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  • 101.
    Jayaputera, Glenn
    et al.
    Dynamically generated user-specified MAS.
    Zaslavsky, Arkady
    Loke, Seng Wai
    Dynamically generated user-specified MAS.
    Dynamically generated user-specified MAS2006Inngår i: Agent-Oriented Software Engineering VI: 6th international workshop, AOSE 2005, Utrecht, The Netherlands, July 25, 2005 ; revised and invited papers / [ed] Jörg P. Müller; Franco Zambonelli, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2006, s. 139-153Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents an innovative multi-agent system development approach called mission-based on-demand agent generation. This approach allows agents to be dynamically composed at run-time and most importantly, only when needed. Such an approach is different from the conventional one, where agents are generally composed at design time. Our model of a mission allows the MAS to be suspended and resumed at later stage at the same or different location. We present the formal model of the mission, the strategy to execute the mission and the architecture of the prototype system called eHermes. Finally, we report the experimental results that shows that eHermes handles the load satisfactorily and performs the run-time optimization well.

  • 102.
    Jayaputera, G.T.
    et al.
    Caulfield School of Information Technology, Monash University.
    Loke, Sang Wai
    Department of Computer Science and Computer Engineering, La Trobe University.
    Zaslavsky, Arkady
    Design, implementation and run-time evolution of a mission-based multiagent system2007Inngår i: Web Intelligence and Agent Systems, ISSN 1570-1263, E-ISSN 1875-9289, Vol. 5, nr 2, s. 139-159Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we present our approach to developing a multiagent system based on the proposed concept of the mission. The mission is a high-level abstraction that combines the overall goal of a system, the means and the process of achieving that goal, and is the basis from which agents can be automatically generated. We propose a mechanism to generate agents on-demand and at run-time based on a given mission. Run-time mission evolution is systematically captured and maintained, allowing the mission to be suspended and resumed at a later stage at the same or different locations. We report on the theory, algorithm, implementation and experimental results of our research.

  • 103.
    Jayaraman, Prem Prakash
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Cost efficient data collection of sensory originated data using context-aware mobile devices2008Inngår i: 2008 Ninth International Conference on Mobile Data Management workshops: MDMW ; Beijing, China, 27 - 30 April 2008, Piscataway, NJ: IEEE Communications Society, 2008, s. 190-197Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Sensory originated data collection and processing has always been a big challenge in wireless sensor networks (WSN). WSN represent a distributed producer of large amount of valuable data required by varied number of applications. In this paper we propose the use of context aware data mules (CADAMULE) as a solution for smart data collection within sensor networks. We present an extension to Context Spaces modelling theory by incorporating context discovery at runtime. This facilitates our system to discover new context attributes by looking into previous situations and events when pre-defined context is not sufficient for the reasoning process. We use this model as a base to provide contextual information to the mobile data mule whose spare capacity for communication and processing can be used to collect and process sensor data. The focus of the paper is to propose and evaluate a cost-efficient data collection technique which uses a cost formula computed from the context information obtained by the system. We validate our system by a simulation in which we try to reason out and identify the best and also the most cost efficient data mule. The context aware data mule negotiates with the sensor node collecting and delivering the data to the sink

  • 104.
    Jayaraman, Prem Prakash
    et al.
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Cost-efficient data collection approach using K-nearest neighbors in a 3D sensor network2010Inngår i: 11th IEEE International Conference on Mobile Data Management, MDM 2010, Piscataway, NJ: IEEE Communications Society, 2010, s. 183-188Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Sensor networks represent an important component of distributed infrastructure supplying raw data to various applications from military to healthcare. A key challenge is costefficient collection of distributed data streaming from those sensor networks. In this paper we propose the use of mobile data collectors that employ K-NN queries as a cost-efficient approach to collect data within the sensor network. We investigate a 3D sensor network and propose a cost-efficient 3D-KNN algorithm that uses minimal energy and communication overheads to compute k-nearest neighbors. The 3D-KNN algorithm uses a 3 dimensional plane rotation algorithm that maps sensor nodes on a 3D plane to a reference plane identified by the mobile data collector. We propose a cost-efficient KNN boundary estimation algorithm that computes KNN boundary based on network density. We also propose a neighbor prediction algorithm that uses distance, signal to noise ratio and mobile data collector's trajectory information to identify sensor nodes along the mobile data collector's path. We simulate the proposed 3D-KNN algorithm using GlomoSim and validate its cost efficiency by evaluating its energy efficiency and query latency. Lessons and results of extensive simulation conclude the paper

  • 105.
    Jayaraman, Prem Prakash
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Coverage area computation on the run for efficient sensor data collection2008Inngår i: New technologies, mobility and security: proceedings of NTMS '2008 conference and workshops ; [held in Tangier, Morocco during November 5 - November 7 2008] / [ed] Akshai Aggarwal, Piscataway, NJ: IEEE Communications Society, 2008Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Wireless sensor networks have emerged as a key area of research in recent years. With the dominance of ubiquitous and pervasive era of computing, these networks present a rich infrastructure for valuable information. In this paper we focus on efficient data collection in sensor networks by proposing an algorithm to compute a coverage (collection) area using smart mobile objects. The algorithm proposed computes a collection area dynamically covering nodes around the mobile objects current location. It uses a weighed graph technique to identify nodes from which data can be collected efficiently by the mobile object discarding the rest. The proposed algorithm computes the collection area using Voronoi Diagrams and Delaunay triangle. We validate the proposed algorithm by simulating the algorithm over a Bluetooth based sensor network. We also evaluate the algorithms efficiency to compute the coverage area by changing the mobile objects context parameters.

  • 106.
    Jayaraman, Prem Prakash
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Intelligent mobile data mules for cost-efficient sensor data collection2010Inngår i: International Journal of Next-Generation Computing, ISSN 2229-4678, E-ISSN 0976-5034, Vol. 1, nr 1Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Sensor networks represent an important component of distributed pervasive infrastructure. A key challenge facing sensor networks is cost-effcient collection of data streaming from these distributed data sites. In this paper, we present a mobile data mule-based sensor data collection approach employing K-Nearest Neighbours queries. We propose a novel 3D-KNN algorithm that dynamically computes nearest sensors spread within a 3D environment around the data mule. The 3D-KNN algorithm incorporates a novel boundary estimation and neighbour selection algorithm to compute the nearest neighbour set. Further, we propose a neighbour prediction algorithm that computes sensor locations within the vicinity of the data mules' trajectory. We simulate the proposed 3D-KNN algorithm using GlomoSim validating its cost-effciency by extensive evaluations. Results of our simulations conclude the paper.

  • 107.
    Jayaraman, Prem Prakash
    et al.
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Intelligent processing of K-nearest neighbors queries using mobile data collectors in a location aware 3D wireless sensor network2010Inngår i: Trends in applied intelligent systems: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1 - 4, 2010 ; proceedings, part III / [ed] Nicolás García-Pedrajas; Francisco Herrera; Colin Fyfe; José Manuel Benítez; Moonis Ali, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2010, s. 260-270Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The increased acceptance of sensor networks into everyday pervasive environments has lead to the creation of abundant distributed resource constrained data sources. In this paper, we propose an intelligent mobile data collector-based K-Nearest Neighbor query processing algorithm namely 3D-KNN. The K-Nearest Neighbor query is an important class of query processing approach in sensor networks. The proposed algorithm is employed over a sensor network that is situated within a 3 dimensional space. We propose a novel boundary estimation algorithm which computes an energy efficient sensor boundary that encloses at least k nearest nodes. We then propose a 3D plane rotation algorithm that maps selected sensor nodes on different planes onto a reference plane and a novel k nearest neighbor selection algorithm based on node distance and signal-to-noise ratio parameters. We have implemented the 3D-KNN algorithm in GlomoSim and validate the proposed algorithm's cost efficiency by extensive performance evaluation over well defined system criteria

  • 108.
    Jayaraman, Prem Prakash
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    On-the-fly situation composition within smart spaces2009Inngår i: Smart Spaces and Next Generation Wired/Wireless Networking: 9th International Conference, NEW2AN 2009 and Second Conference on Smart Spaces, ruSMART 2009, St. Petersburg, Russia, September 15-18, 2009. Proceedings / [ed] Sergey Balandin; Dmitri Moltchanev; Yevgeni Koucheryavy, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2009, s. 52-65Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Advances in pervasive computing systems have made smart computing spaces a reality. These smart spaces are sources of large amount of data required for context aware pervasive applications to function autonomously. In this paper we present a situation aware reasoning system that composes situations at runtime based on available  information from the smart spaces. Our proposed system R-CS uses situation composition on-the-fly to compute temporal situations that best represent the real world situation (contextual information). Our proposed situation composition algorithm is dependent on underlying sensor data (hardware and software). These sensory data are prone to errors like inaccuracy, old data, data ambiguity etc. R-CS proposes algorithms that incorporate sensor data errors estimation techniques into our proposed dynamic situation composition based reasoning system. R-CS is built as an extension to Context Spaces, a fixed situation set based reasoning system. We implement R-CS dynamic situation composition algorithms over context spaces and validate our proposed R-CS model against context spaces' fixed situation reasoning model.

  • 109.
    Jayaraman, Prem Prakash
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Sensor data collection using heterogeneous mobile devices2007Inngår i: 2007 IEEE International Conference on Pervasive Services: [ICPS '07] ; Istanbul, Turkey, 15 - 20 July 2007, Piscataway, NJ: IEEE Communications Society, 2007, s. 161-164Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Data collection has always been a major challenge in sensor networks and various techniques have been proposed to enable efficient data collection. One such methodology is the use of mobile elements within the existing infrastructure to enable data collection. The paper proposes the use of existing mobile elements like mobile phones which have enough spare capacity to act as data carriers within a sensor network to carry sensor data. With advent of technology, mobile devices have become so powerful that they can work in a pervasive environment and make decisions based on context information like presence, location etc. Our proposal is an intelligent heterogeneous network in which the sensor nodes act as the data accumulators and the context-aware mobile phones act as data carriers of the sensed data. A framework that enables the mobile node and sensor node communication over Bluetooth is proposed and a p implementation is presented.

  • 110.
    Jayaraman, Prem Prakash
    et al.
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Smart sensing and sensor data collection on the move for modelling intelligent environments2008Inngår i: Next Generation Teletraffic and Wired/Wireless Advanced Networking: 8th International Conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART 2008, St. Petersburg, Russia, September 3-5, 2008. Proceedings / [ed] Sergey Balandin; Dimitri Moltchanov; Yevgeni Koucheryavy, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2008, s. 306-317Konferansepaper (Fagfellevurdert)
    Abstract [en]

    With advent of pervasive computing and considerable acceptance of sensor networks, smart sensing techniques and data collection have been topics of interest. This paper presents a smart sensing and data collection technique from sensor networks using context aware high powered mobile objects within the environment. The paper proposes CAM-R a context aware robot that can move within smart environments sensing new sensor sources and collecting sensory originated data efficiently. Based on these sensed data sources, we propose an extension to context spaces model that builds a virtual model of the intelligent environment. This intelligent environment model built using extended context spaces can be used by number of context aware applications to efficiently query and retrieve data from the sensor network using CAM-R based data collection approach. We also present a prototype implementation of CAM-R built using off-the-shelf hardware and a context based cost function used to compute data collection decisions. We validate our system by implementing the virtual modelling of the intelligent environment based on simulated input obtained from CAM-R and sensors. We also evaluate CAM-Rby simulating and comparing the energy spent by the sensor nodes during data collection process using our proposed approach and traditional fixed sink based approach.

  • 111.
    Jayaraman, Prem
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Dynamic situation modeling and reasoning under uncertainty2009Inngår i: AUPC '09: ICPS 2009 & co-located workshops compilation proceedings, July 13-16, 2009, Imperial College, London, UK, New York: ACM Digital Library, 2009, s. 113-122Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Reasoning under uncertainty is a key challenge in context aware pervasive systems. In this paper we propose R-CS a situation based context reasoning model that employs ranking technique to rank and order context attributes. Using the proposed ranking technique and available context information, we compute dynamic situation spaces (a collection of contextual attributes that best represent a real world situation) We also propose and incorporate multilevel hierarchical contextual regions into R-CS that enables situation reasoning to be based on one or more dependent context attributes. We present a theoretical approach to compute importance and relevance of newly discovered context attributes which are not defined within the situation space definition by employing the approach of investigating similar neighboring situation spaces. R-CS builds on context spaces theory, a context model based on situation reasoning. We have implemented the proposed algorithms/approaches into R-CS and have validated them by evaluating against context spaces reasoning model.

  • 112.
    Kang, Yong-Bin
    et al.
    Faculty of Information Technology, Monash University.
    Krishnaswamy, Shonali
    Faculty of Information Technology, Monash University.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    A retrieval strategy using the integrated knowledge of similarity and associations2011Inngår i: Database systems for advanced applications: 16th international conference, DASFAA 2011, Hong Kong, China, April 22-25, 2011 : proceedings / [ed] Jeffrey Xu Yu; Myoung Ho Kim; Rainer Unland, Heidelberg: Encyclopedia of Global Archaeology/Springer Verlag, 2011, s. 16-30Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Retrieval is often considered the most important task in Case-Based Reasoning (CBR), since it lays the foundation for overall performance of CBR systems. In CBR, a typical retrieval strategy is realized through similarity knowledge encoded in similarity measures. This strategy is often called similarity-based retrieval (SBR). This paper proposes and validates that association analysis techniques can be used to improve SBR. We propose a retrieval strategy USIMSCAR that performs the retrieval task by integrating similarity and association knowledge. We show its reliability, in comparison with several retrieval methods implementing SBR, using datasets from UCI ML Repository

  • 113.
    Kang, Yong-Bin
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Krishnaswamy, Shonali
    Monash University, Melbourne, VIC.
    Bartolini, Claudio
    HP Labs, Palo-Alto.
    A computer-facilitated method for matching incident cases using semantic similarity measurement2009Inngår i: 2009 IFIP/IEEE International Symposium on Integrated Network Management: IM 2009 ; [Hofstra University, Hempstead], New York, NY, USA, 1 - 5 June 2009, Piscataway, NJ: IEEE Communications Society, 2009, s. 10-19Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents a new computer-facilitated approach for incident management to improve typical incident management. Our approach automates typical manual-based incident resolution process by proposing a new semantic similarity measurement between a given incident call and incident cases stored already in a case base. The proposed semantic similarity measurement distinguishes traditional similarity measures by incorporating additional useful information and exploiting semantic knowledge about features appeared in two incident descriptions to be compared. First, we state how typical incident management is processed and what its problems are. We then propose our automated incident resolution process with its core components. After that we introduce our identified additional useful information for our similarity measurement and describe how our similarity measurement algorithm is carried out. In an experimental evaluation, we show the technical coherence and feasibility of the proposed solution using a real dataset.

  • 114.
    Kang, Yong-Bin
    et al.
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Krishnaswamy, Shonali
    Caulfield School of Information Technology, Monash University.
    Bartolini, Claudio
    HP Labs, Palo-Alto.
    A knowledge-rich similarity measure for improving IT incident resolution process2010Inngår i: Proceedings of the 25th Annual ACM Symposium on Applied Computing 2010: Sierre, Switzerland, March 22 - 26, 2010, New York: ACM Digital Library, 2010, s. 1781-1788Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The aim of incident management is to restore a given IT service disruption, simply called incident, to normal state as quickly as possible. In incident management, it is essential to resolve a new incident efficiently and accurately. However, typically, incident resolution process is largely manual, thus, it is time-consuming and error-prone. This paper proposes a new knowledge-rich similarity measure for improving this process. The role of this measure is to retrieve the most similar past incident cases for a new incident without human intervention. The solution information contained the retrieved incident cases can be utilized to resolve the new incident. The main feature of our similarity measure is to incorporate additional useful meta knowledge, outside of incident description that is the only exploited information in typical similarity measures used in CBR, to improve effectiveness. Moreover, this measure exploits as much semantic knowledge as possible about features contained in previous incident cases. Through an experimental evaluation, we show the effectiveness, technical coherence and feasibility of this measure using a real dataset

  • 115. Kodikara, E. Ruwini
    et al.
    Brännström, Robert
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Åhlund, Christer
    Zaslavsky, Arkady
    APM: Adaptive Performance Metric2006Konferansepaper (Annet vitenskapelig)
  • 116. Kodikara, R.E.
    et al.
    Mitra, Karan
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Context aware vertical handovers in next generation networks2006Inngår i: Proceedings of HiPC Workshops 2006, 2006Konferansepaper (Fagfellevurdert)
  • 117.
    Kodikara, R.E
    et al.
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Åhlund, Christer
    ConEx: context exchange in MANETs for real time multimedia2006Inngår i: International Conference on Networking: ICN 2006 ; Morne, Mauritius, 23 - 28 April, 2006 ; bonus: International Conference on Mobile Communications and Learning Technologies (MCL 2006), International Conference on Systems (ICONS 2006) ; proceedings / [ed] Pascal Lorenz, Los Alamitos, Calif: IEEE Computer Society Press , 2006, s. 70-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    MANETs are important and integral part of next generation wireless networking. Real time multimedia communication over MANETs is challenging due to reasons like network topology changes, limitations of wireless links and demanding requirements of multimedia. Channel adaptivity is adopting applications to the dynamic and unpredictable network conditions. QoS adaptivity is adopting lower layers to multimedia application requirements. The novel cross layer context exchange approach called ConEx, presented in this paper improves the efficiency of this two-way information exchange. This paper focuses on adaptive multimedia applications over mobile ad hoc networks, which addresses the challenges of multimedia applications. ConEx uses publish-subscribe event notification system for vertical context exchange across layers of the mobile host and horizontal context exchange across the MANET. ConEx architecture and implementation issues are discussed in this paper.

  • 118.
    Kodikara, Ruwini E.
    et al.
    Centre for Distributed Systems and Software Engineering, Monash University.
    Åhlund, Christer
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Towards context aware adaptation in wireless networks2008Inngår i: Proceedings: The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, UBICOMM 2008 : 29 September - 4 October 2008, Valencia, Spain / [ed] Jaime Lloret Mauri, Piscataway, NJ: IEEE Communications Society, 2008, s. 245-250Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Next generation ubiquitous computing will comprise of context aware adaptive applications and protocols. There is a need of a generic architecture to cater for the adaptation requirements of increasingly demanding real-time applications and increasing dynamic wireless networks. This paper discusses the adaptive approach supported by CA3RM-Com architecture. CA3RM-Com is the context aware architecture proposed for real-time communication in wireless networks. It addresses the context representation, context acquisition, context exchange,and context management. Specific details of the architecture and referring adaptations that CA3RM-Com can support are discussed. Moreover the extended simulation results of adaptive multi-homed Mobile IP are presented in this paper.

  • 119.
    Kodikara, Ruwini
    et al.
    Caulfield School of Information Technology, Monash University.
    Ling, Sea
    Caulfield School of Information Technology, Monash University.
    Zaslavsky, Arkady
    Evaluating cross-layer context exchange in mobile ad-hoc networks with colored petri nets2007Inngår i: 2007 IEEE International Conference on Pervasive Services: [ICPS '07] ; Istanbul, Turkey, 15 - 20 July 2007, Piscataway, NJ: IEEE Communications Society, 2007, s. 173-176Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Context awareness is a key component of next generation pervasive computing systems and networks. Cross layer context exchange can be proposed as an efficient solution for adaptive applications in wireless networks where traditional layered protocol stack is inadequate. ConEx is the context exchange architecture based on subscriptions. ConEx is composed of a vertical context exchange module for cross layer context exchange. We are presenting the Coloured Petri Nets based simulation model and model validation of ConEx cross layer context exchange module in this paper.

  • 120.
    Kodikara, Ruwini
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Åhlund, Christer
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Context modelling for crosslayer context aware adaptations2009Inngår i: International Journal On Advances in Networks and Services, ISSN 1942-2644, E-ISSN 1942-2644, Vol. 2, nr 1, s. 63-75Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Demand for real-time services over the Internet while moving, is growing rapidly. This necessitates efficient delivery of wireless real-time traffic. Limitations of existing layered protocol stack for wireless networks lead to the proposal of cross-layer interactions as an alternative solution. At the same time, next generation ubiquitous computing drives wireless applications and protocols to be context aware. A generic context aware architecture with context modeling can aid increasingly demanding realtime applications over highly dynamic wireless networks to be cross-layer context aware and adaptive. Moreover, a generic architecture can make lower layer protocols to be context aware and adaptive to various situations dynamically. This article discusses the adaptive approach supported by proposed cross layer context aware architecture called CA3RM-Com. The scope of this article is to discuss context modeling specifically and address the issue of context representation of multi-layer context for various adaptive situations. Various single layer and multi-layer crosslayer adaptations and the representation of context parameters with respect to each layer of the protocol stack is discussed. We discuss how these adaptations can be operated in the proposed CA3RM-Com architecture. Context aware adaptive multi-homed Mobile IP is discussed as an example adaptation that the architecture can support. Moreover, the extended simulation of context aware adaptive multi-homed Mobile IP is discussed.

  • 121.
    Kodikara, Ruwini
    et al.
    Centre for Distributed Systems and Software Engineering, Monash University.
    Åhlund, Christer
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Zaslavsky, Arkady
    Supporting adaptive real-time mobile communication with multilayer context awareness2008Inngår i: Wireless and Mobile Networking: IFIP Joint Conference on Mobile and Wireless Communications Networks (MWCN'2008) and Personal Wireless Communications (PWC'2008), Toulouse, France, September 30 - October 2, 2008 / [ed] Zoubir Mammeri, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2008, s. 435-446Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Real time mobile communication is challenging due to the inherent limitations of mobile networks. On the other hand the stringent quality of service requirements of real time traffic is highly in demand. Our first contribution is the generic context aware architecture for adaptive real time applications. Adaptation is based on the awareness of context parameters from different layers of the existing protocol stack which involves context exchange among the neighboring layers as well as non-neighboring layers. The architecture comprises of context representation, context acquisition, cross-layer context exchange and context management. Our second contribution is the mobility aware, adaptive Multi-homed Mobile IP. Simulation of adaptive M-MIP was carried out as a proof of concept. Simulation demonstrated that adaptation to mobility was able to decrease Mobile IP handover latency. Further, the results show that the quality of service of real time traffic can be enhanced by using context aware adaptive MIP. The simulation involved with various speeds ranging from pedestrian scenarios to vehicular scenarios. Results are analyzed with variable data rates. The evaluations show that performance of the proposed solution is better compared to conventional MIP in terms of packet loss and throughput of real time traffic.

  • 122. Krishnaswamy, S.
    et al.
    Zaslavsky, Arkady
    Activating a passive database using knowledge discovery techniques1998Inngår i: Proceedings of the Ninth International Conference on Computing and Information, University of Manitoba and T R Labs , 1998Konferansepaper (Fagfellevurdert)
  • 123.
    Krishnaswamy, S.
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, Seng Wai
    Monash University, Melbourne, VIC.
    Internet delivery of distributed data mining services: Architectures, issues and prospects2002Inngår i: Architectural issues of web-enabled electronic business, Hersey, PA: Idea Group Publishing, 2002, s. 113-127Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 124.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Loke, S.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Towards anytime anywhere data mining e-services2002Inngår i: Proceedings of the Australian Data Mining Workshop (ADM'02) at the 15th Australian Joint Conference on Artificial Intelligence: Canberra, Australia, December 2002 / [ed] S.J. Simoff; G.J. Williams; M. Hegland, Sydney University of Technology , 2002, s. 47-56Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The term mobile data mining is becoming prevalent as a consequence of research and development in mining data streams from mobile devices. On another strand of development Application Service Providers (ASP) hosting Internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained by the high cost of data mining software. This paper advocates the paradigm of anytime anywhere data mining services to facilitate delivery of data mining as a service in pervasive enviroments charachterised by ad-hoc task requests and the need for results anytime anywhere. The proliferation of handheld devices and wireless technologies pose new challenges and provide new opportunities for the analysis of data and teh delivery of results. We review the current state-of-the-art in data mining ASPs in the commercial domain and discuss our research in enabling a virtual community of data mining e-services- We evaluate the benefits and discuss the issues and challenges in enabling anytime anywhere data mining services. 

  • 125.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Loke, Seng Wai
    Zaslavsky, Arkady
    A hybrid model for improving response time in distributed data mining2004Inngår i: IEEE transactions on systems, man and cybernetics. Part B. Cybernetics, ISSN 1083-4419, E-ISSN 1941-0492, Vol. 34, nr 6, s. 2466-2479Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents a hybrid distributed data mining (DDM) model for optimization of response time. The model combines a mobile agent approach with client server strategies to reduce the overall response time. The hybrid model proposes and develops accurate a priori estimates of the computation and communication components of response time as the costing strategy to support optimization. Experimental evaluation of the hybrid model is presented.

  • 126.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Loke, Seng Wai
    RMIT University, Melbourne.
    Zaslavsky, Arkady
    Application run time estimation: a quality of service metric for web-based data mining services2002Inngår i: Applied computing 2002: proceedings of the 2002 ACM Symposium on Applied Computing ; Universidad Carlos III De Madrid, Madrid, Spain, March 11 - 14, 2002 / [ed] Gary Lamont, New York: IEEE Communications Society, 2002, s. 1153-1159Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The emergence of Application Service Providers (ASP) hosting Internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained by the high cost of data mining software. Response time is an important Quality of Service (QoS) metric for web-based data mining service providers. The ability to estimate the response time of data mining algorithms apriori benefits both clients and service providers. The advantage for the clients is that it helps to impose QoS constraints on the service level agreements and the benefit for the service-providers is that it facilitates optimising resource utilisation and scheduling. In this paper we present a novel rough sets based technique for identifying similarity templates to estimate application run times. We also present experimental results and analysis of this technique.

  • 127. Krishnaswamy, Shonali
    et al.
    Loke, Seng Wai
    Zaslavsky, Arkady
    Cost models for distributed data mining2000Inngår i: SEKE 2000: Twelfth International Conference on Software Engineering and Knowledge Engineering, July 6 - 8, 2000, Hotel W Chicago Lake Shore, Chicago, Illinois, USA ; [proceedings], Skokie, Ill, 2000Konferansepaper (Fagfellevurdert)
  • 128.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Loke, Seng Wai
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Efficient prediction of quality of service for data mining web services2003Inngår i: Proceedings of the Third International Conference on Electronic Business, Singapore: NUS Press Pte Ltd , 2003Konferansepaper (Fagfellevurdert)
  • 129.
    Krishnaswamy, Shonali
    et al.
    School of Computer Science & Software Engineering, Monash University Melbourne.
    Loke, Seng Wai
    School of Computer Science and Information Technology, RMIT University.
    Zaslavsky, Arkady
    Knowledge elicitation through web-based data mining services2001Inngår i: Advances in Learning Software Organizations: Third International Workshop, LSO 2001 Kaiserslautern, Germany, September 12-13, 2001 Proceedings / [ed] Klaus-Dieter Althoff, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2001, s. 120-134Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Knowledge is a vital component for organisational growth and data mining provides the technological basis for automated knowledge elicitation from data sources. The emergence of Application Service Providers hosting Internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained by the high cost of data mining software. In this paper, we present two alternative models of organisation for data mining service providers. We use the interaction protocols between organisations requiring data mining services and the service providers to motivate the need for specification of data mining task requests that adequately represent the requirements and constraints of the clients and also illustrate the importance of description mechanisms for data mining systems and services in order to support Internet delivery of such services. We present an XML-based approach for describing both, data mining task requests and the functionality and services of data mining service providers.

  • 130. Krishnaswamy, Shonali
    et al.
    Loke, Seng Wai
    Zaslavsky, Arkady
    Predicting run times of applications using rough sets2002Inngår i: Information processing and management of uncertainty in knowledge-based systems: proceedings; Ninth International Conference IPMU 2002; July 1 - 5, 2002, [Annecy, France], Annecy: IPMU , 2002Konferansepaper (Fagfellevurdert)
  • 131. Krishnaswamy, Shonali
    et al.
    Zaslavsky, Arkady
    A rule measure to represent the temporal changes of data mining patterns1999Inngår i: Proceedings of the Workshop on Computer Science and Information Technologies CSIT '99, Moscow: University of MEPhl Publishing , 1999Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Data mining is the automated extraction of hitherto unknown patterns in large databases. Patterns or rules extracted by mining algorithms are generally true for the current state of the database. As the database state changes due to new transactions these rules may either become invalid or may have increased support. In this paper we present a new rule measure - Rule Trend Analysis (RTA) - which quantifies and represents the trend or behaviour of patterns extracted by data mining systems as these rules evolve along a continuous time interval. This measure is derived using the database log file by analysing transactions that are compliant with the rule and those that are not. We present both the theoretical aspects as well as the results obtained by implementing this technique of data mining rule analysis.

  • 132. Krishnaswamy, Shonali
    et al.
    Zaslavsky, Arkady
    Using knowledge discovery techniques for database schema refinement1999Inngår i: Proceedings of the 32nd Annual Hawaii International Conference on System Sciences: January 5 - 8, 1999, Maui, Hawaii : abstracts and CD-ROM of full papers / [ed] Ralph H. Sprague, Los Alamitos, Calif: IEEE Communications Society, 1999Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper proposes the automated translation of rules extracted from data mining or knowledge discovery tools into active database rules. We term this process of translating a knowledge discovery rule and incorporating it into a database schema in the form of an ECA (event-condition-action) rule as database schema refinement. We introduce a new rule identification measure for categorising knowledge discovery rules into semantic integrity constraints and probabilistic rules, which forms the basis for determining the mode of constraint enforcement in the enriched schema. This measure is based on database statistics and history. Using this measure we estimate and model both the static and dynamic characteristics of a given rule. The rule classification process is followed by the generation of the ECA equivalents. We present a generic technique and show how this is implemented in an Oracle database. Finally, the monitoring of the database scheme refinement process and the transition of a rule from one state to another are discussed

  • 133.
    Krishnaswamy, Shonali
    et al.
    School of Computer Science & Software Engineering, Monash University Melbourne.
    Zaslavsky, Arkady
    Loke, Seng Wai
    School of Computer Science & Software Engineering, Monash University Melbourne.
    A hybrid model for optimising distributed data mining2004Inngår i: Distributed Computing - IWDC 2003: 5th International Workshop Kolkata, India, December 27-30, 2003. Proceedings / [ed] Samir R. Das; Sajal K. Das, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2004, s. 300-310Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents a hybrid model for improving the response time of distributed data mining (DDM). The hybrid DDM model uses cost formulae and prediction techniques to compute an estimate of the response time for a DDM process and applies a combination of client-server and mobile agent strategies based on the estimates to reduce the overall response time. Experimental results that establish the validity and demonstrate the improved response time of the hybrid model are presented.

  • 134.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, Seng Wai
    Monash University, Melbourne, VIC.
    Estimating computation times in data intensive e-services2003Inngår i: Web Information Systems Engineering, WISE: Proceedings of the Fourth International Conference on Web Information Systems Engineering, Piscataway, NJ: IEEE Communications Society, 2003, s. 72-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Apriori estimation of quality of service (QoS) levels is a significant issue in e-services since Service Level Agreements (SLAs) need to specify and adhere to such estimates. Response time is an important metric for data intensive e-services such as data mining, data analysis and querying/information retrieval from large databases where the focus is on the time taken to present results to clients. A key component of response time in such data intensive services is the time taken to perform the computation, namely, the time taken to perform either data mining, analysis or retrieval. In this paper we present a novel approach for accurately estimating the computation times of data intensive e-services.

  • 135.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, Seng Wai
    RMIT university.
    Towards data mining services on the Internet with a multiple service provider model: an XML based approach2001Inngår i: Journal of Electronic Commerce Research, ISSN 1938-9027, E-ISSN 1526-6133, Vol. 2, nr 3, s. 103-130Artikkel i tidsskrift (Fagfellevurdert)
  • 136.
    Krishnaswamy, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, S.W.
    RMIT university.
    Techniques for estimating the computation and communication costs of distributed data mining2002Inngår i: Computational science - ICCS 2002: international conference, Amsterdam, The Netherlands, April 21 - 24, 2002 ; proceedings / [ed] Peter M.A. Sloot, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2002, s. 603-612Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Distributed Data Mining (DDM) is the process of mining distributed and heterogeneous datasets. DDM is widely seen as a means of addressing the scalability issue of mining large data sets. Consequently, there is an emerging focus on optimisation of the DDM process. In this paper we present cost formulae for estimating the communication and computation time for different distributed data mining scenarios.

  • 137.
    Krishnaswarny, G.
    et al.
    Monash University, Melbourne, VIC.
    Loke, Seng Wai
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Supporting the optimisation of distributed data mining by predicting application run times2002Inngår i: Proceedings of the Fourth International Conference on Enterprise Information Systems : Ciudad Real, Spain, April 3 - 6, 2002 / ICEIS 2000, INSTICC Press, 2002, s. 374-381Konferansepaper (Fagfellevurdert)
    Abstract [en]

    There is an emerging interest in optimisation strategies for distributed data mining in order to improve response time. Optimisation techniques operate by first identifying factors that affect the performance in distributed data mining, computing/assigning a "cost" to those factors for alternate scenarios or strategies and then choosing a strategy that involves the least cost. In this paper we propose the use of application run time estimation as solution to estimating the cost of performing a data mining task in different distributed locations. A priori knowledge of the response time provides a sound basis for optimisation strategies, particularly if there are accurate techniques to obtain such knowledge. In this paper we present a novel rough set based technique for predicting the run times of applications. We also present experimental validation of the prediction accuracy of this technique for estimating the run times of data mining tasks

  • 138.
    Krishnaswarny, S.
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, S.W.
    Monash University, Melbourne, VIC.
    An architecture to support distributed data mining services in e-commerce environments2000Inngår i: Proceedings: International Workshop on Advanced Issues of E-Commerce and Web-Based Information Systems : June 8 - 9, Milpitas, California / [ed] Philip S. Yu, Los Alamitos, Calif: IEEE Communications Society, 2000, s. 239-246Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents our hybrid architectural model for distributed data mining (DDM), which is tailored to meet the needs of e-businesses in which application service providers sell DDM services to e-commerce users and systems. The hybrid architecture integrates the client-server and the mobile agent technologies. This model focuses on the optimisation and costing issues of DDM, which are particularly relevant in the context of billing users for data mining services

  • 139.
    Krishnaswarny, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Loke, Seng Wai
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Estimating computation times of data-intensive applications2004Inngår i: IEEE Distributed Systems Online, ISSN 1541-4922, E-ISSN 1541-4922, Vol. 5, nr 4Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present a holistic approach to estimation that uses rough sets theory to determine a similarity template and then compute a runtime estimate using identified similar applications. We tested the technique in two real-life data-intensive applications: data mining and high-performance computing.

  • 140.
    Krishnaswarny, Shonali
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, Seng-Wai
    Monash University, Melbourne, VIC.
    Federated data mining services and a supporting XML-based language2001Inngår i: Proceedings of the 34th Annual Hawaii International Conference on System Sciences : January 3 - 6, 2001, Maui, Hawaii ; abstracts and CD-ROM of full papers / [ed] Ralph H. Sprague, Los Alamitos, Calif: IEEE Communications Society, 2001, s. 70-79Konferansepaper (Fagfellevurdert)
    Abstract [en]

    E-businesses are increasingly looking towards data mining systems for meeting their business intelligence needs. However, the current state of the art in data mining does not allow any one system to be able to meet the diverse business intelligence needs of e-businesses. A second bottleneck is the high initial cost involved in establishing data mining infrastructure within an organisation. We propose the concept of a federated data mining system hosted by an Application Service Provider (ASP) as a means of alleviating the bottlenecks of high cost and diverse data mining needs. We also present an XML DTD, which provides the basis for data mining systems to describe their services and architecture to the rest of the federation.

  • 141.
    Kumar, V.
    et al.
    University of Missouri.
    Cetintemel, Ugar
    Brown university.
    Zaslavsky, Arkady
    Labrinidis, A.
    University of Pittsburgh.
    Foreword: MobiDE 2005 : Proceedings of the 4th ACM International Workshop on Data Engineering for Wireless and Mobile Access2005Inngår i: Data engineering for wireless and mobile access: MobiDE 2005 ; proceedings of the Fourth ACM International Workshop on Data Engineering for Wireless and Mobile Access, June 12, 2005, Baltimore, Maryland, USA / [ed] Ugur Cetintemel, New York: Association for Computing Machinery (ACM), 2005, s. iii-ivKonferansepaper (Annet vitenskapelig)
  • 142. Lai, S.J.
    et al.
    Zaslavsky, Arkady
    Behavioural discovery of network protocols functionality for OSI model conformande testing1994Inngår i: Modelling and simulation - MS '94: proceedings of the IASTED international conference ; Pittsburgh, PA, U.S.A., May 2 - 4, 1994 / [ed] M.H. Hamza, Anaheim, CA: ACTA Press, 1994, s. 370-372Konferansepaper (Fagfellevurdert)
  • 143.
    Lai, S.J.
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Martin, G.M.
    Monash University, Melbourne, VIC.
    A simulation model of adaptive protocols in distributed computing systems with mobile hosts1995Inngår i: Proceedings of the 28th Annual Simulation Symposium: April 9 - 13, 1995, Phoenix, Arizona, Los Alamitos, Calif: IEEE Communications Society, 1995, s. 220-227Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Simulation is a scientific method which is largely dominated by computers and has allowed the testing and assessment of many models before actual implementation. The paper proposes an approach to construction of a simulation that models the behaviour of an adaptive queuing protocol (AQP). AQP was developed for database applications on mobile computers in a distributed multidatabase environment but can also be used in many other areas including distributed operating systems. By constructing the simulation model it is possible to both prove that it can be implemented, and at the same time study its expected behaviour in a mobile computing environment. The results of the simulation are analysed and discussed

  • 144. Lai, S.J.
    et al.
    Zaslavsky, Arkady
    Martin, G.M.
    Yeo, L.H.
    Cost-efficient adaptive protocol with buffering for advanced mobile database applications1995Inngår i: Database systems for advanced applications '95: proceedings of the Fourth International Conference on Database Systems for Advanced Applications, Singapore, April 10 - 13, 1995 / [ed] Tok Wang Ling; Yoshifumi Masunaga, Singapore: World Scientific and Engineering Academy and Society, 1995, s. 87-94Konferansepaper (Fagfellevurdert)
  • 145. Leonas, Vladas
    et al.
    Pirotta, Martin
    Zaslavsky, Arkady
    Pay-for-resources models in mobile business applications2002Inngår i: Evolution Scenarios for Emerging Mobile Commerce Services, 2002Konferansepaper (Fagfellevurdert)
  • 146. Ling, Chris
    et al.
    Vaile, Stuart
    Zaslavsky, Arkady
    SoundHunter: towards a context-aware mobile agent system2004Inngår i: Proceedings of the 3rd Asian International Mobile Computing Conference, Kasetsart University , 2004Konferansepaper (Fagfellevurdert)
  • 147.
    Linger, Henry
    et al.
    Department of Information Systems, Monash university.
    Burstein, Frada
    Department of Information Systems, Monash university.
    Zaslavsky, Arkady
    Aitken, Campbell
    Macfarlane Burnet Centre for Medical Research.
    Crofts, Nick
    Macfarlane Burnet Centre for Medical Research.
    Conceptual development of an information systems framework for improving continuity in epidemiological research1998Inngår i: European Journal of Epidemiology, ISSN 0393-2990, E-ISSN 1573-7284, Vol. 14, nr 6, s. 587-593Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Lack of continuity is a problem for survey-based epidemiological research. Poor access to experience and inadequate retention of information means new projects seldom build on successful predecessors to the maximum possible extent. We have designed a data management framework which addresses this problem using a well-known information systems approach. Our ideas provide a means of storing data in a manner which reflects the original research concepts. This makes collected data accessible and understandable without reference to the questionnaire, and allows new questionnaires to be designed quickly and easily. Our framework provides a means for recording developmental, conceptual and other supporting information and documentation which is traditionally poorly conserved. We illustrate the components of the framework using a major Australian epidemiological project as a case study. Once the necessary software is developed, our framework will improve organisational memory within individual research units and has the potential to become a valuable support tool for survey-based research.

  • 148.
    Linger, Henry
    et al.
    Monash University, Melbourne, VIC.
    Burstein, Frada
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Crofts, Nick
    Monash University, Melbourne, VIC.
    A framework for a dynamic organizational memory information system1999Inngår i: Journal of Organizational Computing and Electronic Commerce, ISSN 1091-9392, E-ISSN 1532-7744, Vol. 9, nr 2-3, s. 189-203Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Organizational memory information systems (OMIS) implement important aspects of organizational memory with the aim of enhancing organizational effectiveness. We propose a 3-layered framework for a dynamic OMIS. The framework consists of a pragmatic layer to support the actual activity, a conceptual layer to store the concepts inherent in that activity, and a process layer to store the experience of performing that activity. Both the conceptual and process layers represent organizational memory repositories in the form of respective models. The implementation of OMIS assumes that any activity is the instantiation of relevant conceptual and process models and includes the reuse of knowledge stored in association with those models. In this way, organizational memory is always mapped to current activity, and its adequacy is constantly evaluated. This provides the potential for the models to evolve as a direct result of the current activity. A partial implementation of this framework to support epidemiological research is illustrated.

  • 149.
    Loke, Seng Wai
    et al.
    Monash University, Melbourne, VIC.
    Padovitz, Amir
    Zaslavsky, Arkady
    A unifying model for representing and reasoning about context under uncertainty2006Inngår i: Proceedings of the Eleventh International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems: IPMU 2006, Paris: Editions E.D.K. , 2006, s. 1983-1989Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Modeling and reasoning about context under uncertainty is a major challenge in context-aware computing. This paper proposes a novel approach to represent context in a unifying way and to perform reasoning about context represented with that model, under uncertainty. We develop a novel reasoning approach based on Multi- Attribute Utility Theory as the means to integrate heuristics about the relative importance, inaccuracy and characteristics of sensory information. Our approach allows applying different reasoning approaches, and in this paper we qualitatively and quantitatively compare between our proposed reasoning approach and Dempster-Shafer sensor data fusion technique

  • 150.
    Loke, Seng Wai
    et al.
    School of Computer Science & Software Engineering, Monash University Melbourne.
    Padovitz, Amir
    School of Computer Science & Software Engineering, Monash University Melbourne.
    Zaslavsky, Arkady
    Context-based addressing: the concept and an implementation for large-scale mobile agent systems using publish-subscribe event notification2003Inngår i: Distributed Applications and Interoperable Systems: 4th IFIP WG6.1 International Conference, DAIS 2003, Paris, France, November 17-21, 2003. Proceedings / [ed] Jean-Bernard Stefani, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2003, s. 274-284Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We introduce the notion of context-based addressing, i.e. the ability to refer to and send messages to a collection of agents based on their current context, without knowing the precise identities of the agents. We describe a simple implementation of context-based addressing for mobile agents using Elvin, a publish-subscribe event notification system, as a proof-of-concept, and to investigate the feasibility of the event-based paradigm for implementing context-based addressing for mobile agents.

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