FireGrid: An e-infrastructure for next-generation emergency response support

Peer reviewed paper published in Journal of Parallel and Distributed Computing.The FireGrid project aims to harness the potential of advanced forms of computation to support the response to large-scale emergencies (with an initial focus on the response to fires in the built environment). Computational models of physical phenomena are developed, and then deployed and computed on High Performance Computing resources to infer incident conditions by assimilating live sensor data from an emergency in real time–or, in the case of predictive models, faster-than-real time. The results of these models are then interpreted by a knowledge-based reasoning scheme to provide decision support information in appropriate terms for the emergency responder. These models are accessed over a Grid from an agent-based system, of which the human responders form an integral part. This paper proposes a novel FireGrid architecture, and describes the rationale behind this architecture and the research results of its application to a large-scale fire experiment.Emergency response, Grid, High performance computing, Multi-agent system, Knowledge-based reasoning, Fire simulation mode

A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids

[EN] Peer-to-Peer (P2P) overlay communications networks have emerged as a new paradigm for implementing distributed services in microgrids due to their potential benefits: they are robust, scalable, fault-tolerant, and they can route messages even with a large number of nodes which are frequently entering or leaving from the network. However, current P2P systems have been mainly developed for file sharing or cycle sharing applications where the processes of searching and managing resources are not optimized. Locality algorithms have gained a lot of attention due to their potential to provide an optimized path to groups with similar interests for routing messages in order to get better network performance. This paper develops a fully functional decentralized communication architecture with a new P2P locality algorithm and a specific protocol for monitoring and control of microgrids. Experimental results show that the proposed locality algorithm reduces the number of lookup messages and the lookup delay time. Moreover, the proposed communication architecture heavily depends of the lookup used algorithm as well as the placement of the communication layers within the architecture. Experimental results will show that the proposed techniques meet the network requirements of smart microgrids even with a large number of nodes on stream.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2R. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under BES-2013-064539.Marzal-Romeu, S.; González-Medina, R.; Salas-Puente, RA.; Figueres Amorós, E.; Garcerá, G. (2017). A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids. Energies. 10(9):1-25. https://doi.org/10.3390/en10091275S125109Khan, R. H., & Khan, J. Y. (2013). A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network. Computer Networks, 57(3), 825-845. doi:10.1016/j.comnet.2012.11.002Dada, J. O. (2014). Towards understanding the benefits and challenges of Smart/Micro-Grid for electricity supply system in Nigeria. Renewable and Sustainable Energy Reviews, 38, 1003-1014. doi:10.1016/j.rser.2014.07.077Lidula, N. W. A., & Rajapakse, A. D. (2011). Microgrids research: A review of experimental microgrids and test systems. Renewable and Sustainable Energy Reviews, 15(1), 186-202. doi:10.1016/j.rser.2010.09.041Hussain, A., Arif, S. M., Aslam, M., & Shah, S. D. A. (2017). Optimal siting and sizing of tri-generation equipment for developing an autonomous community microgrid considering uncertainties. Sustainable Cities and Society, 32, 318-330. doi:10.1016/j.scs.2017.04.004Dehghanpour, K., Colson, C., & Nehrir, H. (2017). A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids. Energies, 10(5), 620. doi:10.3390/en10050620Palizban, O., Kauhaniemi, K., & Guerrero, J. M. (2014). Microgrids in active network management – part II: System operation, power quality and protection. Renewable and Sustainable Energy Reviews, 36, 440-451. doi:10.1016/j.rser.2014.04.048Shi, W., Li, N., Chu, C.-C., & Gadh, R. (2017). Real-Time Energy Management in Microgrids. IEEE Transactions on Smart Grid, 8(1), 228-238. doi:10.1109/tsg.2015.2462294Deng, R., Yang, Z., Chow, M.-Y., & Chen, J. (2015). A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches. IEEE Transactions on Industrial Informatics, 11(3), 570-582. doi:10.1109/tii.2015.2414719Moazami Goodarzi, H., & Kazemi, M. (2017). A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm. Energies, 10(4), 485. doi:10.3390/en10040485Erol-Kantarci, M., Kantarci, B., & Mouftah, H. (2011). Reliable overlay topology design for the smart microgrid network. IEEE Network, 25(5), 38-43. doi:10.1109/mnet.2011.6033034Hassan Youssef, K. (2016). Optimal management of unbalanced smart microgrids for scheduled and unscheduled multiple transitions between grid-connected and islanded modes. Electric Power Systems Research, 141, 104-113. doi:10.1016/j.epsr.2016.07.015Giotitsas, C., Pazaitis, A., & Kostakis, V. (2015). A peer-to-peer approach to energy production. Technology in Society, 42, 28-38. doi:10.1016/j.techsoc.2015.02.002Kazmi, S. A. A., Shahzad, M. K., Khan, A. Z., & Shin, D. R. (2017). Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective. Energies, 10(4), 501. doi:10.3390/en10040501Werth, A., Andre, A., Kawamoto, D., Morita, T., Tajima, S., Tokoro, M., … Tanaka, K. (2018). Peer-to-Peer Control System for DC Microgrids. IEEE Transactions on Smart Grid, 9(4), 3667-3675. doi:10.1109/tsg.2016.2638462Deconinck, G., Vanthournout, K., Beitollahi, H., Qui, Z., Duan, R., Nauwelaers, B., … Belmans, R. (2008). A Robust Semantic Overlay Network for Microgrid Control Applications. Architecting Dependable Systems V, 101-123. doi:10.1007/978-3-540-85571-2_5Bandara, H. M. N. D., & Jayasumana, A. P. (2012). Collaborative applications over peer-to-peer systems–challenges and solutions. Peer-to-Peer Networking and Applications, 6(3), 257-276. doi:10.1007/s12083-012-0157-3Palizban, O., & Kauhaniemi, K. (2015). Hierarchical control structure in microgrids with distributed generation: Island and grid-connected mode. Renewable and Sustainable Energy Reviews, 44, 797-813. doi:10.1016/j.rser.2015.01.008Khatibzadeh, A., Besmi, M., Mahabadi, A., & Reza Haghifam, M. (2017). Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies, 10(2), 169. doi:10.3390/en10020169Planas, E., Gil-de-Muro, A., Andreu, J., Kortabarria, I., & Martínez de Alegría, I. (2013). General aspects, hierarchical controls and droop methods in microgrids: A review. Renewable and Sustainable Energy Reviews, 17, 147-159. doi:10.1016/j.rser.2012.09.032Olivares, D. E., Mehrizi-Sani, A., Etemadi, A. H., Canizares, C. A., Iravani, R., Kazerani, M., … Hatziargyriou, N. D. (2014). Trends in Microgrid Control. IEEE Transactions on Smart Grid, 5(4), 1905-1919. doi:10.1109/tsg.2013.2295514Vandoorn, T. L., Vasquez, J. C., De Kooning, J., Guerrero, J. M., & Vandevelde, L. (2013). Microgrids: Hierarchical Control and an Overview of the Control and Reserve Management Strategies. IEEE Industrial Electronics Magazine, 7(4), 42-55. doi:10.1109/mie.2013.2279306Zhou, B., Li, W., Chan, K. W., Cao, Y., Kuang, Y., Liu, X., & Wang, X. (2016). Smart home energy management systems: Concept, configurations, and scheduling strategies. Renewable and Sustainable Energy Reviews, 61, 30-40. doi:10.1016/j.rser.2016.03.047Ancillotti, E., Bruno, R., & Conti, M. (2013). The role of communication systems in smart grids: Architectures, technical solutions and research challenges. Computer Communications, 36(17-18), 1665-1697. doi:10.1016/j.comcom.2013.09.004Llaria, A., Terrasson, G., Curea, O., & Jiménez, J. (2016). Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment. Applied Sciences, 6(3), 61. doi:10.3390/app6030061Luna, A. C., Diaz, N. L., Graells, M., Vasquez, J. C., & Guerrero, J. M. (2016). Cooperative energy management for a cluster of households prosumers. IEEE Transactions on Consumer Electronics, 62(3), 235-242. doi:10.1109/tce.2016.7613189Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and Challenges of Wireless Sensor Networks in Smart Grid. IEEE Transactions on Industrial Electronics, 57(10), 3557-3564. doi:10.1109/tie.2009.2039455Zhao, C., He, J., Cheng, P., & Chen, J. (2017). Consensus-Based Energy Management in Smart Grid With Transmission Losses and Directed Communication. IEEE Transactions on Smart Grid, 8(5), 2049-2061. doi:10.1109/tsg.2015.2513772Lo, C.-H., & Ansari, N. (2013). Decentralized Controls and Communications for Autonomous Distribution Networks in Smart Grid. IEEE Transactions on Smart Grid, 4(1), 66-77. doi:10.1109/tsg.2012.2228282Li, C., Savaghebi, M., Guerrero, J., Coelho, E., & Vasquez, J. (2016). Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control. Energies, 9(9), 717. doi:10.3390/en9090717Wu, X., Jiang, P., & Lu, J. (2014). Multiagent-Based Distributed Load Shedding for Islanded Microgrids. Energies, 7(9), 6050-6062. doi:10.3390/en7096050Kantamneni, A., Brown, L. E., Parker, G., & Weaver, W. W. (2015). Survey of multi-agent systems for microgrid control. Engineering Applications of Artificial Intelligence, 45, 192-203. doi:10.1016/j.engappai.2015.07.005Lopes, A. L., & Botelho, L. M. (2008). Improving Multi-Agent Based Resource Coordination in Peer-to-Peer Networks. Journal of Networks, 3(2). doi:10.4304/jnw.3.2.38-47Cameron, A., Stumptner, M., Nandagopal, N., Mayer, W., & Mansell, T. (2015). Rule-based peer-to-peer framework for decentralised real-time service oriented architectures. Science of Computer Programming, 97, 202-234. doi:10.1016/j.scico.2014.06.005Zhang, C., Wu, J., Cheng, M., Zhou, Y., & Long, C. (2016). A Bidding System for Peer-to-Peer Energy Trading in a Grid-connected Microgrid. Energy Procedia, 103, 147-152. doi:10.1016/j.egypro.2016.11.264Malatras, A. (2015). State-of-the-art survey on P2P overlay networks in pervasive computing environments. Journal of Network and Computer Applications, 55, 1-23. doi:10.1016/j.jnca.2015.04.014Eng Keong Lua, Crowcroft, J., Pias, M., Sharma, R., & Lim, S. (2005). A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Surveys & Tutorials, 7(2), 72-93. doi:10.1109/comst.2005.1610546Xu, J., Kumar, A., & Yu, X. (2004). On the Fundamental Tradeoffs Between Routing Table Size and Network Diameter in Peer-to-Peer Networks. IEEE Journal on Selected Areas in Communications, 22(1), 151-163. doi:10.1109/jsac.2003.818805Stoica, I., Morris, R., Karger, D., Kaashoek, M. F., & Balakrishnan, H. (2001). Chord. ACM SIGCOMM Computer Communication Review, 31(4), 149-160. doi:10.1145/964723.383071Rowstron, A., & Druschel, P. (2001). Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. Lecture Notes in Computer Science, 329-350. doi:10.1007/3-540-45518-3_18Yuh-Jzer Joung, Li-Wei Yang, & Chien-Tse Fang. (2007). Keyword search in DHT-based peer-to-peer networks. IEEE Journal on Selected Areas in Communications, 25(1), 46-61. doi:10.1109/jsac.2007.070106Stoica, I., Morris, R., Liben-Nowell, D., Karger, D. R., Kaashoek, M. F., Dabek, F., & Balakrishnan, H. (2003). Chord: a scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking, 11(1), 17-32. doi:10.1109/tnet.2002.808407Gottron, C., König, A., & Steinmetz, R. (2010). A Survey on Security in Mobile Peer-to-Peer Architectures—Overlay-Based vs. Underlay-Based Approaches. Future Internet, 2(4), 505-532. doi:10.3390/fi2040505Seyedi, Y., Karimi, H., & Guerrero, J. M. (2017). Centralized Disturbance Detection in Smart Microgrids With Noisy and Intermittent Synchrophasor Data. IEEE Transactions on Smart Grid, 8(6), 2775-2783. doi:10.1109/tsg.2016.2539947Youssef, T., Elsayed, A., & Mohammed, O. (2016). Data Distribution Service-Based Interoperability Framework for Smart Grid Testbed Infrastructure. Energies, 9(3), 150. doi:10.3390/en9030150Liu, X., Xia, H., & Chien, A. A. (2004). Validating and Scaling the MicroGrid: A Scientific Instrument for Grid Dynamics. Journal of Grid Computing, 2(2), 141-161. doi:10.1007/s10723-004-4200-3Kansal, P., & Bose, A. (2012). Bandwidth and Latency Requirements for Smart Transmission Grid Applications. IEEE Transactions on Smart Grid, 3(3), 1344-1352. doi:10.1109/tsg.2012.2197229Kuo, M.-T., & Lu, S.-D. (2013). Design and Implementation of Real-Time Intelligent Control and Structure Based on Multi-Agent Systems in Microgrids. Energies, 6(11), 6045-6059. doi:10.3390/en6116045Del Val, E., Rebollo, M., & Botti, V. (2012). Enhancing decentralized service discovery in open service-oriented multi-agent systems. Autonomous Agents and Multi-Agent Systems, 28(1), 1-30. doi:10.1007/s10458-012-9210-0Howell, S., Rezgui, Y., Hippolyte, J.-L., Jayan, B., & Li, H. (2017). Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources. Renewable and Sustainable Energy Reviews, 77, 193-214. doi:10.1016/j.rser.2017.03.107Frey, S., Diaconescu, A., Menga, D., & Demeure, I. (2015). A Generic Holonic Control Architecture for Heterogeneous Multiscale and Multiobjective Smart Microgrids. ACM Transactions on Autonomous and Adaptive Systems, 10(2), 1-21. doi:10.1145/2700326Miers, C., Simplicio, M., Gallo, D., Carvalho, T., Bressan, G., Souza, V., … Damola, A. (2010). A Taxonomy for Locality Algorithms on Peer-to-Peer Networks. IEEE Latin America Transactions, 8(4), 323-331. doi:10.1109/tla.2010.5595121Porsinger, T., Janik, P., Leonowicz, Z., & Gono, R. (2017). Modelling and Optimization in Microgrids. Energies, 10(4), 523. doi:10.3390/en10040523Ali, M., Zakariya, M., Asif, M., & Ullah, A. (2012). TCP/IP Based Intelligent Load Management System in Micro-Grids Network Using MATLAB/Simulink. Energy and Power Engineering, 04(04), 283-289. doi:10.4236/epe.2012.44038Shin, I.-J., Song, B.-K., & Eom, D.-S. (2017). International Electronical Committee (IEC) 61850 Mapping with Constrained Application Protocol (CoAP) in Smart Grids Based European Telecommunications Standard Institute Machine-to-Machine (M2M) Environment. Energies, 10(3), 393. doi:10.3390/en10030393Loh, P. C., Li, D., Chai, Y. K., & Blaabjerg, F. (2013). Autonomous Operation of Hybrid Microgrid With AC and DC Subgrids. IEEE Transactions on Power Electronics, 28(5), 2214-2223. doi:10.1109/tpel.2012.2214792Overlay networks for smart gridshttp://users.atlantis.ugent.be/cdvelder/papers/2013/wauters2013sgv.pdfEugster, P. T., Felber, P. A., Guerraoui, R., & Kermarrec, A.-M. (2003). The many faces of publish/subscribe. ACM Computing Surveys, 35(2), 114-131. doi:10.1145/857076.857078Ali, I. (2012). High-speed Peer-to-peer Communication based Protection Scheme Implementation and Testing in Laboratory. International Journal of Computer Applications, 38(4), 16-24. doi:10.5120/4596-6793Yoo, B.-K., Yang, S.-H., Yang, H.-S., Kim, W.-Y., Jeong, Y.-S., Han, B.-M., & Jang, K.-S. (2011). Communication Architecture of the IEC 61850-based Micro Grid System. Journal of Electrical Engineering and Technology, 6(5), 605-612. doi:10.5370/jeet.2011.6.5.605Dou, X., Quan, X., Wu, Z., Hu, M., Yang, K., Yuan, J., & Wang, M. (2014). Hybrid Multi-Agent Control in Microgrids: Framework, Models and Implementations Based on IEC 61850. Energies, 8(1), 31-58. doi:10.3390/en801003

Collaborative e-science architecture for Reaction Kinetics research community

This paper presents a novel collaborative e-science architecture (CeSA) to address two challenging issues in e-science that arise from the management of heterogeneous distributed environments: (i) how to provide individual scientists an integrated environment to collaborate with each other in distributed, loosely coupled research communities where each member might be using a disparate range of tools; and (ii) how to provide easy access to a range of computationally intensive resources from a desktop. The Reaction Kinetics research community was used to capture the requirements and in the evaluation of the proposed architecture. The result demonstrated the feasibility of the approach and the potential benefits of the CeSA

Investigating grid computing technologies for use with commercial simulation packages

As simulation experimentation in industry become more computationally demanding, grid computing can be seen as a promising technology that has the potential to bind together the computational resources needed to quickly execute such simulations. To investigate how this might be possible, this paper reviews the grid technologies that can be used together with commercial-off-the-shelf simulation packages (CSPs) used in industry. The paper identifies two specific forms of grid computing (Public Resource Computing and Enterprise-wide Desktop Grid Computing) and the middleware associated with them (BOINC and Condor) as being suitable for grid-enabling existing CSPs. It further proposes three different CSP-grid integration approaches and identifies one of them to be the most appropriate. It is hoped that this research will encourage simulation practitioners to consider grid computing as a technologically viable means of executing CSP-based experiments faster

Mobile Computing in Physics Analysis - An Indicator for eScience

This paper presents the design and implementation of a Grid-enabled physics analysis environment for handheld and other resource-limited computing devices as one example of the use of mobile devices in eScience. Handheld devices offer great potential because they provide ubiquitous access to data and round-the-clock connectivity over wireless links. Our solution aims to provide users of handheld devices the capability to launch heavy computational tasks on computational and data Grids, monitor the jobs status during execution, and retrieve results after job completion. Users carry their jobs on their handheld devices in the form of executables (and associated libraries). Users can transparently view the status of their jobs and get back their outputs without having to know where they are being executed. In this way, our system is able to act as a high-throughput computing environment where devices ranging from powerful desktop machines to small handhelds can employ the power of the Grid. The results shown in this paper are readily applicable to the wider eScience community.Comment: 8 pages, 7 figures. Presented at the 3rd Int Conf on Mobile Computing & Ubiquitous Networking (ICMU06. London October 200

Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms

This deliverable describes the work done in task 3.1, Middleware analysis: Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms from work package 3, Middleware Implementation. The document is divided in four parts: The introduction with application scenarios and middleware requirements, Catnets middleware architecture, evaluation of existing middleware toolkits, and conclusions. -- Die Arbeit definiert Anforderungen an Grid und Peer-to-Peer Middleware Architekturen und analysiert diese auf ihre Eignung für die prototypische Umsetzung der Katallaxie. Eine Middleware-Architektur für die Umsetzung der Katallaxie in Application Layer Netzwerken wird vorgestellt.Grid Computing