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  • 1.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Smart distribution of IT load in energy efficient data centers with focus on cooling systems2018In: IECON 2018: 44th Annual Conference of the IEEE Industrial Electronics Society, 2018Conference paper (Refereed)
  • 2.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A hybrid fault detection and diagnosis method in server rooms’ cooling systems2019Conference paper (Refereed)
    Abstract [en]

    Data centers as all complex systems are prone to faults, and cost of them can be very high. This paper is focused on detecting the faults in the cooling systems, in particular on local fans level. In the paper, a hybrid approach is proposed. In the approach a model is used as substitute of the real system to generate dataset containing records of both normal and fault cases. On the generated data, machine learning algorithm or ensemble of algorithms are selected and trained to detect the faults. To demonstrate the approach, the rack model of real data center is created, and reliability of the model is shown. Using the model, the dataset with normal as well as abnormal records of data is generated. To detect faults of local fans, simple classifiers are built for all pairs: a local fan – a processor unit. Classifiers are trained on one part of generated data (training data), and then their accuracy is estimated on another part of generated data (test data). A real-time fault detection system is built based on the classifiers. The rack model is used as the substitute of the real plant to check operability of the system.

  • 3. Eriksson, Martin
    et al.
    Lucchese, Riccardo
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Jonas
    RISE - Swedish Institute of Computer Science.
    Ljung, Anna-Lena
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Monitoring and Modelling Open Compute Servers2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 7177-7184Conference paper (Refereed)
    Abstract [en]

    Energy efficient control of server rooms in modern data centers can help reducing the energy usage of this fast growing industry. Efficient control, however, cannot be achieved without: i) continuously monitoring in real-time the behavior of the basic thermal nodes within these infrastructures, i.e., the servers; ii) analyzing the acquired data to model the thermal dynamics within the data center. Accurate data and accurate models are indeed instrumental for implementing efficient data centers cooling strategies. In this paper we focus on a class of Open Compute Servers, designed in an open-source fashion and currently deployed by Facebook. We thus propose a set of methods for collecting real-time data from these platforms and a control-oriented model describing the thermal dynamics of the CPUs and RAMs of these servers as a function of both manipulable and exogenous inputs (e.g., the CPU utilization levels and the air mass flow produced by the server's fans). We identify the parameters of this model from real data and make the results available to other researchers.

  • 4.
    Kamel, Nidal
    et al.
    Universiti Teknologi PETRONAS, Department of Electrical and Electronics Engineering.
    Samraj, Andrews
    Faculty of Information Science & Technology (FIST), Multimedia University, Melaka.
    Mousavi, Arash
    Faculty of Information Science & Technology (FIST), Multimedia University, Melaka.
    Whitening of background brain activity via parametric modeling2007In: Discrete dynamics in nature and society, ISSN 1026-0226, E-ISSN 1607-887X, article id 48720Article in journal (Refereed)
    Abstract [en]

    Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further elaboration on how this might be done. In this paper, we investigate the whitening capabilities of two parametric techniques: a direct one based on Levinson solution of Yule-Walker equations, called AR Yule-Walker, and an indirect one based on the least-squares solution of forward-backward linear prediction ( FBLP) equations, called AR-FBLP. The whitening effect of the two algorithms is investigated with real background electroencephalogram ( EEG) colored noise and compared in time and frequency domains.

  • 5.
    Kleyko, Denis
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Osipov, Evgeny
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Papakonstantinou, Nikolaos
    VTT Technical Research Centre of Finland, Espoo.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fault Detection in the Hyperspace: Towards Intelligent Automation Systems2015In: IEEE International Conference on Industrial Informatics: INDIN 2015, Cambridge, UK, July 22-24, 2015. Proceedings, Piscataway, NJ: IEEE Communications Society, 2015, p. 1219-1224, article id 7281909Conference paper (Refereed)
    Abstract [en]

    This article presents a methodology for intelligent, biologically inspired fault detection system for generic complex systems of systems. The proposed methodology utilizes the concepts of associative memory and vector symbolic architectures, commonly used for modeling cognitive abilities of human brain. Compared to classical methods of artificial intelligence used in the context of fault detection the proposed methodology shows an unprecedented performance, while featuring zero configuration and simple operations.

  • 6.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Berezovskaya, Yulia
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering a nd Automation, Aalto University.
    Zhang, Xiaojing
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy efficient decision making in data centers with multiple cooling methods2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 8785-8790Conference paper (Refereed)
    Abstract [en]

    Cooling systems consume around 40% of modern data centres' total energy consumption, thus reducing the energy waste in this sector will have positive environmental impact. There exist several cooling methods appropriate for particular conditions. Since environmental conditions, such as air temperature, change on seasonal bases, no single cooling method can be claimed to be the best. In contrast, data centres with multiple cooling methods can perform more efficiently. However, the decision-making process of which cooling system is the most appropriate one should be an automated process. In this paper, a decision-making process based on simulation is proposed. The simulation tool comprises of a mathematical model and a multi-agent control. The mathematical model simulates the thermal behaviour of SICS ICE data centre, which is a real facility located in Northern Sweden. The main aim of the simulation is to calculate thermal conditions and energy consumption of different cooling methods in cold and hot seasons. The result then will be used by multi-agent control to choose the most appropriate cooling method.

  • 7.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Berezovskaya, Yulia
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    ABB Corporate Research, Västerås, Sweden.
    Minde, Tor Björn
    SICS Swedish ICT, Luleå, Sweden.
    Improvement of Energy Efficiency in Data Centers via Flexible Humidity Control2016In: IECON Proceedings (Industrial Electronics Conference), Piscataway, NJ: IEEE Computer Society, 2016, p. 5585-5590, article id 7793777Conference paper (Refereed)
    Abstract [en]

    Abstract- The main goal of climate control systems in data centres is to keep the temperature and humidity in a suitable level for computational devices. Therefore, cooling and humidification systems are essential parts of every Building Automation System (BAS), which is utilized in server rooms. Although the current climate control systems ensure appropriate thermal conditions to computational nodes such as servers, they waste substantial amount of energy. The main cause of this inefficiency is that the current climate control systems, which are responsible for thermal management of the data centres, follow rigid control strategies that maintain constant thermal conditions irrespective of climate changes caused by various computational loads in the plant. To address this issue, in our previous works we proposed a method of optimizing energy consumption in data centre cooling systems while maintaining an acceptable level of thermal comfort for CPUs in the server room. In this paper, we present the enhancement of our previous method by incorporating humidity control into it. The enhanced method consists of a thermal model of server room, and a simulation tool to find an energy efficient control strategy for the climate control system in different situations by comparing different control strategies. The effectiveness of the proposed method has been investigated via simulation and the result, which shows 41.5% reduction in total energy consumption is presented.

  • 8.
    Mousavi, Arash
    et al.
    School of Computer Science, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia.
    Nordin, M. J.
    School of Computer Science, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia.
    An Architectural Model for a Multi-Agent Mobile Workforce Brokerage System based on CBR-BDI Agent Architecture and Active Shared-Data Space Coordination Model2007In: Proceedings of the International Conference on Electrical Engineering and Informatics, Bandung, Indonesia: ICEEI , 2007, p. 294-297Conference paper (Refereed)
    Abstract [en]

    Resource allocation is a core and important function of every workflow management system. Resource allocation consists of twomain parts namely; matchmaking and brokering that in normal cases are combined as a single functional unit. However in anintegrated mobile environment, where the resources such as mobile workforces are combinations of human workers and mobiledevices, matchmaking and brokering can no longer be coupled. In such environments, the accuracy of resource allocation isexpected to become quite low due to frequent disconnection, mobility of resources and human factors. In addition, resourceallocation must be fair towards human resources. An accurate and fair resource allocation in mobile environments, on the otherhand can not be attained without using an independent brokerage system. To guaranty the accuracy and fairness, the desired mobileworkforce brokerage system (MWBS) must act based on real-time environmental information as well as the history of the systemwhen an allocation is required. In this paper an architectural model for a fair and accurate multi-agent MWBS is proposed based onCBR-BDI agent architecture and Active Shared-Data Space coordination model.

  • 9.
    Mousavi, Arash
    et al.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Nordin, M. J.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Othman, Z. A.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    An ontology driven, procedural reasoning system-like agent model, for multi-agent based mobile workforce brokering systems2010In: Journal of Computer Science, ISSN 0973-2926, Vol. 6, no 5, p. 557-565Article in journal (Refereed)
    Abstract [en]

    Problem statement: It has been proven that Believe, Desire, Intention (BDI) agent architecture, performs suitably in dynamic and unpredictable environments. Although BDI architecture has been formulated rigorously, implementing BDI architecture is not as straightforward as it has been promised. Nevertheless, the preeminent implementation of BDI architecture is Procedural Reasoning System (PRS) and Jadex is a Java-based platform that successfully applies PRS BDI architecture to implement BDI agents. However, Jadex utilizes XML format to represent plans, beliefs and goals which are the core of the PRS BDI agents. Although XML is a suitable format for exchanging data, it does not add any semantic to the data that it represents. Approach: In contrast, in our proposed Ontology driven PRS like model (O-PRS), we used Ontology with OWL format to represent Believes, Plans and Events. Our Ontology had been designed particularly for implementing BDI agents which are used in Mobile Workforce Brokering Systems (MWBS), a multi-agent system that automated the process of allocating tasks to Mobile Workforces. Results: This research was an endeavor to equip the PRS model with Ontology and semantic knowledge representation and reasoning capability. In this study firstly, our proposed model was formulated, then the model was been examined using a simulation tool (MWBS-SIM) which simulated MWBS in its Initialization phase. We used JADE to implement the Agents, Protégé OWL to create the Ontology and Jena as a semantic web platform by means of which MWBS is able to connect to the Ontology and apply the O-PRS model. Conclusion: The result of our simulation showed that O-PRS is a feasible approach. Furthermore, Ontology provided better means for knowledge sharing and navigation therefore, multi-agent systems constructed using O-PRS, were more generic and more adaptable in comparison with those that use XML.

  • 10.
    Mousavi, Arash
    et al.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Nordin, M. J.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Othman, Z. A.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Ontology-driven coordination model for multiagent-based mobile workforce brokering systems2012In: Applied intelligence (Boston), ISSN 0924-669X, E-ISSN 1573-7497, Vol. 36, no 4, p. 768-787Article in journal (Refereed)
    Abstract [en]

    Coordination has been recognized by many researchers as the most important feature of multi-agent systems. Coordination is defined as managing interdependencies amongst activities (Malone and Crowston in ACM Comput. Surv. 26(1):87-119, 1994). The traditional approach of implementing a coordination mechanism is to hard-wire it into a coordination system at design time. However, in dynamic and open environments, many attributes of the system cannot be accurately identified at the design time. Therefore, dynamic coordination, capable of coordinating activities at run-time, has emerged. On the other hand, a successful dynamic coordination model for multi-agent systems requires knowledge sharing as well as common vocabulary. Therefore, an ontological approach is an appropriate way in proposing dynamic coordination models for multi-agent systems. In this paper, an Ontology-Driven Dynamic Coordination Model (O-DC) for Multiagent-Based Mobile Workforce Brokering Systems (MWBS) (Mousavi et al. in Int. J. Comput. Sci. 6:(5):557-565, 2010; Mousavi et al. in Proceedings of 4th IEEE international symposium on information technology, ITSim'10, Kuala Lumpur, Malaysia, 15-17 June 2010, vol. 3, pp. 1416-1421, 2010; Mousavi and Nordin in Proceedings of the IEEE international conference on electrical engineering and informatics, Bandung, Indonesia, 17-19 June 2007, pp. 294-297, 2007) is proposed and formulated. Subsequently, the applicability of O-DC is examined via simulation based on a real-world scenario

  • 11.
    Mousavi, Arash
    et al.
    School of Computer Science, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia.
    Nordin, M. J.
    School of Computer Science, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia.
    Othman, Z. A.
    School of Computer Science, Faculty of Information Science and Technology, University Kebangsaan Malaysia.
    Sulaiman, Riza
    School of Chemical Sciences and Food Technology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi.
    A method for Human Resource Risk Management in Mobile Workforce Brokering Systems2011In: American Journal of Applied Sciences, ISSN 1546-9239, E-ISSN 1554-3641, Vol. 8, no 12, p. 1287-1294Article in journal (Refereed)
    Abstract [en]

    Problem statement: Human Resource Risk Management is one of the crucial issues in Mobile Workforce Management Systems (MWM) in general, and in Mobile Workforce Brokering Systems (MWBS) in Particular. It is important because, if not properly managed, it will cause reduction in accuracy of the automated MWBS, which in turn necessitates more human involvement in the task allocation process. Thus, no reliable planning and scheduling schema can be made or achieved. Approach: However, a proven approach to tackle this problem is via contingency planning. In this study, we examined a specific type of HR risk called Unexpected Absence of mobile workforces in the context of an ontology-driven and multiagent-based MWBS. Our contingency plan that mainly consists of a statistical method is incorporated into the body of a coordination medium represented in OWL ontology format. Results: The proposed statistical method evaluates the past history and the current claims of an MW in order to find out a realistic plan for the next period of the system's run. Conclusion: Finally, via a case study we have illustrated that this method increases the accuracy and reliability of a periodical plan, made for MWBS in its initialization phase.

  • 12.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Pang, Cheng
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy Efficient Automation Model for Office Buildings based on Ontology, Agents and IEC 61499 Function Blocks2014In: Proceedings of 2014 IEEE 19th International Conference on Emerging Technologies & Factory Automation (ETFA 2014): Barcelona, Spain, 16-19 Sept. 2014, Piscataway, NJ: IEEE Communications Society, 2014, article id 7005081Conference paper (Refereed)
    Abstract [en]

    Execution of business processes is an important factor that distinguishes residential and office buildings based on their energy usage. Unlike residential buildings, in offices workflows determine how and when energy-consuming devices have to be utilized. Thus, energy efficient building automation systems for office buildings should take into account the dynamic and unpredictable nature of business processes. However, the existing systems lack this important feature. In this paper, a model for combining automation and business processes is proposed. The model is implemented using IEC 61499 Function Block architecture, multi-agent systems and ontology. The proposed method has been examined in a meeting room scheduling scenario, in which meeting scheduling and automated control of the meeting room equipment have been combined and the energy usage has been measured to evaluate the improvement in efficient use of energy using the proposed model.

  • 13.
    Mousavi, Arash
    et al.
    Department of Industrial Computing, Faculty of Information Science and Technology, National University of Malaysia.
    Sulaiman, Riza
    Department of Industrial Computing, Faculty of Information Science and Technology, National University of Malaysia.
    Nordin, M. J.
    Department of Industrial Computing, Faculty of Information Science and Technology, National University of Malaysia.
    Ohman, Z. A.
    Department of Industrial Computing, Faculty of Information Science and Technology, National University of Malaysia.
    Schukor, S. A.
    Department of Industrial Computing, Faculty of Information Science and Technology, National University of Malaysia.
    Providing fairness to mobile workforces in an automated task allocation process: A semantic multi-agent approach2012In: American Journal of Applied Sciences, ISSN 1546-9239, E-ISSN 1554-3641, Vol. 9, no 7, p. 1055-1062Article in journal (Refereed)
    Abstract [en]

    Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work as a team. Approach: In an automated Mobile Workforce Brokering System (MWBS) tasks are automatically assigned to MWs at Run-Time phase of the system's run. However, the environmental risks specifically risk of disconnection disrupts the task allocation process. Disconnection causes unfair task allocation when an MW must carry the next upcoming task according to a rotator work schedule, but he is disconnected. In this situation another MW has to perform the task in order to satisfy a pre-planned daily workload. Results: In this study we explore through the Run-Time phase of MWBS and explain how its underpinning ontology-driven coordination model tackles the risk of disconnection and improves the fairness in the task allocation process. Conclusion: Moreover, fairness rates in task allocation processes are compared between an existing system and MWBS and improvement in fairness rate is shown and analyzed for 4 consecutive periods (months) of the system's run

  • 14.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy Efficient Agent Function Block: A semantic agent approach to IEC 61499 function blocks in energy efficient building automation systems2015In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 54, p. 127-142Article in journal (Refereed)
    Abstract [en]

    Automation plays a vital role in improving energy efficiency in buildings. Building Automation Systems (BASs) are drastically growing in size and complexity. The traditional centralized automation systems cannot suitably address this growth due to insufficient flexibility and scalability. IEC 61499 Function Block (FB) is a promising software paradigm for industrial automation that addresses these complexities because of its object-oriented, event-driven and distributed paradigm. However, efficient energy management in a heterogeneous system comprising of many energy consuming components, functioning in highly dynamic and partially predictable environments, requires a higher level of intelligence that FB currently does not possess. To cope with this issue, a software entity called 2eA-FB has been introduced by combining FB, intelligent software agent and semantic web technologies. Being capable of field-level control, communication and reasoning over semantically enriched domain knowledge, 2eA-FB bridges the gap between management and automation layers of BAS and controls the energy consumption for individual energy consuming components, separately and intelligently. This in turn results in more efficient overall energy consumption for the whole system

  • 15.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Berezovskaya, Yulia
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    ABB AB, Corporate research.
    Cyber-physical Design of Data Centers Cooling Systems Automation2015In: IEEE TrustCom-BigDataSE-ISPA 2015: Helsinki, 20-22 Aug. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 254-260, article id 7345657Conference paper (Refereed)
    Abstract [en]

    Modern data centers in many aspects are akin to industrial plants that generate a lot of heat by consuming substantial amount of energy and require powerful cooling and ventilation. Cooling system contributes with 30 to 50% of the total energy consumption of data centers. An effective way to address energy efficiency in such cooling systems is to apply advanced automation solutions, similar to that of industrial and building automation systems. However, existing automation solutions are not flexible enough to meet requirements of cooling systems in modern data centres. This paper is an endeavour to utilize distributed adaptive automation architecture in order to improve energy efficiency of cooling. The proposed automation algorithms are validated in a simulation environment which models the thermal behaviour of a server room and helps to find the most energy efficient control strategy for controlling thecooling devices. This paper describes the simulation tool comprising of thermal behaviour modelling in MATLAB/SIMULINK connected in closed-loop with the distributed control environment of IEC 61499 standard. Simulation of a typical server room under certain constraints using the proposed tool is described and the results are presented. The results demonstrate the potential of improving higher energy efficiency, flexibility and better decision-making ability for controlling the cooling systems.

  • 16.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Berezovskaya, Yulia
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    ABB AB, Corporate research.
    Towards Energy Smart Data Centers: Simulation of Server Room Cooling System2015In: Proceedings of 2015 IEEE 20th International Conference on Emerging Technologies & Factory Automation (ETFA 2015): Luxembourg, 8-11 Sept. 2015, Piscataway, NJ: IEEE Communications Society, 2015, article id 7301573Conference paper (Refereed)
    Abstract [en]

    Cooling is an extremely important process in modern data centers. Cooling systems of server rooms ensure appropriate operation conditions to IT systems, such as servers and data storage, but, on the other side, they consume a lot of energy. Current control systems, which are installed in data centers and are responsible for thermal management of the facilities, are following conservative control strategies that maintain constant thermal conditions irrespective of computer load and outside temperature, thus efficient use of energy has not been appropriately addressed by them. In this paper, a method of optimizing energy consumption while maintaining an acceptable level of thermal comfort for CPUs in the server room is proposed.In the proposed method, a behavioral thermal model for serverroom should be created first, and then thermal behavior of theserver room would be simulated under different circumstancesusing its thermal model, in order to find an optimum controlstrategy capable of retaining balance between thermal comfortand efficient use of energy. The effectiveness of the proposedmethod has been investigated via simulating a typical serverroom using MATLAB and SIMULINK and the results aredemonstrated.

  • 17.
    Mousavi, Arash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yavarian, Alireza
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering a nd Automation, Aalto University.
    Zhang, Xiaojing
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Power quality assessment of energy efficient cooling systems in data centers2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 7191-7196Conference paper (Refereed)
    Abstract [en]

    Power quality is an important aspect in data centers and power system operators prefer data centers with high standard power quality. Modern data centers consume large amount of electrical power. As the cooling systems are accounted for 40% of the total power consumption in data centers, energy efficiency in this sector is of high importance. This research investigates if the existing energy efficient cooling strategies can also meet the power quality level defined by the IEEE 519-2014 standard. In this research three automation strategies based on IEC 61499 standard for cooling system in a typical server room are considered and the effects of each one on power quality parameters are investigated via simulation. The investigation has been performed for both; internal power grid of data center and upstream power network that data center is connected to. Power quality parameters which are considered are Total Harmonic Distortion (THD), voltage and current distortions. Results of simulation prove that the automation strategies with highest energy efficiency, also meet the higher power quality standard.

  • 18.
    Osipov, Evgeny
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    How to make a distributed programming course a big fun2015In: Frontiers in Education Conference, Conference Proceedings, ISSN 1539-4565Article in journal (Refereed)
    Abstract [en]

    This article presents experiences of teachers from Luleâ University of Technology when enhancing the teaching approach and depth of an undergraduate course on network programming and distributed applications. During the trial run of the course in the fall of 2013 agent-oriented programming and cloud technologies were married to provide students an exciting practical scenario and capability to test the performance of truly large scale distributed systems under extremely high traffic loads.

  • 19.
    Yang, Chen-Wei
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Dubinin, Victor N.
    University of Auckland, Penza State University, Department of Computer Science, University of Penza.
    On Automatic Generation of IEC61850/IEC61499 Substation Automation Systems Enabled by Ontology2015In: IECON 2014: 40th Annual Conference of the IEEE Industrial Electronics Society, Dallas, TX, USA , Oct. 29 2014 - Nov. 1 2014, Piscataway, NJ: IEEE Communications Society, 2015, p. 3577-3583Conference paper (Refereed)
    Abstract [en]

    This paper presents an introductory step in theautomatic generation of distributed control software for powerdistribution automation systems based on Ontology DrivenEngineering enabled by industrial standards IEC61850 andIEC61499. The novelty of this approach is the ability ofautomatically generating the logical connections between thelogical nodes. The paper covers the several stages of thetransformation process, such as developing the IEC61850ontology and the ontology transformation rules. The developed IEC61850 ontology includes the logical nodes descriptions and additional contextual relations between the logical nodes which is lacking in the IEC61850 SCL configuration language. Then, the IEC61850 ontology is transformed to an existing IEC61499 ontology, adding classes of IEC61850 logical nodes as IEC61499 function blocks in the IEC61499 ontology. The means of the transformation of the ontologies is based on the eSWRL sematic web rules language, an extension to the rule language SWRL. The end result is the development of an IEC61850 ontology and a set of eSWRL rules which facilitates the ontology transformation.

  • 20.
    Zhang, Xiaojing
    et al.
    Department of Power Device, ABB AB, Corporate Research, Vasteras.
    Lindberg, Thomas
    Department of Engineering and Physics, Karlstad University.
    Xiong, N.
    School of Innovation, Design and Engineering, Malardalen University, Vasteras.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cooling Energy Consumption Investigation of Data Center IT Room with Vertical Placed Server2017In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, p. 2047-2052Article in journal (Refereed)
    Abstract [en]

    As energy consumption by cooling data center IT equipment can be over 40% of total energy consumption, efficient cooling for large data centers is essential for reducing operation costs. Modern data centers are complex systems involving IT facilities, power system, cooling and ventilation systems. In our previous work, literature study was made to investigate available data center energy consumption models; and energy consumption models for data center IT room with distributed air flow control were developed. In this paper, the models are further extended and developed to cover the combined distributed air flow control and vertical placed servers in raised floor ventilation system. Simulation of the three types of ventilation systems with Even load, Idle server and Uneven load scenarios showed that significant cooling energy consumed by a traditional ventilation system can be saved by applying the proposed new concept and method.

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