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

Current challenges and future trends in the field of communication architectures for microgrids

[EN] The concept of microgrid has emerged as a feasible answer to cope with the increasing number of distributed renewable energy sources which are being introduced into the electrical grid. The microgrid communication network should guarantee a complete and bidirectional connectivity among the microgrid resources, a high reliability and a feasible interoperability. This is in a contrast to the current electrical grid structure which is characterized by the lack of connectivity, being a centralized-unidirectional system. In this paper a review of the microgrids information and communication technologies (ICT) is shown. In addition, a guideline for the transition from the current communication systems to the future generation of microgrid communications is provided. This paper contains a systematic review of the most suitable communication network topologies, technologies and protocols for smart microgrids. It is concluded that a new generation of peer-to-peer communication systems is required towards a dynamic smart microgrid. Potential future research about communications of the next microgrid generation is also identified.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant BES-2013-064539.Marzal-Romeu, S.; Salas-Puente, RA.; González Medina, R.; Garcerá, G.; Figueres Amorós, E. (2018). Current challenges and future trends in the field of communication architectures for microgrids. Renewable and Sustainable Energy Reviews. 82(2):3610-3622. https://doi.org/10.1016/j.rser.2017.10.101S3610362282

A Mini Review of Peer-to-Peer (P2P) for Vehicular Communication

In recent times, peer-to-peer (P2P) has evolved, where it leverages the capability to scale compared to server-based networks. Consequently, P2P has appeared to be the future distributed systems in emerging several applications. P2P is actually a disruptive technology for setting up applications that scale to numerous concurrent individuals. Thus, in a P2P distributed system, individuals become themselves as peers through contributing, sharing, and managing the resources in a network. In this paper, P2P for vehicular communication is explored. A comprehensive of the functioning concept of both P2P along with vehicular communication is examined. In addition, the advantages are furthermore conversed for a far better understanding on the implementation

Efficient Event Notification Middleware for Smart Microgrids over P2P Networks

© 2018 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Microgrids are moving towards large-scale smart distributed networks which demand an efficient and reliable communication infrastructure to manage, control and monitor energy resources. With regard to this, publisher/subscriber eventbased middleware has become relevant for large-scale distributed time applications because it allows decouple time and space between senders and receivers. Particularly the content publish/subscribe systems over structured peer-to-peer (P2P) networks has emerged to enhance scalability and dynamism of notification middleware systems. However, this type of systems use multicast routing schemes that still generate much network traffic and as a consequence an overload of the communication channel is produced. This results in inefficient network utilization and rapid depletion of network resources leading to unreliable operations, degradation of system performance and even instability of the microgrid. In this paper, a new content-based publish/subscribe notification middleware over structured P2P systems is proposed, such that smart microgrid communication requirements are met. This proposed system organizes the publications and subscriptions in a one dimensional representation using the Hilbert space filling curve. Through this representation, an innovative routing and matching algorithms are developed. Experimental results demonstrate that the proposed publisher/subscribe system significantly enhance efficiency of the system, network performance and the use of computational resources.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- 2 R. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under BES- 2013- 064539.Marzal-Romeu, S.; Salas-Puente, RA.; González-Medina, R.; Garcerá, G.; Figueres Amorós, E. (2018). Efficient Event Notification Middleware for Smart Microgrids over P2P Networks. IEEE Transactions on Smart Grid. https://doi.org/10.1109/TSG.2018.2865432

サーバクラスタでの低消費電力化のための移行モデルの研究

博士(工学)法政大学 (Hosei University

Large-Scale Distributed Coalition Formation

The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the ability to efficiently locate agents by resources that agents possess. Combined with a task model defined for CyberCraft, this technology feeds into an algorithm that constructs task coalitions in a large-scale DMAS. Experiments reveal the flexibility and effectiveness of these concepts for achieving maximum work throughput in a simulated CyberCraft environment

Energy-aware service provisioning in P2P-assisted cloud ecosystems

Cotutela Universitat Politècnica de Catalunya i Instituto Tecnico de LisboaEnergy has been emerged as a first-class computing resource in modern systems. The trend has primarily led to the strong focus on reducing the energy consumption of data centers, coupled with the growing awareness of the adverse impact on the environment due to data centers. This has led to a strong focus on energy management for server class systems. In this work, we intend to address the energy-aware service provisioning in P2P-assisted cloud ecosystems, leveraging economics-inspired mechanisms. Toward this goal, we addressed a number of challenges. To frame an energy aware service provisioning mechanism in the P2P-assisted cloud, first, we need to compare the energy consumption of each individual service in P2P-cloud and data centers. However, in the procedure of decreasing the energy consumption of cloud services, we may be trapped with the performance violation. Therefore, we need to formulate a performance aware energy analysis metric, conceptualized across the service provisioning stack. We leverage this metric to derive energy analysis framework. Then, we sketch a framework to analyze the energy effectiveness in P2P-cloud and data center platforms to choose the right service platform, according to the performance and energy characteristics. This framework maps energy from the hardware oblivious, top level to the particular hardware setting in the bottom layer of the stack. Afterwards, we introduce an economics-inspired mechanism to increase the energy effectiveness in the P2P-assisted cloud platform as well as moving toward a greener ICT for ICT for a greener ecosystem.La energía se ha convertido en un recurso de computación de primera clase en los sistemas modernos. La tendencia ha dado lugar principalmente a un fuerte enfoque hacia la reducción del consumo de energía de los centros de datos, así como una creciente conciencia sobre los efectos ambientales negativos, producidos por los centros de datos. Esto ha llevado a un fuerte enfoque en la gestión de energía de los sistemas de tipo servidor. En este trabajo, se pretende hacer frente a la provisión de servicios de bajo consumo energético en los ecosistemas de la nube asistida por P2P, haciendo uso de mecanismos basados en economía. Con este objetivo, hemos abordado una serie de desafíos. Para instrumentar un mecanismo de servicio de aprovisionamiento de energía consciente en la nube asistida por P2P, en primer lugar, tenemos que comparar el consumo energético de cada servicio en la nube P2P y en los centros de datos. Sin embargo, en el procedimiento de disminuir el consumo de energía de los servicios en la nube, podemos quedar atrapados en el incumplimiento del rendimiento. Por lo tanto, tenemos que formular una métrica, sobre el rendimiento energético, a través de la pila de servicio de aprovisionamiento. Nos aprovechamos de esta métrica para derivar un marco de análisis de energía. Luego, se esboza un marco para analizar la eficacia energética en la nube asistida por P2P y en la plataforma de centros de datos para elegir la plataforma de servicios adecuada, de acuerdo con las características de rendimiento y energía. Este marco mapea la energía desde el alto nivel independiente del hardware a la configuración de hardware particular en la capa inferior de la pila. Posteriormente, se introduce un mecanismo basado en economía para aumentar la eficacia energética en la plataforma en la nube asistida por P2P, así como avanzar hacia unas TIC más verdes, para las TIC en un ecosistema más verde.Postprint (published version

On service optimization in community network micro-clouds

Cotutela Universitat Politècnica de Catalunya i KTH Royal Institute of TechnologyInternet coverage in the world is still weak and local communities are required to come together and build their own network infrastructures. People collaborate for the common goal of accessing the Internet and cloud services by building Community networks (CNs). The use of Internet cloud services has grown over the last decade. Community network cloud infrastructures (i.e. micro-clouds) have been introduced to run services inside the network, without the need to consume them from the Internet. CN micro-clouds aims for not only an improved service performance, but also an entry point for an alternative to Internet cloud services in CNs. However, the adaptation of the services to be used in CN micro-clouds have their own challenges since the use of low-capacity devices and wireless connections without a central management is predominant in CNs. Further, large and irregular topology of the network, high software and hardware diversity and different service requirements in CNs, makes the CN micro-clouds a challenging environment to run local services, and to achieve service performance and quality similar to Internet cloud services. In this thesis, our main objective is the optimization of services (performance, quality) in CN micro-clouds, facilitating entrance to other services and motivating members to make use of CN micro-cloud services as an alternative to Internet services. We present an approach to handle services in CN micro-cloud environments in order to improve service performance and quality that can be approximated to Internet services, while also giving to the community motivation to use CN micro-cloud services. Furthermore, we break the problem into different levels (resource, service and middleware), propose a model that provides improvements for each level and contribute with information that helps to support the improvements (in terms of service performance and quality) in the other levels. At the resource level, we facilitate the use of community devices by utilizing virtualization techniques that isolate and manage CN micro-cloud services in order to have a multi-purpose environment that fosters services in the CN micro-cloud environment. At the service level, we build a monitoring tool tailored for CN micro-clouds that helps us to analyze service behavior and performance in CN micro-clouds. Subsequently, the information gathered enables adaptation of the services to the environment in order to improve their quality and performance under CN environments. At the middleware level, we build overlay networks as the main communication system according to the social information in order to improve paths and routes of the nodes, and improve transmission of data across the network by utilizing the relationships already established in the social network or community of practices that are related to the CNs. Therefore, service performance in CN micro-clouds can become more stable with respect to resource usage, performance and user perceived quality.Acceder a Internet sigue siendo un reto en muchas partes del mundo y las comunidades locales se ven en la necesidad de colaborar para construir sus propias infraestructuras de red. Los usuarios colaboran por el objetivo común de acceder a Internet y a los servicios en la nube construyendo redes comunitarias (RC). El uso de servicios de Internet en la nube ha crecido durante la última década. Las infraestructuras de nube en redes comunitarias (i.e., micronubes) han aparecido para albergar servicios dentro de las mismas redes, sin tener que acceder a Internet para usarlos. Las micronubes de las RC no solo tienen por objetivo ofrecer un mejor rendimiento, sino también ser la puerta de entrada en las RC hacia una alternativa a los servicios de Internet en la nube. Sin embargo, la adaptación de los servicios para ser usados en micronubes de RC conlleva sus retos ya que el uso de dispositivos de recursos limitados y de conexiones inalámbricas sin una gestión centralizada predominan en las RC. Más aún, la amplia e irregular topología de la red, la diversidad en el hardware y el software y los diferentes requisitos de los servicios en RC convierten en un desafío albergar servicios locales en micronubes de RC y obtener un rendimiento y una calidad del servicio comparables a los servicios de Internet en la nube. Esta tesis tiene por objetivo la optimización de servicios (rendimiento, calidad) en micronubes de RC, facilitando la entrada a otros servicios y motivando a sus miembros a usar los servicios en la micronube de RC como una alternativa a los servicios en Internet. Presentamos una aproximación para gestionar los servicios en entornos de micronube de RC para mejorar su rendimiento y calidad comparable a los servicios en Internet, a la vez que proporcionamos a la comunidad motivación para usar los servicios de micronube en RC. Además, dividimos el problema en distintos niveles (recursos, servicios y middleware), proponemos un modelo que proporciona mejoras para cada nivel y contribuye con información que apoya las mejoras (en términos de rendimiento y calidad de los servicios) en los otros niveles. En el nivel de los recursos, facilitamos el uso de dispositivos comunitarios al emplear técnicas de virtualización que aíslan y gestionan los servicios en micronubes de RC para obtener un entorno multipropósito que fomenta los servicios en el entorno de micronube de RC. En el nivel de servicio, construimos una herramienta de monitorización a la medida de las micronubes de RC que nos ayuda a analizar el comportamiento de los servicios y su rendimiento en micronubes de RC. Luego, la información recopilada permite adaptar los servicios al entorno para mejorar su calidad y rendimiento bajo las condiciones de una RC. En el nivel de middleware, construimos redes de overlay que actúan como el sistema de comunicación principal de acuerdo a información social para mejorar los caminos y las rutas de los nodos y mejoramos la transmisión de datos a lo largo de la red al utilizar las relaciones preestablecidas en la red social o la comunidad de prácticas que están relacionadas con las RC. De este modo, el rendimiento en las micronubes de RC puede devenir más estable respecto al uso de recursos, el rendimiento y la calidad percibidas por el usuario.Postprint (published version