    National Institute of Telecommunications (Inatel), Brazil.
    An efficient fuzzy rule-based big data analytics scheme for providing healthcare-as-a-service2017In: IEEE International Conference on Communications, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7996965Conference paper (Refereed)
    Abstract [en]

    With advancements in information and communication technology (ICT), there is an increase in the number of users availing remote healthcare applications. The data collected about the patients in these applications varies with respect to volume, velocity, variety, veracity, and value. To process such a large collection of heterogeneous data is one of the biggest challenges that needs a specialized approach. To address this issue, a new fuzzy rule-based classifier for big data handling using cloud-based infrastructure is presented in this paper, with an aim to provide Healthcare-as-a-Service (HaaS) to the users located at remote locations. The proposed scheme is based upon the cluster formation using the modified Expectation-Maximization (EM) algorithm and processing of the big data on the cloud environment. Then, a fuzzy rule-based classifier is designed for an efficient decision making about the data classification in the proposed scheme. The proposed scheme is evaluated with respect to different evaluation metrics such as classification time, response time, accuracy and false positive rate. The results obtained are compared with the standard techniques to confirm the effectiveness of the proposed scheme.

  • 55.
    Jing, Xu
    et al.
    College of Information Engineering, Northwest A & F University, Yangling.
    Hu, Hanwen
    College of Information Engineering, Northwest A & F University, Yangling.
    Yang, Huijun
    College of Information Engineering, Northwest A & F University, Yangling.
    Au, Man Ho
    Department of Computing, The Hong Kong Polytechnic University.
    Li, Shuqin
    College of Information Engineering, Northwest A & F University.
    Xiong, Naixue
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK.
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Quantitative Risk Assessment Model Involving Frequency and Threat Degree under Line-of-Business Services for Infrastructure of Emerging Sensor Networks2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 3, article id 642Article in journal (Refereed)
    Abstract [en]

    The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider's server contains a lot of valuable resources. LoBSs' users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs' risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs' risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing.

  • 56.
    Kamal, Ahmed E.
    et al.
    Department of Electrical & Computer Engineering, Iowa State University, USA.
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University, Saudi Arabia.
    Chen, Hsiao-Hwa
    Department of Engineering Science, National Cheng Kung University, Taiwan.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Survivability strategies for emerging wireless networks2017In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 128, p. 1-4Article in journal (Refereed)
  • 57.
    Kekely, Lukáš
    et al.
    CESNET a. l. e., Zikova 4, Prague.
    Kucera, Jan
    CESNET a. l. e., Zikova 4, Prague.
    Pus, Viktor
    CESNET a. l. e., Zikova 4, Prague.
    Korenek, Jan
    IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Software defined monitoring of application protocols2016In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 2, p. 615-626, article id 7087363Article in journal (Refereed)
    Abstract [en]

    With the ongoing shift of network services to the application layer also the monitoring systems focus more on the data from the application layer. The increasing speed of the network links, together with the increased complexity of application protocol processing, require a new way of hardware acceleration. We propose a new concept of hardware acceleration for flexible flow-based application level traffic monitoring which we call Software Defined Monitoring. Application layer processing is performed by monitoring tasks implemented in the software in conjunction with a configurable hardware accelerator. The accelerator is a high-speed application-specific processor tailored to stateful flow processing. The software monitoring tasks control the level of detail retained by the hardware for each flow in such a way that the usable information is always retained, while the remaining data is processed by simpler methods. Flexibility of the concept is provided by a plugin-based design of both hardware and software, which ensures adaptability in the evolving world of network monitoring. Our high-speed implementation using FPGA acceleration board in a commodity server is able to perform a 100 Gb/s flow traffic measurement augmented by a selected application-level protocol analysis

  • 58.
    Khan, Zaheer
    et al.
    Centre for Wireless Communications, University of Oulu.
    Lehtomäki, Janne
    Centre for Wireless Communications, University of Oulu.
    Vasilakos, Athanasios V.
    Centre for Wireless Communications, University of Oulu.
    MacKenzie, Allen B.
    Centre for Wireless Communications, University of Oulu.
    Juntti, Markku
    Centre for Wireless Communications, University of Oulu.
    Adaptive wireless communications under competition and jamming in energy constrained networks2018In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 24, no 1, p. 151-171Article in journal (Refereed)
    Abstract [en]

    We propose a framed slotted Aloha-based adaptive method for robust communication between autonomous wireless nodes competing to access a channel under unknown network conditions such as adversarial disruptions. With energy as a scarce resource, we show that in order to disrupt communications, our method forces the reactive adversary to incur higher energy cost relative to a legitimate node. Consequently, the adversary depletes its energy resources and stops attacking the network. Using the proposed method, a transmitter node changes the number of selected time slots and the access probability in each selected time slot based on the number of unsuccessful transmissions of a data packet. On the receiver side, a receiver node changes the probability of listening in a time slot based on the number of unsuccessful communication attempts of a packet. We compare the proposed method with two other framed slotted Aloha-based methods in terms of average energy consumption and average time required to communicate a packet. For performance evaluation, we consider scenarios in which: (1) Multiple nodes compete to access a channel. (2) Nodes compete in the presence of adversarial attacks. (3) Nodes compete in the presence of channel errors and capture effect.

  • 59.
    Khan, Zaheer
    et al.
    Centre for Wireless Communications, University of Oulu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Barua, Bidushi
    Centre for Wireless Communications, University of Oulu.
    Shahabuddin, Shahriar
    Centre for Wireless Communications, University of Oulu.
    Ahmadi, Hamed
    CTVR, Trinity College Dublin.
    Cooperative content delivery exploiting multiple wireless interfaces: methods, new technological developments, open research issues and a case study2016In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 22, no 6, p. 1961-1983Article in journal (Refereed)
    Abstract [en]

    In this tutorial paper, we discuss and compare cooperative content delivery (CCD) techniques that exploit multiple wireless interfaces available on mobile devices to efficiently satisfy the already massive and rapidly growing user demand for content. The discussed CCD techniques include simultaneous use of wireless interfaces, opportunistic use of wireless interfaces, and aggregate use of wireless interfaces. We provide a taxonomy of different ways in which multiple wireless interfaces are exploited for CCD, and also discuss the real measurement studies that evaluate the content delivery performance of different wireless interfaces in terms of energy consumption and throughput. We describe several challenges related to the design of CCD methods using multiple interfaces, and also explain how new technological developments can help in accelerating the performance of such CCD methods. The new technological developments discussed in this paper include wireless interface aggregation, network caching, and the use of crowdsourcing. We provide a case study for selection of devices in a group for CCD using multiple interfaces. We consider this case study based on the observation that in general different CCD users can have different link qualities in terms of transmit/receive performance, and selection of users with good link qualities for CCD can accelerate the content delivery performance of wireless networks. Finally, we discuss some open research issues relating to CCD using multiple interfaces.

  • 60.
    Kim, Dohyung
    et al.
    Sungkyunkwan University, Suwon, South Korea.
    Bi, Jun
    Tsinghua University, Beijing .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yeom, Ikjun
    Sungkyunkwan University, Suwon .
    Security of Cached Content in NDN2017In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 12, no 12, p. 2933-2944Article in journal (Refereed)
    Abstract [en]

    In Named-Data Networking (NDN), content is cached in network nodes and served for future requests. This property of NDN allows attackers to inject poisoned content into the network and isolate users from valid content sources. Since a digital signature is embedded in every piece of content in NDN architecture, poisoned content is discarded if routers perform signature verification; however, if every content is verified by every router, it would be overly expensive to do. In our preliminary work, we have suggested a content verification scheme that minimizes unnecessary verification and favors already verified content in the content store, which reduces the verification overhead by as much as 90% without failing to detect every piece of poisoned content. Under this scheme, however, routers are vulnerable to verification attack, in which a large amount of unverified content is accessed to exhaust system resources. In this paper, we carefully look at the possible concerns of our preliminary work, including verification attack, and present a simple but effective solution. The proposed solution mitigates the weakness of our preliminary work and allows this paper to be deployed for real-world applications.

  • 61.
    Kong, Linghe
    et al.
    Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
    Ye, Lingsheng
    Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
    Wu, Fan
    Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
    Tao, Meixia
    Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
    Chen, Guihai
    Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Autonomous Relay for Millimeter-Wave Wireless Communications2017In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 35, no 9, p. 2127-2136Article in journal (Refereed)
    Abstract [en]

    Millimeter-wave (mmWave) communication is the rising technology for next-generation wireless transmission. Benefited by its abundant bandwidth and short wavelength, mmWave is advanced in multi-gigabit transmittability and beamforming. In contrast, the short wavelength also makes mmWave easily blocked by obstacles. In order to bypass these obstacles, relays are widely needed in mmWave communications. Unmanned autonomous vehicles (UAVs), such as drones and self-driving robots, enable the mobile relays in real applications. Nevertheless, it is challenging for a UAV to find its optimal relay location automatically. On the one hand, it is difficult to find the location accurately due to the complex and dynamic wireless environment; on the other hand, most applications require the relay to forward data immediately, so the autonomous process should be fast. To tackle this challenge, we propose a novel method AutoRelay specialized for mmWave communications. In AutoRelay, the UAV samples the link qualities of mmWave beams while moving. Based on the real-time sampling, the UAV gradually adjusts its path to approach the optimal location by leveraging compressive sensing theory to estimate the link qualities in candidate space, which increases the accuracy and save the time. Performance results demonstrate that AutoRelay outperforms existing methods in achieving an accurate and efficient relay strategy.

  • 62.
    Kumar, Neeraj
    et al.
    Thapar University, Department of Computer Science & Engineering, Patiala, Punjab.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rodrigues, Joel J.P.C.
    University of Beira Interior.
    A Multi-Tenant Cloud-Based DC Nano Grid for Self-Sustained Smart Buildings in Smart Cities2017In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 55, no 3, p. 14-21, article id 7876851Article in journal (Refereed)
    Abstract [en]

    Energy is one of the most valuable resources of the modern era and needs to be consumed in an optimized manner by an intelligent usage of various smart devices, which are major sources of energy consumption nowadays. With the popularity of low-voltage DC appliances such as-LEDs, computers, and laptops, there arises a need to design new solutions for self-sustainable smart energy buildings containing these appliances. These smart buildings constitute the next generation smart cities. Keeping focus on these points, this article proposes a cloud-assisted DC nanogrid for self-sustainable smart buildings in next generation smart cities. As there may be a large number of such smart buildings in different smart cities in the near future, a huge amount of data with respect to demand and generation of electricity is expected to be generated from all such buildings. This data would be of heterogeneous types as it would be generated from different types of appliances in these smart buildings. To handle this situation, we have used a cloud-based infrastructure to make intelligent decisions with respect to the energy usage of various appliances. This results in an uninterrupted DC power supply to all low-voltage DC appliances with minimal dependence on the grid. Hence, the extra burden on the main grid in peak hours is reduced as buildings in smart cities would be self-sustainable with respect to their energy demands

  • 63.
    Kundu, Arghya
    et al.
    Lexmark International Pvt. Ltd. Kolkata, India.
    Laha, Sougata
    School of Computer Engineering Nanyang Technological University, Singapore.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Correlation-based genetic algorithm for real-parameter optimization2016In: 2016 IEEE Congress on Evolutionary Computation (CEC), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 4804-4809, article id 7744405Conference paper (Refereed)
    Abstract [en]

    We propose a genetic algorithm (GA) by taking into account the correlation between the current best candidate with the other candidates in the population. In this paper we propose a new selection operator and in addition we have designed a prediction operator which works on an archive of selected candidates. We test our proposed algorithm on the problem definitions for the CEC 2014 special session and competition on single objective real-parameter numerical optimization.

  • 64.
    Lan, Kun
    et al.
    Department of Computer and Information Science, University of Macau.
    Fong, Simon
    Department of Computer and Information Science, University of Macau.
    Song, Wei
    School of Computer Science, North China University of Technology, Beijing .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Milham, Richard C.
    Department of Information Technology, Durban University of Technology.
    Self-Adaptive Pre-Processing Methodology for Big Data Stream Mining in Internet of Things Environmental Sensor Monitoring2017In: Symmetry, ISSN 2073-8994, E-ISSN 2073-8994, Vol. 9, no 10, article id 244Article in journal (Refereed)
    Abstract [en]

    Over the years, advanced IT technologies have facilitated the emergence of new ways of generating and gathering data rapidly, continuously, and largely and are associated with a new research and application branch, namely, data stream mining (DSM). Among those multiple scenarios of DSM, the Internet of Things (IoT) plays a significant role, with a typical meaning of a tough and challenging computational case of big data. In this paper, we describe a self-adaptive approach to the pre-processing step of data stream classification. The proposed algorithm allows different divisions with both variable numbers and lengths of sub-windows under a whole sliding window on an input stream, and clustering-based particle swarm optimization (CPSO) is adopted as the main metaheuristic search method to guarantee that its stream segmentations are effective and adaptive to itself. In order to create a more abundant search space, statistical feature extraction (SFX) is applied after variable partitions of the entire sliding window. We validate and test the effort of our algorithm with other temporal methods according to several IoT environmental sensor monitoring datasets. The experiments yield encouraging outcomes, supporting the reality that picking significant appropriate variant sub-window segmentations heuristically with an incorporated clustering technique merit would allow these to perform better than others

  • 65.
    Lee, Cheng-Chi
    et al.
    Department of Library and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan, Republic of China; Department of Photonics and Communication Engineering, Asia University, Taichung, Taiwan, Republic of China.
    Li, Chun-Ta
    Department of Information Management, Tainan University of Technology, Tainan, Taiwan, Republic of China.
    Cheng, Chung-Lun
    Department of Library and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan, Republic of China.
    Lai, Yan-Ming
    Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, Republic of China.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Novel Group Ownership Delegate Protocol for RFID Systems2018In: Information Systems Frontiers, ISSN 1387-3326, E-ISSN 1572-9419Article in journal (Refereed)
    Abstract [en]

    In recent years, Radio Frequency Identification (RFID) applications of various kinds have been blooming. However, along with the stunning advancement have come all sorts of security and privacy issues, for RFID tags oftentimes store private data and so the permission to read a tag or any other kind of access needs to be carefully controlled. Therefore, of all the RFID-related researches released so far, a big portion focuses on the issue of authentication. There have been so many cases where the legal access to or control over a tag needs to be switched from one reader to another, which has encouraged the development of quite a number of different kinds of ownership transfer protocols. On the other hand, not only has the need for ownership transfer been increasing, but a part of it has also been evolving from individual ownership transfer into group ownership transfer. However, in spite of the growing need for practical group ownership transfer services, little research has been done to offer an answer to the need. In this paper, we shall present a new RFID time-bound group ownership delegate protocol based on homomorphic encryption and quadratic residues. In addition, in order to provide more comprehensive service, on top of mutual authentication and ownership delegation, we also offer options for the e-th time verification as well as the revocation of earlier delegation.

  • 66.
    Li, Changle
    et al.
    State Key Laboratory of Integrated Services Networks, Xidian University.
    Zhang, Beibei
    State Key Laboratory of Integrated Services Networks, Xidian University.
    Yuan, Xiaoming
    State Key Laboratory of Integrated Services Networks, Xidian University.
    Ullah, Sana
    Department of Computer and Software Technology, University of Swat.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    MC-MAC: a multi-channel based MAC scheme for interference mitigation in WBANs2018In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 24, no 3, p. 719-733Article in journal (Refereed)
    Abstract [en]

    Wireless body area networks (WBANs) support the inter-operability of biomedical sensors and medical institutions with convenience and high-efficiency, which makes it an appropriate solution for the pervasive healthcare. Typically, WBANs comprise in-body or around-body sensor nodes for collecting data of physiological feature. Therefore, the efficient medium access control (MAC) protocol is a crucial paramount to coordinate these devices and forward data to the medical center in an efficient and reliable way. However, the extensive use of wireless channel and coexistence of WBANs may result in inevitable interference which will cause performance degradation. Besides, contention-based access in single channel in WBANs is less efficient for dense medical traffic on account of large packet delay, energy consumption and low priority starvation. To address these issues above, we propose a multi-channel MAC (MC-MAC) scheme to obtain better network performance. Considering the characteristic and emergency degree of medical traffic, we introduce a novel channel mapping and selection mechanism, cooperating with conflict avoidance strategy, to organize nodes to access available channels without collisions. In addition, we have evaluated the performance of MC-MAC and the standard IEEE 802.15.6 via simulation and hardware test. The test is conducted by hardware platform based on prototype system of WBANs. Both of the analysis and simulation results show that MC-MAC outperforms the IEEE 802.15.6 in terms of packet delay, throughput, packet error rate and frame error rate

  • 67.
    Li, Di
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology.
    Nan, Zhou
    School of Mechanical and Automotive Engineering, South China University of Technology.
    Jiafu, Wan
    School of Mechanical and Automotive Engineering, South China University of Technology.
    Zhenkun, Zhai
    School of Mechanical and Automotive Engineering, South China University of Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Towards a model-integrated computing paradigm for reconfigurable motion control system2017In: IEEE International Conference on Industrial Informatics (INDIN), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 756-761, article id 7819260Conference paper (Refereed)
    Abstract [en]

    To accommodate the trend toward mass customization launched by intelligent manufacturing, the paper proposes the adoption of model-integrated computing (MIC) paradigm in the motion control system development process for enhancing flexibility and robustness. Hierarchical structural and behavioral diversities in motion control system are considered during the implementation of MIC paradigm. For design-phase implementation, a motion-control-domain-specific modeling language is developed, and formal semantics are integrated. With regard to execution-phase implementation, a real-time runtime framework compliant with the IEC 61499 standard is proposed. Extensions of function block chain and priority-based event propagation are proposed. Dynamically extendable FB types library for motion control domain is constructed. A prototype three-axis motion control system is modeled using the proposed modelling language and is then deployed to the implemented framework to prove the feasibility of the adoption of the MIC paradigm in motion control domain

  • 68.
    Li, He
    et al.
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Ota, Kaoru
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Dong, Mianxiong
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Nagano, Koji
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Multimedia Processing Pricing Strategy in GPU-accelerated Cloud Computing2017In: IEEE Transactions on Cloud Computing, E-ISSN 2168-7161Article in journal (Refereed)
    Abstract [en]

    Graphics processing unit (GPU) accelerated processing performs significant efficiency in many multimedia applications. With the development of GPU cloud computing, more and more cloud providers focus on GPU-accelerated services. Since the high maintenance cost and different speedups for various applications, GPU-accelerated services still need a different pricing strategy. Thus, in this paper, we propose an optimal GPU-accelerated multimedia processing service pricing strategy for maximize the profits of both cloud provider and users. We first analyze the revenues and costs of the cloud provider and users when users adopt GPU-accelerated multimedia processing services then state the profit functions of both the cloud provider and users. With a game theory based method, we find the optimal solutions of both the cloud provider’s and users’ profit functions. Finally, through large scale simulations, our pricing strategy brings higher profit to the cloud provider and users compared to the original pricing strategy of GPU cloud services.

  • 69.
    Li, Tong
    et al.
    Technology Research Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing.
    Zhang, Tianyu
    Technology Research Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing.
    Zhong, Bin
    School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan.
    Zhang, Zhongshan
    University of Science and Technology, Beijing, Technology Research Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Physical layer security via maximal ratio combining and relay selection over Rayleigh fading channel2015In: 26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015: Hong Kong, Aug. 30 2015-Sept. 2 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 612-616, article id 7343372Conference paper (Refereed)
    Abstract [en]

    The impact of both maximal ratio combining (MRC) and relay selection on the physical layer security in wireless communication systems is studied by analyzing some important factors, including the probability characteristic of the legitimate receiver (Bob) and malicious eavesdropper (Eve)'s end-to-end signal-to-noise ratio (SNR), the secrecy outage probability, and the average secrecy channel capacity over Rayleigh fading Channel. We assume that Bob receives its data from both the relay and the source by cooperative communication, provided that MRC is employed at the receiver. Compared to the conventional MRC methods, a higher spatial diversity order can be exploited by performing relay selection in the proposed method, as validated via both theoretical analysis and numerical simulation. The theoretical closed-form expressions for some figures of merit, e.g., the secrecy outage probability and the average secrecy capacity, are all consistent with the numerical results

  • 70.
    Li, Xiaomin
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Li, Di
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Wan, Jiafu
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Lai, Chinfeng
    Department of Computer Science and Information Engineering, National Chung Cheng University, Jiayi.
    Wang, Shiyong
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    A review of industrial wireless networks in the context of Industry 4.02017In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 23, no 1, p. 23-41Article in journal (Refereed)
    Abstract [en]

    There have been many recent advances in wireless communication technologies, particularly in the area of wireless sensor networks, which have undergone rapid development and been successfully applied in the consumer electronics market. Therefore, wireless networks (WNs) have been attracting more attention from academic communities and other domains. From an industrial perspective, WNs present many advantages including flexibility, low cost, easy deployment and so on. Therefore, WNs can play a vital role in the Industry 4.0 framework, and can be used for smart factories and intelligent manufacturing systems. In this paper, we present an overview of industrial WNs (IWNs), discuss IWN features and related techniques, and then provide a new architecture based on quality of service and quality of data for IWNs. We also propose some applications for IWNs and IWN standards. Then, we will use a case from our previous achievements to explain how to design an IWN under Industry 4.0. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make IWNs truly ubiquitous for a wide range of applications. 

  • 71.
    Li, Xuran
    et al.
    Faculty of Information Technology, Macau University of Science and Technology.
    Dai, Hong-Ning
    Faculty of Information Technology, Macau University of Science and Technology.
    Wang, Qiu
    Faculty of Information Technology, Macau University of Science and Technology, Macau.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    AE-shelter: An novel anti-eavesdropping scheme in wireless networks2017In: IEEE International Conference on Communications, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7996847Conference paper (Refereed)
    Abstract [en]

    To protect confidential communications from eavesdropping attacks in wireless networks, we propose a novel anti-eavesdropping scheme named AE-Shelter. In our proposed scheme, we place a number of friendly jammers at a circular boundary to protect legitimate communications. The jammers sending artificial noise can mitigate the eavesdropping capability of wiretapping the confidential information. We also establish a theoretical model to evaluate the performance of AE-Shelter. Our results show that our proposed AE-Shelter scheme can significantly reduce the eavesdropping risk without significantly degrading the network performance.

  • 72.
    Liao, Xuhong
    et al.
    National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    He, Yong
    National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University.
    Small-World Human Brain Networks: Perspectives and Challenges2017In: Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, E-ISSN 1873-7528, Vol. 77, p. 286-300Article in journal (Refereed)
    Abstract [en]

    Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and aging and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field.

  • 73.
    Lin, Bing
    et al.
    College of Mathematics and Computer Sciences, Fuzhou University.
    Guo, Wenzhong
    College of Mathematics and Computer Sciences, Fuzhou University.
    Xiong, Naixue
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology.
    Chen, Guolong
    College of Mathematics and Computer Sciences, Fuzhou University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Hong
    College of Mathematics and Computer Sciences, Fuzhou University.
    A Pretreatment Workflow Scheduling Approach for Big Data Applications in Multi-cloud Environments2016In: IEEE Transactions on Network and Service Management, ISSN 1932-4537, E-ISSN 1932-4537, Vol. 13, no 3, p. 581-594Article in journal (Refereed)
    Abstract [en]

    The rapid development of the latest distributed computing paradigm, i.e., cloud computing, generates a highly fragmented cloud market composed of numerous cloud providers and offers tremendous parallel computing ability to handle Big Data problems. One of the biggest challenges in Multi-clouds is efficient workflow scheduling. Although the workflow scheduling problem has been studied extensively, there are still very few primal works tailored for Multi-cloud environments. Moreover, the existing research works either fail to satisfy the Quality of Service (QoS) requirements, or do not consider some fundamental features of cloud computing such as heterogeneity and elasticity of computing resources. In this paper, a scheduling algorithm which is called Multi-Clouds Partial Critical Paths with Pretreatment (MCPCPP) for Big Data workflows in Multi-clouds is presented. This algorithm incorporates the concept of Partial Critical Paths, and aims to minimize the execution cost of workflow while satisfying the defined deadline constraint. Our approach takes into considerations the essential characteristics of Multi-clouds such as the charge per time interval, various instance types from different cloud providers as well as homogeneous intra-bandwidth vs. heterogeneous inter-bandwidth. Various types of workflows are used for evaluation purpose and our experimental results show that the MCPCPP is promising.

  • 74.
    Lin, Chao
    et al.
    Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University.
    He, Debiao
    Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University.
    Huang, Xinyi
    School of Mathematics and Computer Science, Fujian Normal University.
    Choo, Kim-Kwang Raymond
    The University of Texas at San Antonio.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    BSeIn: A blockchain-based secure mutual authentication with fine-grained access control system for industry 4.02018In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 116, p. 42-52Article in journal (Refereed)
    Abstract [en]

    To be prepared for the ‘Industry 4.0’-era, we propose a hierarchical framework comprising four tangible layers, which is designed to vertically integrate inter-organizational value networks, engineering value chain, manufacturing factories, etc. The conceptual framework allows us to efficiently implement a flexible and reconfigurable smart factory. However, we need to consider security inherent in existing (stand-alone) devices and networks as well as those that may arise in such integrations. Especially the existing solutions are insufficient to address these fundamental security concerns. Thus, we present a blockchain-based system for secure mutual authentication, BSeIn, to enforce fine-grained access control polices. The proposed system (with integrated attribute signature, multi-receivers encryption and message authentication code) is designed to provide privacy and security guarantees such as anonymous authentication, auditability, and confidentiality. BSeIn also scales well due to the utilization of smart contract. We then evaluate the security and performance of BSeIn. For example, findings from the performance evaluation demonstrate that Initialization/Request Issuance/Chain Transaction/State Delivery/Permission Update phase only cost 12.123/4.810/6.978/0.013/2.559s, respectively.

  • 75.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Labeau, Fabrice
    Department of Electrical and Computer Engineering, McGill University, Montreal.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    QoE-based optimal resource allocation in wireless healthcare networks: opportunities and challenges2015In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 21, no 8, p. 2483-2500Article in journal (Refereed)
    Abstract [en]

    Ubiquitous health monitoring is a mobile health service with the aim of monitoring patients’ conditions anytime and anywhere by collecting and transferring biosignal data from patients to health-service providers (e.g., healthcare centers). As a critical issue in ubiquitous health monitoring, wireless resource allocation can influence the performance of health monitoring, and the majority of work in wireless resource allocation for health monitoring has focused on quality-of-service oriented allocation schemes with primary challenges at the physical and MAC layers. Recently, quality-of-experience (QoE) oriented resource allocation schemes in wireless health monitoring have attracted attentions as a promising design to a better service of healthcare monitoring. In this paper, we overview the metrics of assessing the quality of medical images, and discuss the performance of these metrics in QoE-oriented resource allocation for health monitoring. We start with addressing the state-of-the-art QoE metrics by providing a taxonomy of the different metrics employed in assessing medical images. We then present the design of resource allocation schemes for health monitoring. After that, we present a case study to compare the performance of different classes of metrics in designing resource allocation schemes. We end the paper with a few open issues in the design of novel QoE metrics for resource allocation in health monitoring.

  • 76.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of Chengdu, 610051, China.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of Chengdu, 610051, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    User-Priority-Based Power Control in D2D Networks for Mobile Health2017In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234Article in journal (Refereed)
    Abstract [en]

    A device-to-device (D2D) assisted cellular network is pervasive to support ubiquitous healthcare applications, since it is expected to bring the significant benefits of improving user throughput, extending the battery life of mobiles, etc. However, D2D and cellular communications in the same network may cause cross-tier interference (CTI) to each other. Also a critical issue of using D2D assisted cellular networks under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical equipments. In consideration of CTI and EMI, we study the problem of optimizing the energy efficiency (EE) across the mobile users in different priorities (different levels of emergency) within the Internet of vehicles for mobile health, and propose a penalty-function algorithm of power control to solve the aforementioned problem. Numerical results demonstrate that the proposed algorithm can achieve remarkable improvements in terms of EE, while ensuring an allowable level of EMI on medical equipments.

  • 77.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Yao, Yuanzhe
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    User-priority based power control over the D2D assisted Internet of vehicles for mobile health2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 3, p. 824-831, article id 7858717Article in journal (Refereed)
    Abstract [en]

    A device-to-device (D2D) assisted cellular network is pervasive to support ubiquitous healthcare applications, since it is expected to bring the significant benefits of improving user throughput, extending the battery life of mobiles, etc. However, D2D and cellular communications in the same network may cause cross-tier interference (CTI) to each other. Also a critical issue of using D2D assisted cellular networks under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical equipments. In consideration of CTI and EMI, we study the problem of optimizing individual channel rates of the mobile users in different priorities (different levels of emergency) within the Internet of vehicles for mobile health, and propose an algorithm of controlling the transmit power to solve the above-mentioned problem under a gametheoretical framework. Numerical results show that the proposed algorithm can converge linearly to the optimum, while ensuring an allowable level of EMI on medical equipments.

  • 78.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Yao, Yuanzhe
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Neural Networks for Computer-Aided Diagnosis in Medicine: a review2016In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 216, p. 700-708Article in journal (Refereed)
    Abstract [en]

    This survey makes an overview of the most recent applications on the neural networks for the computer-aided medical diagnosis (CAMD) over the past decade. CAMD can facilitate the automation of decision making, extraction and visualization of complex characteristics for clinical diagnosis purposes. Over the past decade, neural networks have attained considerable research interest and are widely employed to complex CAMD systems in diverse clinical application domains, such as detecting diseases, classification of diseases, testing the compatibility of new drugs, etc. Overall, this paper reviews the state-of-the-art of neural networks for CAMD. It helps the readers understand the topic of neural networks for CAMD by summarizing the findings addressed in recent academic papers as well as presenting a few open issues of developing the research on this topic.

  • 79.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Wu, Xuanli
    Communication Technology Research Center, Harbin Institute of Technology.
    Labeau, Fabrice
    Department of Electrical and Computer Engineering, McGill University, Montreal.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Internet of vehicles for E-health applications in view of EMI on medical sensors2015In: Journal of Sensors, ISSN 1687-725X, E-ISSN 1687-7268, Vol. 2015, article id 315948Article in journal (Refereed)
    Abstract [en]

    Wireless technologies are pervasive to support ubiquitous healthcare applications. However, RF transmission in wireless technologies can lead to electromagnetic interference (EMI) on medical sensors under a healthcare scenario, and a high level of EMI may lead to a critical malfunction of medical sensors. In view of EMI to medical sensors, we propose a joint power and rate control algorithm under game theoretic framework to schedule data transmission at each of wireless sensors. The objective of such a game is to maximize the utility of each wireless user subject to the EMI constraints for medical sensors. We show that the proposed game has a unique Nash equilibrium and our joint power and rate control algorithm would converge to the Nash equilibrium. Numerical results illustrate that the proposed algorithm can achieve robust performance against the variations of mobile hospital environments

  • 80.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Yao, Yuanzhe
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Labeau, Fabrice
    Department of Electrical and Computer Engineering, McGill University, Montreal.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Optimal Network QoS over the Internet of Vehicles for E-Health Applications2016In: International Journal of Mobile Information Systems, ISSN 1574-017X, E-ISSN 1875-905X, Vol. 2016, article id 5140486Article in journal (Refereed)
    Abstract [en]

    Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In consideration of EMI on medical sensors, we study the optimization of quality of service (QoS) within the whole Internet of vehicles for E-health and propose a novel model to optimize the QoS by allocating the transmit power of each user. Our results show that the optimal power control policy depends on the objective of optimization problems: a greedy policy is optimal to maximize the summation of QoS of each user, whereas a fair policy is optimal to maximize the product of QoS of each user. Algorithms are taken to derive the optimal policies, and numerical results of optimizing QoS are presented for both objectives and QoS constraints.

  • 81.
    Liu, Jun
    et al.
    Xi’an Jiaotong University, Xi’an, China.
    Yan, Zheng
    Xidian University, Xi’an, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Laurence T.
    Department of Computer Science, St. Francis Xavier University, Antigonish, Canada.
    Guest Editorial Data Mining in Cyber, Physical, and Social Computing2017In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 11, no 1, p. 194-196Article in journal (Refereed)
    Abstract [en]

    Presents an introduction to the issue which focuses on data mining in cyber, physical, and social computing

  • 82.
    Liu, Kai
    et al.
    School of Electronics and Information Engineering, Beihang University, Beijing.
    Chang, Xiaoyang
    School of Electronics and Information Engineering, Beihang University, Beijing.
    Liu, Feng
    School of Electronics and Information Engineering, Beihang University, Beijing.
    Wang, Xin
    Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Cooperative MAC Protocol with Rapid Relay Selection for Wireless Ad hoc Networks2015In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 91, p. 262-282Article in journal (Refereed)
    Abstract [en]

    We propose a cooperative MAC protocol with rapid relay selection (RRS-CMAC) to improve the cooperation efficiency and multiple access performance in wireless ad hoc networks. In this protocol, if the data rate between a sender and its recipient is low, an optimal relay is selected by a rate differentiation phase (RDP), priority differentiation phase (PDP), and contention resolution phase (CRP) for relays with the same priority. In the RDP, each contending relay determines its data rate level based on the data rate from the sender to itself and that from itself to the recipient, and then broadcasts busy tones to its neighbor nodes or senses the channel according to the values of its binary digits, which are determined by its data rate level. Relays with the highest data rate levels win and continue to the next phase. In PDP, these winning relays send busy tones or sense the channel according to their own priority values, with the highest priority relays winning in this phase. Then CRP is performed using k-round contention resolution (k-CR) to select a unique optimal relay. Relays sending busy tones earliest and for the longest duration proceed to the next round, while others, sensing a busy tone, subsequently withdraw from contention. A packet piggyback mechanism is adopted to allow data packet transmission without reservation if the winning relay has a packet to send, and the direct transmission rate to its recipient is high. This reduces reservation overhead and improves channel utilization. Both theoretical analysis and simulation results show that the throughput of the proposed protocol is better than those of the CoopMACA and 2rcMAC protocols.

  • 83.
    Liu, Tong
    et al.
    Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
    Zhou, Yanmin
    Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
    Zhang, Qian
    Department of Computer Science and Engineering, Hong Kong University of Science and Technology.
    Vasilakos, Athanasios
    Computer Science Department, Kuwait University.
    Stochastic Optimal Control for Participatory Sensing Systems with Heterogenous Requests2016In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 5, p. 1619-1631Article in journal (Refereed)
    Abstract [en]

    We consider the crucial problem of maximizing the system-wide performance which takes into account request processing throughput, smartphone user experience and system stability in a participatory sensing system with cooperative smartphones. Three important controls need to be made, i.e., 1) request admission control, 2) task allocation, and 3) task scheduling on smartphones. It is highly challenging to achieve the optimal system-wide performance, given arbitrary unknown arrivals of sensing requests, intrinsic tradeoff between request processing throughput and smartphone user experience degradation, and heterogenous requests. Little existing work has studied this crucial problem of maximizing the system-wide performance of a participatory sensing system as a whole. In response to the challenges, we propose an optimal online control approach to maximize the system-wide performance of a participatory sensing system. Exploiting the stochastic Lyapunov optimization techniques, it derives the optimal online control strategies for request admission control, task allocation and task scheduling on smartphones. The most salient feature of our approach is that the achieved system-wide performance is arbitrarily close to the optimum, despite unpredictable and arbitrary request arrivals. Rigorous theoretical analysis and comprehensive simulation evaluation jointly demonstrate the efficacy of our online control approach.

  • 84.
    Liu, Xiao
    et al.
    School of Information Science and Engineering, Central South University, ChangSha .
    Zhao, Shaona
    School of Information Science and Engineering, Central South University, ChangSha .
    Liu, Anfeng
    School of Information Science and Engineering, Central South University, ChangSha .
    Xiong, Naixue
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Knowledge-aware Proactive Nodes Selection approach for energy management in Internet of Things2017In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115Article in journal (Refereed)
    Abstract [en]

    Internet of Things will serve communities across the different domains of life. Tracking mobile targets is one important system engineering application in IOT, and the resource of embedded devices and objects working under IoT implementation are constrained. Thus, building a scheme to make full use of energy is key issue for mobile target tracking applications. To achieve both energy efficiency and high monitoring performance, an effective Knowledge-aware Proactive Nodes Selection (KPNS) system is proposed in this paper. The innovations of KPNS are as follows: 1) the number of proactive nodes are dynamically adjusted based on prediction accuracy of target trajectory. If the prediction accuracy is high, the number of proactive nodes in the non-main predicted area will be decreased. If prediction accuracy of moving trajectory is low, large number of proactive nodes will be selected to enhance monitoring quality. 2) KPNS takes full advantage of energy to further enhance target tracking performance by properly selecting more proactive nodes in the network. We evaluated the efficiency of KPNS with both theory analysis and simulation based experiments. The experimental results demonstrate that compared with Probability-based target Prediction and Sleep Scheduling strategy (PPSS), KPNS scheme improves the energy efficiency by 60%, and can reduce target missing rate and tracking delay to 66%, 75% respectively.

  • 85.
    Liu, Yongxin
    et al.
    South China University of Technology.
    Wang, Xiaoxiong
    South China University of Technology.
    Wan, Jiafu
    South China University of Technology.
    Xue, Xuejun
    South China Agricultural University.
    Song, Houbing
    West Virginia University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Exploring data validity in transportation systems for smart cities2017In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 55, no 5, p. 26-33, article id 7926913Article in journal (Refereed)
    Abstract [en]

    Efficient urban transportation systems are widely accepted as essential infrastructure for smart cities, and they can highly increase a city°s vitality and convenience for residents. The three core pillars of smart cities can be considered to be data mining technology, IoT, and mobile wireless networks. Enormous data from IoT is stimulating our cities to become smarter than ever before. In transportation systems, data-driven management can dramatically enhance the operating efficiency by providing a clear and insightful image of passengers° transportation behavior. In this article, we focus on the data validity problem in a cellular network based transportation data collection system from two aspects: Internal time discrepancy and data loss. First, the essence of time discrepancy was analyzed for both automated fare collection (AFC) and automated vehicular location (AVL) systems, and it was found that time discrepancies can be identified and rectified by analyzing passenger origin inference success rate using different time shift values and evolutionary algorithms. Second, the algorithmic framework to handle location data loss and time discrepancy was provided. Third, the spatial distribution characteristics of location data loss events were analyzed, and we discovered that they have a strong and positive relationship with both high passenger volume and shadowing effects in urbanized areas, which can cause severe biases on passenger traffic analysis. Our research has proposed some data-driven methodologies to increase data validity and provided some insights into the influence of IoT level data loss on public transportation systems for smart cities.

  • 86.
    Liu, Yuhong
    et al.
    Department of Information Science and Technology, Penn State Altoona.
    Sun, Yan
    Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island.
    Ryoo, Jungwoo
    Department of Information Science and Technology, Penn State Altoona.
    Rizvi, Syed S.
    Department of Information Science and Technology, Penn State Altoona.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A survey of security and privacy challenges in cloud computing: Solutions and future directions2015In: Journal of Computing Science and Engineering, ISSN 1976-4677, E-ISSN 2093-8020, Vol. 9, no 3, p. 119-133Article in journal (Refereed)
    Abstract [en]

    While cloud computing is gaining popularity, diverse security and privacy issues are emerging that hinder the rapid adoption of this new computing paradigm. And the development of defensive solutions is lagging behind. To ensure a secure and trustworthy cloud environment it is essential to identify the limitations of existing solutions and envision directions for future research. In this paper, we have surveyed critical security and privacy challenges in cloud computing, categorized diverse existing solutions, compared their strengths and limitations, and envisioned future research directions.

  • 87.
    Luo, Hongmin
    et al.
    School of Computer Science and Engineering, Beihang University, Beijing.
    Chen, Zhe
    Huawei Technologies.
    Li, Jiawei
    School of Electronic and Information Engineering, Beijing Jiaotong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Preventing Distributed Denial-of-Service Flooding Attacks with Dynamic Path Identifiers2017In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 12, no 8, p. 1801-1805, article id 7888484Article in journal (Refereed)
    Abstract [en]

    In recent years, there are increasing interests in using path identifiers (PIDs) as inter-domain routing objects. However, the PIDs used in existing approaches are static, which makes it easy for attackers to launch distributed denial-ofservice (DDoS) flooding attacks. To address this issue, in this paper, we present the design, implementation, and evaluation of D-PID, a framework that uses PIDs negotiated between neighboring domains as inter-domain routing objects. In DPID, the PID of an inter-domain path connecting two domains is kept secret and changes dynamically. We describe in detail how neighboring domains negotiate PIDs, how to maintain ongoing communications when PIDs change. We build a 42-node prototype comprised by six domains to verify D-PID’s feasibility and conduct extensive simulations to evaluate its effectiveness and cost. The results from both simulations and experiments show that D-PID can effectively prevent DDoS attacks.

  • 88.
    Makkie, Milad
    et al.
    Computer Science Department, University of Georgia, Athens, GA, USA.
    Huang, Heng
    School of Automation, Northwestern Polytechnical University, Xi'an, China.
    Zhao, Yu
    Computer Science Department, University of Georgia, Athens, GA, USA.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Liu, Tianming
    Harvard Center for Neurodegeneration and Repair, Boyd GSRC 420, Athens, GA 30602, United States.
    Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics2018In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286Article in journal (Refereed)
    Abstract [en]

    In recent years, analyzing task-based fMRI (tfMRI) data has become an essential tool for understanding brain function and networks. However, due to the sheer size of tfMRI data, its intrinsic complex structure, and lack of ground truth of underlying neural activities, modeling tfMRI data is hard and challenging. Previously proposed data modeling methods including Independent Component Analysis (ICA) and Sparse Dictionary Learning only provided shallow models based on blind source separation under the strong assumption that original fMRI signals could be linearly decomposed into time series components with corresponding spatial maps. Given the Convolutional Neural Network (CNN) successes in learning hierarchical abstractions from low-level data such as tfMRI time series, in this work we propose a novel scalable distributed deep CNN autoencoder model and apply it for fMRI big data analysis. This model aims to both learn the complex hierarchical structures of the tfMRI big data and to leverage the processing power of multiple GPUs in a distributed fashion. To deploy such a model, we have created an enhanced processing pipeline on the top of Apache Spark and Tensorflow, leveraging from a large cluster of GPU nodes over cloud. Experimental results from applying the model on the Human Connectome Project (HCP) data show that the proposed model is efficient and scalable toward tfMRI big data modeling and analytics, thus enabling data-driven extraction of hierarchical neuroscientific information from massive fMRI big data.

  • 89.
    Mashayekhy, Lena
    et al.
    Department of Computer Science, Wayne State University, Detroit.
    Nejad, Mahyar Movahed
    Department of Computer Science, Wayne State University, Detroit.
    Grosu, Daniel
    Department of Computer Science, Wayne State University, Detroit.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Online Mechanism for Resource Allocation and Pricing in Clouds2016In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 4, p. 1172-1184Article in journal (Refereed)
    Abstract [en]

    Cloud providers provision their various resources such as CPUs, memory, and storage in the form of virtual machine (VM) instances which are then allocated to the users. The users are charged based on a pay-as-you-go model, and their payments should be determined by considering both their incentives and the incentives of the cloud providers. Auction markets can capture such incentives, where users name their own prices for their requested VMs. We design an auction-based online mechanism for VM provisioning, allocation, and pricing in clouds that considers several types of resources. Our proposed online mechanism makes no assumptions about future demand of VMs, which is the case in real cloud settings. The proposed online mechanism is invoked as soon as a user places a request or some of the allocated resources are released and become available. The mechanism allocates VM instances to selected users for the period they are requested for, and ensures that the users will continue using their VM instances for the entire requested period. In addition, the mechanism determines the payment the users have to pay for using the allocated resources. We prove that the mechanism is incentive-compatible, that is, it

  • 90.
    Mehboob, Usama
    et al.
    School of EE and CS, National University of Sciences and Technology (NUST), Islamabad.
    Qadir, Junaid
    Department of Electrical Engineering, Information Technology University (ITU), Punjab.
    Ali, Salman
    School of EE and CS, National University of Sciences and Technology (NUST), Islamabad.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Genetic algorithms in wireless networking: techniques, applications, and issues2016In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 20, no 6, p. 2467-2501Article in journal (Refereed)
    Abstract [en]

    In recent times, wireless access technology is becoming increasingly commonplace due to the ease of operation and installation of untethered wireless media. The design of wireless networking is challenging due to the highly dynamic environmental condition that makes parameter optimization a complex task. Due to the dynamic, and often unknown, operating conditions, modern wireless networking standards increasingly rely on machine learning and artificial intelligence algorithms. Genetic algorithms (GAs) provide a well-established framework for implementing artificial intelligence tasks such as classification, learning, and optimization. GAs are well known for their remarkable generality and versatility and have been applied in a wide variety of settings in wireless networks. In this paper, we provide a comprehensive survey of the applications of GAs in wireless networks. We provide both an exposition of common GA models and configuration and provide a broad-ranging survey of GA techniques in wireless networks. We also point out open research issues and define potential future work. While various surveys on GAs exist in the literature, our paper is the first paper, to the best of our knowledge, which focuses on their application in wireless networks.

  • 91.
    Meng, Tong
    et al.
    Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
    Wu, Fan
    Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
    Yang, Zheng
    School of Software, Tsinghua University.
    Chen, Guihai
    Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Spatial Reusability-Aware Routing in Multi-Hop Wireless Networks2016In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 1, p. 244-255Article in journal (Refereed)
    Abstract [en]

    In the problem of routing in multi-hop wireless networks, to achieve high end-to-end throughput, it is crucial to find the "best" path from the source node to the destination node. Although a large number of routing protocols have been proposed to find the path with minimum total transmission count/time for delivering a single packet, such transmission count/time minimizing protocols cannot be guaranteed to achieve maximum end-to-end throughput. In this paper, we argue that by carefully considering spatial reusability of the wireless communication media, we can tremendously improve the end-to-end throughput in multi-hop wireless networks. To support our argument, we propose spatial reusability-aware single-path routing (SASR) and anypath routing (SAAR) protocols, and compare them with existing single-path routing and anypath routing protocols, respectively. Our evaluation results show that our protocols significantly improve the end-to-end throughput compared with existing protocols. Specifically, for single-path routing, the median throughput gain is up to 60 percent, and for each source-destination pair, the throughput gain is as high as 5.3x; for anypath routing, the maximum per-flow throughput gain is 71.6 percent, while the median gain is up to 13.2 percent

  • 92.
    Meng, Weizhi
    et al.
    Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.
    Raymond Choo, Kim-Kwang
    Department of Information Systems and Cyber Security and the Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, United States.
    Furnell, Steven
    School of Computing, Electronics and Mathematics, Plymouth University, United Kindom.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Probst, Christian W.
    Unitec Institute of Technology, New Zealand.
    Towards Bayesian-based Trust Management for Insider Attacks in Healthcare Software-Defined Networks2018In: IEEE Transactions on Network and Service Management, ISSN 1932-4537, E-ISSN 1932-4537, Vol. 15, no 2, p. 761-773Article in journal (Refereed)
    Abstract [en]

    The medical industry is increasingly digitalized and Internet-connected (e.g., Internet of Medical Things), and when deployed in an Internet of Medical Things environment, software-defined networks (SDN) allow the decoupling of network control from the data plane. There is no debate among security experts that the security of Internet-enabled medical devices is crucial, and an ongoing threat vector is insider attacks. In this paper, we focus on the identification of insider attacks in healthcare SDNs. Specifically, we survey stakeholders from 12 healthcare organizations (i.e., two hospitals and two clinics in Hong Kong, two hospitals and two clinics in Singapore, and two hospitals and two clinics in China). Based on the survey findings, we develop a trust-based approach based on Bayesian inference to figure out malicious devices in a healthcare environment. Experimental results in either a simulated and a real-world network environment demonstrate the feasibility and effectiveness of our proposed approach regarding the detection of malicious healthcare devices, i.e., our approach could decrease the trust values of malicious devices faster than similar approaches.

  • 93.
    Moetesum, Momina
    et al.
    Department of Computer Science, Bahria University, Islamabad.
    Hadi, Fazle
    Department of Computer Science, Bahria University, Islamabad.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Minhas, Abid Ali
    Department of Computer Science, Bahria University, Islamabad.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An adaptive and efficient buffer management scheme for resource-constrained delay tolerant networks2016In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 22, no 7, p. 2189-2201Article in journal (Refereed)
    Abstract [en]

    Provisioning buffer management mechanism is especially crucial in resource-constrained delay tolerant networks (DTNs) as maximum data delivery ratio with minimum overhead is expected in highly congested environments. However, most DTN protocols do not consider resource limitations (e.g., buffer, bandwidth) and hence, results in performance degradation. To strangle and mitigate the impact of frequent buffer overflows, this paper presents an adaptive and efficient buffer management scheme called size-aware drop (SAD) that strives to improve buffer utilization and avoid unnecessary message drops. To improve data delivery ratio, SAD exactly determines the requirement based on differential of newly arrived message(s) and available space. To vacate inevitable space from a congested buffer, SAD strives to avoid redundant message drops and deliberate to pick and discard most appropriate message(s) to minimize overhead. The performance of SAD is validated through extensive simulations in realistic environments (i.e., resource-constrained and congested) with different mobility models (i.e., Random Waypoint and disaster). Simulation results demonstrate the performance supremacy of SAD in terms of delivery probability and overhead ratio besides other metrics when compared to contemporary schemes based on Epidemic (DOA and DLA) and PRoPHET (SHLI and MOFO).

  • 94.
    Mohd, Bassam Jamil
    et al.
    Computer Engineering Department, Hashemite University.
    Hayajneh, Thaier
    School of Engineering and Computing Sciences, New York Institute of Technology.
    Khalaf, Zaid Abu
    School of Engineering and Computing Sciences, New York Institute of Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A comparative study of steganography designs based on multiple FPGA platforms2016In: International Journal of Electronic Security and Digital Forensics, ISSN 1751-911X, E-ISSN 1751-9128, Vol. 8, no 2, p. 164-190Article in journal (Refereed)
    Abstract [en]

    Steganography methods conceal covert messages inside communicated data. Field-programmable gate array (FPGA) hardware implementation provides speed, flexibility and configurability. It is extremely difficult to compare published results from different platforms and technologies. The goal of our research work is to mitigate the dependency by examining implementations from multiple FPGA platforms. The research studies the implementations of 12 spatial steganography methods using Altera and Xilinx FPGAs. The methods include mix-bit LSB, least significant bit (LSB), random LSB and texture-based algorithms. The objective of the research is to develop platform-independent resources, timing, power and energy models; to empower future steganography research. Further, the article evaluates steganography methods using typical performance metrics as well as a novel performance metric. The results suggest that the mix-bit methods exhibit good performance across most of the metrics. However, when image quality is a concern, the two-bit LSB is the front runner

  • 95.
    Mohd, Bassam Jamil
    et al.
    Computer Engineering Department, Hashemite University.
    Hayajneh, Thaier
    School of Engineering and Computing Sciences, New York Institute of Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A survey on lightweight block ciphers for low-resource devices: Comparative study and open issues2015In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 58, p. 73-93Article in journal (Refereed)
    Abstract [en]

    This paper investigates the lightweight block ciphers' implementations, which have received a fair amount of research for their essential security role in low-resource devices. Our objective is to present a comprehensive review of state-of-the-art research progress in lightweight block ciphers' implementation and highlight future research directions. At first, we present taxonomy of the cipher design space and accurately define the scope of lightweight ciphers for low-resource devices. Moreover, this paper discusses the performance metrics that are commonly reported in the literature when comparing cipher implementations. The sources of inaccuracies and deviations are carefully examined. In order to mitigate the confusion in the composite metrics, we developed a general metric which includes the basic metrics. Our analysis designated the energy/bit metric as the most appropriate metric for energy-constrained low-resource designs. Afterwards, the software and hardware implementations of the block cipher algorithms are surveyed, investigated, and compared. The paper selects the top performing ciphers in various metrics and suggests the Present cipher as a good reference for hardware implementations. What transpires from this survey is that unresolved research questions and issues are yet to be addressed by future research projects.

  • 96.
    Niu, Hao
    et al.
    Institute of Industrial Science, University of Tokyo.
    Zhu, Nanhao
    CETC Group, GCI Science and Technology Co.
    Sun, Li
    Department of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Sezaki, Kaoru
    Institute of Industrial Science, University of Tokyo.
    Security-embedded opportunistic user cooperation with full diversity2016In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 22, no 5, p. 1513-1522Article in journal (Refereed)
    Abstract [en]

    As a promising technique for wireless networks, cooperative communications is coming to maturity in both theory and practice. The main merit of the cooperation technique is its capability in providing additional transmission links to harvest the spatial diversity gain at the physical layer. However, due to the broadcast nature of wireless medium, the diversity gain can be also freely achieved at the potential eavesdropper if the cooperation is performed blindly. To solve this problem, we propose a security-embedded opportunistic user cooperation scheme (OUCS) in this paper. The OUCS first defines a concept called secrecy-providing capability (SPC) for both the source and the cooperative relays. By comparing the values of SPC of these nodes, the OUCS jointly decides whether to cooperate and with whom to cooperate from the perspective of physical layer security. The secrecy outage performance of the OUCS is then derived. From the results we prove that full diversity can be achieved (i.e., the diversity order is N + 1 for N cooperative relays), which outperforms existing alternatives. Finally, numerical results are provided to validate the theoretical analysis.

  • 97.
    Pace, Pasquale
    et al.
    University of Calabria.
    Loscri, Valeria
    Inria Lille-Nord Europe/FUN.
    Zheng, Zhengguo
    University of Sussex.
    Ruggeri, Guiseppe
    University Mediterranea of Reggio Calabria.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Smart Wireless Access Networks and Systems for Smart Cities2016In: Ad hoc networks, ISSN 1570-8705, E-ISSN 1570-8713, Vol. 43, p. 1-2Article in journal (Other academic)
  • 98.
    Pan, Linqiang
    et al.
    Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan.
    Wu, Tingfang
    Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan.
    Su, Yansen
    Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cell-like spiking neural P systems with request rules2017In: IEEE Transactions on Nanobioscience, ISSN 1536-1241, E-ISSN 1558-2639, Vol. 16, no 6, p. 513-522Article in journal (Refereed)
    Abstract [en]

    Cell-like spiking neural P systems (in short, cSN P systems) are a class of distributed and parallel computation models inspired by both the way in which neurons process information and communicate to each other by means of spikes and the compartmentalized structures of living cells. cSNP systems have been proved to be Turing universal if more spikes can be produced by consuming some spikes or spikes can be replicated. In this work, in order to answer the open problem whether this functioning of producing more spikes and replicating spikes can be avoided by using some strategy without the loss of computation power, we introduce cSN P systems with request rules, which have classical spiking rules and forgetting rules, and also request rules in the skin membrane. The skin membrane can receive spikes from the environment by the application of request rules. cSN P systems with request rules are proved to be Turing universal. The results show that the decrease of computation power caused by removing the internal functioning of producing spikes and replicating spikes can be compensated by request rules, which suggests that the communication between a cell and the environment is an essential ingredient of systems in terms of computation power.

  • 99.
    Pavone, Mario
    et al.
    Department of Mathematics and Computer Science, University of Catania.
    Ramadan, Rabie A.
    Computer Engineering Department, Faculty of Engineering, Cairo University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Intelligent cloud computing2016In: Memetic Computing, ISSN 1865-9284, E-ISSN 1865-9292, Vol. 8, no 4, p. 253-254Article in journal (Refereed)
  • 100.
    Perera, Charith
    et al.
    The Open University, UK.
    Qin, Yongrui
    University of Huddersfield, UK.
    Estrella, Julio C.
    University of Sao Paulo.
    Reiff-Marganiec, Stephan
    University of Leicester, UK.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fog Computing for Sustainable Smart Cities: A Survey2017In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 50, no 3, article id 32Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, especially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g., network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build a sustainable IoT infrastructure for smart cities. In this article, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges toward implementing them, to shed light on future research directions on realizing Fog computing for building sustainable smart cities.

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