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    Network service registration based on role-goal-process-service meta-model in a P2P network

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    Service composition-based network software customisation is currently a research hotspot in the field of software engineering. A key problem of the hotspot is how to efficiently discover services distributed over the Internet. In the service oriented architecture, service discovery suffers from the performance bottleneck of centralised universal description discovery and integration (UDDI), and inaccurate matching of service semantics. In this study, the authors describe a novel method for service labelling, registration and discovery, which is based on the role-goal-process-service meta-model. This approach enables ones to achieve accurate matching of service semantics by extending web service description language with RGP demand-information. The authors also suggest a peer-to-peer (P2P)-based architecture of service discovery to address the issues in the UDDI bottleneck and the complexity of semantic computation. By adopting the proposed approach, an experiment prototype system has been designed and implemented in Beijing municipal transportation system. The experimental results show the proposed approach is effective in addressing the aforementioned problems

    Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS

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    Structural relations established among agents influence the performance of decentralized service discovery process in multiagent systems. Moreover, distributed systems should be able to adapt their structural relations to changes in environmental conditions. In this article, we present a service-oriented multiagent systems, where agents initially self-organize their structural relations based on the similarity of their services. During the service discovery process, agents integrate a mechanism that facilitates the self-organization of their structural relations to adapt the structure of the system to the service demand. This mechanism facilitates the task of decentralized service discovery and improves its performance. Each agent has local knowledge about its direct neighbors and the queries received during discovery processes. With this information, an agent is able to analyze its structural relations and decide when it is more appropriate to modify its direct neighbors and select the most suitable acquaintances to replace them. The experimental evaluation shows how this self-organization mechanism improves the overall performance of the service discovery process in the system when the service demand changesThis work is partially supported by the Spanish Ministry of Science and Innovation through grants CSD2007-0022 (CONSOLIDER-INGENIO 2010), TIN2012-36586-C03-01, TIN2012-36586-C03-01, TIN2012-36586-C03-02, PROMETEOII/2013/019, and FPU grant AP-2008-00601 awarded to E. Del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Vasirani, M.; Fernández, A. (2014). Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS. ACM Transactions on Autonomous and Adaptive Systems. 9(3):1-24. https://doi.org/10.1145/2651423S12493Sherief Abdallah and Victor Lesser. 2007. Multiagent reinforcement learning and self-organization in a network of agents. In Proceedings of the 6th International Conference on Autonomous Agents and Multiagent Systems. 172--179.Lada A. Adamic and Bernardo A. Huberman. 2002. Zipf’s law and the Internet. Glottometrics 3, 143--150.Muntasir Al-Asfoor, Brendan Neville, and Maria Fasli. 2012. Heuristic resource search in a self-organised distributed multi agent system. In Proceedings of the 6th International Workshop on Self-Organizing Systems. 84--89.Mathieu Aquin, Salman Elahi, and Enrico Motta. 2010. Personal monitoring of Web information exchange: Towards Web lifelogging. In Proceedings of the Web Science Conference.Ulrich Basters and Matthias Klusch. 2006. RS2D: Fast adaptive search for semantic Web services in unstructured p2p networks. In Proceedings of the International Semantic Web Conference. 87--100.Umesh Bellur and Roshan Kulkarni. 2007. Improved matchmaking algorithm for semantic Web services based on bipartite graph matching. In Proceedings of the International Semantic Web Conference. 86--93.Devis Bianchini, Valeria De Antonellis, and Michele Melchiori. 2009. Service-based semantic search in p2p systems. In Proceedings of the European Conference on Web Services. 7--16.Bartosz Biskupski, Jim Dowling, and Jan Sacha. 2007. Properties and mechanisms of self-organizing MANET and P2P systems. ACM Transactions on Autonomous and Adaptive Systems 2, 1, 1--34.Alberto Blanc, Yi-Kai Liu, and Amin Vahdat. 2005. Designing incentives for peer-to-peer routing. In Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies. 374--385.Michael Bowling and Manuela Veloso. 2002. Multiagent learning using a variable learning rate. Artificial Intelligence 136, 215--250.Frances M. T. Brazier, Jeffrey O. Kephart, H. Van Dyke Parunak, and Michael N. Huhns. 2009. Agents and service-oriented computing for autonomic computing: A research agenda. IEEE Internet Computing 13, 3, 82--87.Tyson Condie, Sepandar D. Kamvar, and Hector Garcia-Molina. 2004. Adaptive peer-to-peer topologies. In Proceedings of the 4th International Conference on Peer-to-Peer Computing. 53--62.Arturo Crespo and Hector Garcia-Molina. 2002. Routing indices for peer-to-peer systems. In Proceedings of the 22nd International Conference on Distributed Computing Systems. 23--32.Elena Del Val, Natalia Criado, Carlos Carrascosa, Vicente Julian, Miguel Rebollo, Estefania Argente, and Vicente Botti. 2010. THOMAS: A service-oriented framework for virtual organizations. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10). 1631--1632.Elena Del Val, Miguel Rebollo, and Vicente Botti. 2011. Introducing homophily to improve semantic service search in a self-adaptive system. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems. 1241--1242.Elena Del Val, Miguel Rebollo, and Vicente Botti. 2012a. Enhancing decentralized service discovery in open service-oriented multi-agent systems. Autonomous Agents and Multi-Agent Systems 28, 1, 1--30.Elena Del Val, Miguel Rebollo, and Vicente Botti. 2012b. Promoting cooperation in service-oriented MAS through social plasticity and incentives. Journal of Systems and Software 86, 2, 520--537.Gianni Di Caro, Frederick Ducatelle, and Luca Maria Gambardella. 2005. AntHocNet: An adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications 16, 443--455.Ding Ding, Lei Liu, and Hartmut Schmeck. 2010. Service discovery in self-organizing service-oriented environments. In Proceedings of the 2010 IEEE Asia-Pacific Services Computing Conference. 717--724.Sergey N. Dorogovtsev and Jose F. F. Mendes. 2003. Evolution of Networks: From Biological Nets to the Internet and WWW. Oxford University Press.Giovanna Di Marzo Serugendo, Marie-Pierre Gleizes, and Anthony Karageorgos. 2011. Self-Organizing Software: From Natural to Artificial Adaptation. Natural Computing Series.Erik Einhorn and Andreas Mitschele-Thiel. 2008. RLTE: Reinforcement learning for traffic-engineering. In Proceedings of the 2nd International Conference on Autonomous Infrastructure, Management, and Security. 120--133.Nelson Fernandez, Carlos Maldonado, and Carlos Gershenson. 2014. Information measures of complexity, emergence, self-organization, homeostasis, and autopoiesis. In Guided Self-Organization: Inception. Emergence, Complexity and Computation, Vol. 9. Springer, 19--51. DOI: http://dx.doi.org/10.1007/978-3-642-53734-9_2Jose Luis Fernandez-Marquez, Josep Lluis Arcos, and Giovanna Di Marzo Serugendo. 2012. A decentralized approach for detecting dynamically changing diffuse event sources in noisy WSN environments. Applied Artificial Intelligence 26, 4, 376--397. DOI: http://dx.doi.org/10.1080/08839514.2012.653659Agostino Forestiero, Carlo Mastroianni, and Michela Meo. 2009. Self-Chord: A bio-inspired algorithm for structured P2P systems. In Proceedings of the 9th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing. 44--51.Matthew E. Gaston and Marie des Jardins. 2005. Agent-organized networks for multi-agent production and exchange. In Proceedings of the 20th AAAI Conference on Artificial Intelligence. 77--82.Nathan Griffiths and Michael Luck. 2010. Changing neighbours: Improving tag-based cooperation. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems. 249--256.Peter Haase, Ronny Siebes, and Frank van Harmelen. 2008. Expertise-based peer selection in peer-to-peer networks. Knowledge and Information Systems 15, 1, 75--107.Philip N. Howard, Lee Rainee, and Steve Jones. 2001. Days and nights on the Internet. American Behavioural Scientist, 383--404.Bernardo A. Huberman and Lada A. Adamic. 2000. The nature of markets in the WWW. Quarterly Journal of Electronic Commerce 1, 5--12.Michael N. Huhns et al. 2005. Research directions for service-oriented multiagent systems. IEEE Internet Computing 9, 6, 65--70.Tomoko Itao, Tatsuya Suda, Tetsuya Nakamura, Miyuki Imada, Masato Matsuo, and Tomonori Aoyama. 2001. Jack-in-the-Net: Adaptive networking architecture for service emergence. In Proceedings of the Asian-Pacific Conference on Communications. 9.Emily M. Jin, Michelle Girvan, and Mark E. J. Newman. 2001. Structure of growing social networks. Physical Review E 64, 4, 046132.Sachin Kamboj and Keith S. Decker. 2007. Organizational self-design in semi-dynamic environments. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems. 335--337.Rahamatullah Khondoker, S. M. Taslim Arif, Nathan Kerr, and Dennis Schwerdel. 2011. Self-organizing communication services in future network architectures. In Proceedings of the 5th International Workshop on Self-Organizing Systems.Matthias Klusch, Benedikt Fries, and Katia Sycara. 2009. OWLS-MX: A hybrid Semantic Web service matchmaker for OWL-S services. Web Semantics Science Services and Agents on the World Wide Web 7, 2, 121--133.Dionisis Kontominas, Paraskevi Raftopoulou, Christos Tryfonopoulos, and Euripides G. M. Petrakis. 2013. DS4: A distributed social and semantic search system. Advances in Information Retrieval 7814, 832--836.Ramachandra Kota, Nicholas Gibbins, and Nicholas R. Jennings. 2012. Decentralized approaches for self-adaptation in agent organizations. ACM Transactions on Autonomous and Adaptive Systems 7, 1, Article No. 1.Paul Lazarsfeld. 1954. Friendship as a social process: A substantive and methodological analysis. In Freedom and Control in Modern Society. Van Nostrand, New York, NY.Paulo Leito. 2013. Towards self-organized service-oriented multi-agent systems. In Service Orientation in Holonic and Multi Agent Manufacturing and Robotics. Studies in Computational Intelligence, Vol. 472. Springer, 41--56.W. Sabrina Lin, Hong Vikcy Zhao, and K. J. Ray Liu. 2009. Incentive cooperation strategies for peer-to-peer live multimedia streaming social networks. IEEE Transactions on Multimedia 11, 3, 396--412.Sheila A. McIlraith, Tran Cao Son, and Honglei Zeng. 2001. Semantic Web services. IEEE Intelligent Systems 16, 2, 46--53.Miller McPherson, Lynn Smith-Lovin, and James Cook. 2001. Birds of a feather: Homophily in social networks. Annual Review of Sociology 27, 415--444.Vivek Nallur and Rami Bahsoon. 2012. A decentralized self-adaptation mechanism for service-based applications in the cloud. IEEE Transactions on Software Engineering 99, 591--612.Aris Ouksel, Yair Babad, and Thomas Tesch. 2004. Matchmaking software agents in B2B markets. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences. 1--9.Massimo Paolucci, Takahiro Kawamura, Terry R. Payne, and Katia P. Sycara. 2002. Semantic matching of Web services capabilities. In Proceedings of the 1st International Semantic Web Conference. 333--347.Leonid Peshkin and Virginia Savova. 2002. Reinforcement learning for adaptive routing. In Proceedings of the 2002 International Conference on Neural Networks (IJCNN’02). 1825--1830.Paraskevi Raftopoulou and Euripides G. M. Petrakis. 2008. iCluster: A self-organizing overlay network for P2P information retrieval. In Proceedings of the 30th European Conference on Advances in Information Retrieval (ECIR’08). 65--76.Sharmila Savarimuthu, Maryam Purvis, Martin Purvis, and Bastin Tony Roy Savarimuthu. 2011. Mechanisms for the self-organization of peer groups in agent societies. In Multi-Agent-Based Simulation XI. Lecture Notes in Computer Science, Vol. 6532. Springer, 93--107.Giovanna Di Marzo Serugendo, Marie-Pierre Gleizes, and Anthony Karageorgos. 2005. Self-organization in multi-agent systems. Knowledge Engineering Review 20, 2, 165--189.Abdul Khalique Shaikh, Saadat M. Alhashmi, and Rajendran Parthiban. 2012. A semantic impact in decentralized resource discovery mechanism for grid computing environments. In Algorithms and Architectures for Parallel Processing. Lecture Notes in Computer Science, Vol. 7440. Springer, 206--216.Qixiang Sun and Hector Garcia-Molina. 2004. SLIC: A selfish link-based incentive mechanism for unstructured peer-to-peer networks. In Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS’04). 506--515.Mirko Viroli and Franco Zambonelli. 2010. A biochemical approach to adaptive service ecosystems. Information Sciences 180, 10, 1876--1892. DOI: http://dx.doi.org/10.1016/j.ins.2009.11.021Li Wang. 2011. SoFA: An expert-driven, self-organization peer-to-peer semantic communities for network resource management. Expert Systems with Applications 38, 1, 94--105.Kevin Werbach. 2000. Syndication—the emerging model for business in the Internet era. Harvard Business Review 78, 3, 84--93, 214.Tom Wolf and Tom Holvoet. 2005. Emergence versus self-organisation: Different concepts but promising when combined. In Engineering Self-Organising Systems. Lecture Notes in Computer Science, Vol. 3464. Springer, 1--15.Haizheng Zhang, W. Bruce Croft, Brian Levine, and Victor Lesser. 2004. A multi-agent approach for peer-to-peer based information retrieval system. In Proceedings of the 3rd International Conference on Autonomous Agents and Multiagent Systems, Vol. 1. 456--463.Ming Zhong. 2006. Popularity-biased random walks for peer-to-peer search under the square-root principle. In Proceedings of the 5th International Workshop on Peer-to-Peer Systems

    An Overview of Search Strategies in Distributed Environments

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    [EN] Distributed systems are populated by a large number of heterogeneous entities that join and leave the systems dynamically. These entities act as clients and providers and interact with each other in order to get a resource or to achieve a goal. To facilitate the collaboration between entities the system should provide mechanisms to manage the information about which entities or resources are available in the system at a certain moment, as well as how to locate them in an e cient way. However, this is not an easy task in open and dynamic environments where there are changes in the available resources and global information is not always available. In this paper, we present a comprehensive vision of search in distributed environments. This review does not only considers the approaches of the Peer-to-Peer area, but also the approaches from three more areas: Service-Oriented Environments, Multi-Agent Systems, and Complex Networks. In these areas, the search for resources, services, or entities plays a key role for the proper performance of the systems built on them. The aim of this analysis is to compare approaches from these areas taking into account the underlying system structure and the algorithms or strategies that participate in the search process.Work partially supported by the Spanish Ministry of Science and Innovation through grants TIN2009-13839-C03-01, CSD2007-0022 (CONSOLIDER-INGENIO 2010), PROMETEO 2008/051, PAID-06-11-2048, and FPU grant AP-2008-00601 awarded to E. del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Botti, V. (2013). An Overview of Search Strategies in Distributed Environments. Knowledge Engineering Review. 1-33. https://doi.org/10.1017/S0269888913000143S133Sigdel K. , Bertels K. , Pourebrahimi B. , Vassiliadis S. , Shuai L. 2005. A framework for adaptive matchmaking in distributed computing. In Proceedings of GRID Workshop.Prabhu S. 2007. Towards distributed dynamic web service composition. In ISADS '07: Proceedings of the 8th International Symposium on Autonomous Decentralized Systems. IEEE Computer Society, 25–32.Meshkova, E., Riihijärvi, J., Petrova, M., & Mähönen, P. (2008). A survey on resource discovery mechanisms, peer-to-peer and service discovery frameworks. Computer Networks, 52(11), 2097-2128. doi:10.1016/j.comnet.2008.03.006Martin D. , Paolucci M. , Wagner M. 2007. Towards semantic annotations of web services: Owl-s from the sawsdl perspective. In Proceedings of Workshop OWL-S: Experiences and Directions at 4th European Semantic Web Conference, Innsbruck, Austria.Ogston E. , Vassiliadis S. 2001b. Matchmaking among minimal agents without a facilitator. In Proceedings of the 5th International Conference on Autonomous Agents, Bologna, Italy, 608–615.Martin D. , Burstein M. , Hobbs J. , Lassila O. , McDermott D. , McIlraith S. , Narayanan S. , Paolucci M. , Parsia B. , Payne T. , Sirin E. , Srinivasan N. , Sycara K. 2004. Owl-s: Semantic Markup for Web Services. http://www.w3.org/Submission/OWL-S/Eng 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.2005.1610546Liang J. , Kumar R. , Ross K. 2005. Understanding kazaa. In Proceedings of the 5th New York Metro Area Networking Workshop (NYMAN), New York, USA.Ko, S. Y., Gupta, I., & Jo, Y. (2008). A new class of nature-inspired algorithms for self-adaptive peer-to-peer computing. ACM Transactions on Autonomous and Adaptive Systems, 3(3), 1-34. doi:10.1145/1380422.1380426Kleinberg J. 2001. Small-world phenomena and the dynamics of information. In Advances in Neural Information Processing Systems (NIPS), Dietterich, T. G., Becker, S. & Ghahramani, Z. (eds). MIT Press, 431–438.Jha S. , Chalasani P. , Shehory O. , Sycara K. 1998. A formal treatment of distributed matchmaking. In Proceedings of the 2nd International Conference on Autonomous Agents, Sycara, K. P. & Wooldridge, M. (eds). ACM, 457–458.Huhns, M. N. (2002). Agents as Web services. IEEE Internet Computing, 6(4), 93-95. doi:10.1109/mic.2002.1020332He Q. , Yan J. , Yang Y. , Kowalczyk R. , Jin H. 2008. Chord4s: A p2p-based decentralised service discovery approach. In IEEE International Conference on Services Computing, Honolulu, Hawaii, USA, 1, 221–228.Lv Q. , Cao P. , Cohen E. , Li K. , Shenker S. 2002. Search and replication in unstructured peer-to-peer networks. In Proceedings of the 16th International Conference on Supercomputing, ICS '02. ACM, 84–95.Maymounkov P. , Mazieres D. 2002. Kademlia: a peer-to-peer information system based on the xor metric. Proceedings of the 1st International Workshop on Peer-to Peer Systems (IPTPS02), Cambridge, MA, USA.Stoica, I., Morris, R., Karger, D., Kaashoek, M. F., & Balakrishnan, H. (2001). Chord. ACM SIGCOMM Computer Communication Review, 31(4), 149-160. doi:10.1145/964723.383071Fernández A. , Ossowski S. , Vasirani M. 2008. General Architecture. CASCOM: Intelligent Service Coordination in the Semantic Web. Whitestein Series in Software Agent Technologies and Autonomic Computing, 143–160.Ding D. , Liu L. , Schmeck H. 2010. Service discovery in self-organizing service-oriented environments. In Proceedings of the 2010 IEEE Asia-Pacific Services Computing Conference. IEEE Computer Society, 717–724.Crespo A. , Garcia-Molina H. 2004. Semantic overlay networks for p2p systems. In Proceedings of the 3rd International Workshop on Agents and Peer-to-Peer Computing, Lecture Notes in Computer Science, 3601, 1–13. Springer.Rao J. , Su X. 2004. A survey of automated web service composition methods. In Proceedings of the 1st International Workshop on Semantic Web Services and Web Process Composition, SWSWPC 2004, San Diego, CA, USA, 43–54.Constantinescu I. , Faltings B. 2003. Efficient matchmaking and directory services. In Web Intelligence. IEEE Computer Society, 75–81.Cong Z. , Fernández A. 2010. Behavioral matchmaking of semantic web services. In Proceedings of the 4th International Joint Workshop on Service Matchmaking and Resource Retrieval in the Semantic Web (SMR2), Karlsruhe, Germany, 667, 131–140.Cholvi V. , Rodero-Merino L. 2007. Using random walks to find resources in unstructured self-organized p2p networks. In Proceedings of the IEEE Workshop on Dependable Application Support in Self-Organizing Networks, Edinburgh, UK, 51–56.Vázquez-Salceda J. , Vasconcelos W. W. , Padget J. , Dignum F. , Clarke S. , Roig M. P. 2010. Alive: an agent-based framework for dynamic and robust service-oriented applications. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1, AAMAS '10, International Foundation for Autonomous Agents and Multiagent Systems, 1637–1638.Liu L. , Schmeck H. 2010. Enabling self-organising service level management with automated negotiation. In Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT '10, Huang, J. X., Ghorbani, A. A., Hacid, M.-S. & Yamaguchi, T. (eds). IEEE Computer Society, 42–45.Campo C. , Martin A. , Garcia C. , Breuer P. 2002. Service discovery in pervasive multi-agent systems. In AAMAS Workshop on Ubiquitous Agents on Embedded, Wearable, and Mobile Agents, Bologna, Italy.Brazier, F. M. T., Kephart, J. O., Parunak, H. V. D., & Huhns, M. N. (2009). Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda. IEEE Internet Computing, 13(3), 82-87. doi:10.1109/mic.2009.51Bisnik N. , Abouzeid A. 2005. Modeling and analysis of random walk search algorithms in p2p networks. In Proceedings of the 2nd International Workshop on Hot Topics in Peer-to-Peer Systems, Anglano, C. & Mancini, L. V. (eds). IEEE Computer Society, 95–103.Huhns, M. N., Singh, M. P., Burstein, M., Decker, K., Durfee, E., Finin, T., … Zavala, L. (2005). Research Directions for Service-Oriented Multiagent Systems. IEEE Internet Computing, 9(6), 65-70. doi:10.1109/mic.2005.132Ben-Ami D. , Shehory O. 2005. A comparative evaluation of agent location mechanisms in large scale mas. In Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS '05, Pechoucek, M., Steiner, D. & Thompson, S. (eds). ACM, 339–346.Basters U. , Klusch M. 2006. Rs2d: Fast adaptive search for semantic web services in unstructured p2p networks. In International Semantic Web Conference, Lecture Notes in Computer Science 4273, 87–100. Springer.Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509Liu G. , Wang Y. , Orgun M. 2010. Optimal social trust path selection in complex social networks. In Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI). AAAI Press, 1391–1398.Adamic, L., & Adar, E. (2005). How to search a social network. Social Networks, 27(3), 187-203. doi:10.1016/j.socnet.2005.01.007Kalogeraki V. , Gunopulos D. , Zeinalipour-Yazti D. 2002. A local search mechanism for peer-to-peer networks. In Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM '02). ACM, 300–307.Babaoglu O. , Meling H. , Montresor A. 2002. Anthill: a framework for the development of agent-based peer-to-peer systems. In Proceedings of the 22nd International Conference on Distributed Computing Systems, Vienna, Austria, 15–22.Yang B. , Garcia-Molina H. 2002. Efficient search in peer-to-peer networks. In Proceedings of the International Conference on Distributed Computing Systems (ICDCS).Mokhtar S. , Kaul A. , Georgantas N. , Issarny V. 2006. Towards efficient matching of semantic web service capabilities. In Proceedings of International Workshop on Web Services – Modeling and Testing, Palermo, Italy.Fernández A. , Vasirani M. , Cáceres C. , Ossowski S. 2006. Role-based service description and discovery. In AAMAS-06 Workshop on Service-Oriented Computing and Agent-Based Engineering, 1–14.Bailey J. 2006. Fast discovery of interesting collections of web services. In WI '06: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence. IEEE Computer Society, 152–160.Rowstron A. I. T. , Druschel P. 2001. Pastry: scalable, decentralized object location, and routing for large-scale peer-to-peer systems. In Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg, Middleware '01, Sventek, J. & Coulson, G. (eds). Springer-Verlag, 329–350.Kleinberg J. 2006. Complex networks and decentralized search algorithms. In Proceedings of the International Congress of Mathematicians (ICM), Madrid, Spain.Bachlechner D. , Siorpaes K. , Fensel D. , Toma I. 2006. Web service discovery – a reality check. In Proceedings of the 3rd European Semantic Web Conference, Seoul, South Korea.Lopes, 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.3.2.38-47Klusch M. , Fries B. , Sycara K. 2006. Automated semantic web service discovery with owls-mx. In Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS '06, Nakashima, H., Wellman, M. P., Weiss, G. & Stone, P. (eds). ACM, 915–922.Ogston E. , Vassiliadis S. 2001a. Local distributed agent matchmaking. In Proceedings of the 9th International Conference on Cooperative Information Systems, Trento, Italy.Nguyen V. , Martel C. 2005. Analyzing and characterizing small-world graphs. In SODA '05: Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics.Amaral, L. A. N., & Ottino, J. M. (2004). Complex networks. The European Physical Journal B - Condensed Matter, 38(2), 147-162. doi:10.1140/epjb/e2004-00110-5Crespo A. , Garcia-Molina H. 2002. Routing Indices For Peer-to-Peer Systems. In Proceedings of the 22nd International Conference on Distributed Computing Systems (ICDCS'02). IEEE Computer Society, 23.Manku G. S. , Bawa M. , Raghavan P. , Inc V. 2003. Symphony: Distributed hashing in a small world. In Proceedings of the 4th USENIX Symposium on Internet Technologies and Systems, Seattle, USA, 127–140.Chawathe Y. , Ratnasamy S. , Breslau L. , Lanham N. , Shenker S. 2003. Making gnutella-like p2p systems scalable. In Proceedings of the 2003 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, SIGCOMM '03, Feldmann, A., Zitterbart, M., Crowcroft, J. & Wetherall, D. (eds). ACM, 407–418.Yu S. , Liu J. , Le J. 2004. Decentralized web service organization combining semantic web and peer to peer computing. In ECOWS, Lecture Notes in Computer Science 3250, 116–127. Springer.Chaari S. , Badr Y. , Biennier F. 2008. Enhancing web service selection by qos-based ontology and ws-policy. In Proceedings of the 2008 ACM Symposium on Applied Computing, SAC '08, Wainwright, R. L. & Haddad, H. (eds). ACM, 2426–2431.Michlmayr E. 2006. Ant algorithms for search in unstructured peer-to-peer networks. In Proceedings of the 22nd International Conference on Data Engineering (ICDE), Atlanta, GA, USA.Perryea C. , Chung S. 2006. Community-based service discovery. In Proceedings of the International Conference on Web Services, Chicago, IL, USA, 903–906.Upadrashta Y. , Vassileva J. , Grassmann W. 2005. Social networks in peer-to-peer systems. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences, Big Island, Hawaii, USA.Satyanarayanan, M. (2001). Pervasive computing: vision and challenges. IEEE Personal Communications, 8(4), 10-17. doi:10.1109/98.943998Kota R. , Gibbins N. , Jennings N. R 2009. Self-organising agent organisations. In Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems – Volume 2, AAMAS '09. International Foundation for Autonomous Agents and Multiagent Systems, 797–804.Kleinberg, J. M. (2000). Navigation in a small world. Nature, 406(6798), 845-845. doi:10.1038/35022643Watts, D. J. (2004). The «New» Science of Networks. Annual Review of Sociology, 30(1), 243-270. doi:10.1146/annurev.soc.30.020404.104342Risson, J., & Moors, T. (2006). Survey of research towards robust peer-to-peer networks: Search methods. Computer Networks, 50(17), 3485-3521. doi:10.1016/j.comnet.2006.02.001PAPAZOGLOU, M. P., TRAVERSO, P., DUSTDAR, S., & LEYMANN, F. (2008). SERVICE-ORIENTED COMPUTING: A RESEARCH ROADMAP. International Journal of Cooperative Information Systems, 17(02), 223-255. doi:10.1142/s0218843008001816Shvaiko P. , Euzenat J. 2008. Ten challenges for ontology matching. In On the Move to Meaningful Internet Systems: OTM 2008, Meersman, R. & Tari, Z. (eds), Lecture Notes in Computer Science 5332, 1164–1182. Springer.BOCCALETTI, S., LATORA, V., MORENO, Y., CHAVEZ, M., & HWANG, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4-5), 175-308. doi:10.1016/j.physrep.2005.10.009Bianchini D. , Antonellis V. D. , Melchiori M. 2009. Service-based semantic search in p2p systems. In Proceedings of the 2009 Seventh IEEE European Conference on Web Services, ECOWS '09, Eshuis, R., Grefen, P. & Papadopoulos, G. A. (eds). IEEE Computer Society, 7–16.Bromuri S. , Urovi V. , Morge M. , Stathis K. , Toni F. 2009. A multi-agent system for service discovery, selection and negotiation. In Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems, Sierra, C. & Castelfranchi, C. (eds). International Foundation for Autonomous Agents and Multiagent Systems, 1395–1396.Gummadi, P. K., Saroiu, S., & Gribble, S. D. (2002). A measurement study of Napster and Gnutella as examples of peer-to-peer file sharing systems. ACM SIGCOMM Computer Communication Review, 32(1), 82. doi:10.1145/510726.510756Tsoumakos D. , Roussopoulos N. 2003. Adaptive probabilistic search for peer-to-peer networks. In Peer-to-Peer Computing, Linköping, Sweeden, 102–109.Schmidt, C., & Parashar, M. (2004). A Peer-to-Peer Approach to Web Service Discovery. World Wide Web, 7(2), 211-229. doi:10.1023/b:wwwj.0000017210.55153.3dDimakopoulos V. V. , Pitoura E. 2003. A peer-to-peer approach to resource discovery in multi-agent systems. In Proceedings of Cooperative Information Agents, Lecture Notes in Computer Science 2782, 62–77. Springer.Skoutas D. , Sacharidis D. , Kantere V. , Sellis T. 2008. Efficient semantic web service discovery in centralized and p2p environments. In The Semantic Web – ISWC 2008, Sheth, A., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T. & Thirunarayan, K. (eds), Lecture Notes in Computer Science 5318, 583–598. Springer-Verlag.Val E. D. , Rebollo M. 2007. Service Discovery and Composition in Multiagent Systems. In Proceedings of 5th European Workshop On Multi-Agent Systems (EUMAS 2007). Association Tunisienne D'Intelligence Artificielle, 197–212.Srinivasan N. , Paolucci M. , Sycara K. 2004. Adding owl-s to uddi, implementation and throughput. In First International Workshop on Semantic Web Services and Web Process Composition (SWSWPC 2004), San Diego, CA, USA.Thadakamalla, H. P., Albert, R., & Kumara, S. R. T. (2007). Search in spatial scale-free networks. New Journal of Physics, 9(6), 190-190. doi:10.1088/1367-2630/9/6/190Papazoglou, M. P., Traverso, P., Dustdar, S., & Leymann, F. (2007). Service-Oriented Computing: State of the Art and Research Challenges. Computer, 40(11), 38-45. doi:10.1109/mc.2007.400Travers, J., & Milgram, S. (1969). An Experimental Study of the Small World Problem. Sociometry, 32(4), 425. doi:10.2307/2786545Val E. D. , Rebollo M. , Botti V. 2011. Introducing homophily to improve semantic service search in a self-adaptive system. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems, Taipei, Taiwan.Xiao Fan Wang, & Guanrong Chen. (2003). Complex networks: Small-world, scale-free and beyond. IEEE Circuits and Systems Magazine, 3(1), 6-20. doi:10.1109/mcas.2003.1228503Argente, E., Botti, V., Carrascosa, C., Giret, A., Julian, V., & Rebollo, M. (2010). An abstract architecture for virtual organizations: The THOMAS approach. Knowledge and Information Systems, 29(2), 379-403. doi:10.1007/s10115-010-0349-1Watts, D. J. (2002). Identity and Search in Social Networks. Science, 296(5571), 1302-1305. doi:10.1126/science.1070120Simsek Ö. , Jensen D. 2005. Decentralized search in networks using homophily and degree disparity. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Edinburgh, UK, 304–310.Vanthournout, K., Deconinck, G., & Belmans, R. (2005). A taxonomy for resource discovery. Personal and Ubiquitous Computing, 9(2), 81-89. doi:10.1007/s00779-004-0312-9Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440-442. doi:10.1038/30918Wei, Y., & Blake, M. B. (2010). Service-Oriented Computing and Cloud Computing: Challenges and Opportunities. IEEE Internet Computing, 14(6), 72-75. doi:10.1109/mic.2010.147Weyns, D., & Georgeff, M. (2010). Self-Adaptation Using Multiagent Systems. IEEE Software, 27(1), 86-91. doi:10.1109/ms.2010.18Pirró G. , Trunfio P. , Talia D. , Missier P. , Goble C. 2010. Ergot: a semantic-based system for service discovery in distributed infrastructures. In Proceedings of the 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), Melbourne, Australia, 263–272.Yang B. , Garcia-Molina H. 2003. Designing a super-peer network. International Conference on Data Engineering, Bangalore, India, 49.Zhang H. , Croft W. B. , Levine B. , Lesser V. 2004a. A multi-agent approach for peer-to-peer based information retrieval system. In Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems – Volume 1, AAMAS '04. IEEE Computer Society, 456–463.Zhang, H., Goel, A., & Govindan, R. (2004). Using the small-world model to improve Freenet performance. Computer Networks, 46(4), 555-574. doi:10.1016/j.comnet.2004.05.004Sycara, K., Paolucci, M., Soudry, J., & Srinivasan, N. (2004). Dynamic discovery and coordination of agent-based semantic web services. IEEE Internet Computing, 8(3), 66-73. doi:10.1109/mic.2004.1297276Dell'Amico M. 2006. Highly clustered networks with preferential attachment to close nodes. In Proceedings of the European Conference on Complex Systems 2006, Oxford, UK.Mullender, S. J., & Vitányi, P. M. B. (1988). Distributed match-making. Algorithmica, 3(1-4), 367-391. doi:10.1007/bf01762123McIlraith, S. A., Son, T. C., & Honglei Zeng. (2001). Semantic Web services. IEEE Intelligent Systems, 16(2), 46-53. doi:10.1109/5254.920599Gkantsidis, C., Mihail, M., & Saberi, A. (2006). Random walks in peer-to-peer networks: Algorithms and evaluation. Performance Evaluation, 63(3), 241-263. doi:10.1016/j.peva.2005.01.002Zhong M. 2006. Popularity-biased random walks for peer-to-peer search under the square-root principle. In Proceedings of the 5th International Workshop on Peer-to-Peer Systems (IPTPS), Santa Barbara, CA, USA.Cao J. , Yao Y. , Zheng X. , Liu B. 2010. Semantic-based self-organizing mechanism for service registry and discovery. In Proceedings of the 14th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Shanghai, China, 345–350.Ratnasamy S. , Francis P. , Handley M. , Karp R. , Shenker S. 2001. A scalable content-addressable network. In Proceedings of the 2001 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM '01), Cruz, R. & Varghese, G. (eds). ACM.Ouksel A. , Babad Y. , Tesch T. 2004. Matchmaking software agents in b2b markets. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04), Big Island, Hawaii, USA.Slivkins A. 2005. Distance estimation and object

    Discovering Network Neighborhoods Using Peer-to-Peer Lookups

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    In many distributed applications, end hosts need to know the network locations of other nearby participating hosts in order to enhance overall performance. Potential applications that can benefit from the location information include automatic selection of nearby Web servers, proximity routing in a peer-to-peer system, and loss recovery in reliable multicasting. We focus in this paper on the network neighborhood discovery problem in large-scale distributed systems. In these systems, the number of participating nodes can be very large, and the membership can dynamically change. Our goal is for each node to discover other "nearby" participating nodes in a completely decentralized manner, where each node probes only a small subset of other nodes in the system. This approach will lead to improved overall performance by matching client requests for services with participants in the peer-to-peer service system that are, on average, nearby in the network sense. Recent works in distributed peer-to-peer systems, such as Chord, CAN, Tapestry and Pastry, provide efficient distributed lookup structures. In this paper, we investigate a rendezvous-based scheme for a node to discover other nearby participating nodes using a peer-to-peer lookup system such as Chord. Given a key, the Chord protocol maps the key onto a node. Our idea for network neighborhood discovery is for each host to compute a key that characterizes its network location on the Internet. We call such a key the location key, and the nodes that these location keys are mapped to the Rendezvous Points. To lookup other nearby participating nodes, a node seeking some service queries its corresponding rendezvous point using its location key. We focus on the issue of how to generate the location key in a distributed fashion such that nodes that are close to each other in the actual network will have similar location key values, and therefore be mapped to nearby locations on the Chord ring. In this paper, we examine the performance tradeoffs of such a rendezvous scheme using the Global Network Positioning (GNP) approach to generate the location keys. In GNP, each node measures its network distances to a few landmark nodes to derive its coordinates in a D-dimensional geometric space. We generate a host's Chord location key from its 1-dimensional GNP coordinate, and use coordinates from a higher dimensional space to refine the searching process for the closest node. We evaluate our scheme in the context of the nearest neighbor discovery problem. Using data from the Active Measurement Project of the National Laboratory for Applied Network Research (NLANR), we compare its performance with a random mapping scheme, where location keys are randomly generated. Using our coordinate-based rendezvous scheme, 66% of the nodes found their actual closest network neighbor by pinging only a small number of nodes.Singapore-MIT Alliance (SMA

    Service recommendation and selection in centralized and decentralized environments.

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    With the increasing use of web services in everyday tasks we are entering an era of Internet of Services (IoS). Service discovery and selection in both centralized and decentralized environments have become a critical issue in the area of web services, in particular when services having similar functionality but different Quality of Service (QoS). As a result, selecting a high quality service that best suits consumer requirements from a large list of functionally equivalent services is a challenging task. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase of service consumers and a consequent diversity in Quality of Service (QoS) available. Increases in both sides leads to a diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. Furthermore, it is challenging for customers to select suitable services from a large number of services that satisfy consumer functional requirements. Therefore, web service recommendation becomes an attractive solution to provide recommended services to consumers which can satisfy their requirements.In this thesis, first a service ranking and selection algorithm is proposed by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. With the initial list of available services the approach considers those services with a partial match of consumer requirements and ranks them based on the QoS parameters, this allows the consumer to select suitable service. In addition, providing weight value for QoS parameters might not be an easy and understandable task for consumers, as a result an automatic weight calculation method has been included for consumer requirements by utilizing distance correlation between QoS parameters. The second aspect of the work in the thesis is the process of QoS based web service recommendation. With an increasing number of web services having similar functionality, it is challenging for service consumers to find out suitable web services that meet their requirements. We propose a personalised service recommendation method using the LDA topic model, which extracts latent interests of consumers and latent topics of services in the form of probability distribution. In addition, the proposed method is able to improve the accuracy of prediction of QoS properties by considering the correlation between neighbouring services and return a list of recommended services that best satisfy consumer requirements. The third part of the thesis concerns providing service discovery and selection in a decentralized environment. Service discovery approaches are often supported by centralized repositories that could suffer from single point failure, performance bottleneck, and scalability issues in large scale systems. To address these issues, we propose a context-aware service discovery and selection approach in a decentralized peer-to-peer environment. In the approach homophily similarity was used for bootstrapping and distribution of nodes. The discovery process is based on the similarity of nodes and previous interaction and behaviour of the nodes, which will help the discovery process in a dynamic environment. Our approach is not only considering service discovery, but also the selection of suitable web service by taking into account the QoS properties of the web services. The major contribution of the thesis is providing a comprehensive QoS based service recommendation and selection in centralized and decentralized environments. With the proposed approach consumers will be able to select suitable service based on their requirements. Experimental results on real world service datasets showed that proposed approaches achieved better performance and efficiency in recommendation and selection process.N/

    Extending the LWS Data Environment: Distributed Data Processing and Analysis

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    The final stages of this work saw changes to the original framework, as well as the completion and integration of several data processing services. Initially, it was thought that a peer-to-peer architecture was necessary to make this work possible. The peer-to-peer architecture provided many benefits including the dynamic discovery of new services that would be continually added. A prototype example was built and while it showed promise, a major disadvantage was seen in that it was not easily integrated into the existing data environment. While the peer-to-peer system worked well for finding and accessing distributed data processing services, it was found that its use was limited by the difficulty in calling it from existing tools and services. After collaborations with members of the data community, it was determined that our data processing system was of high value and that a new interface should be pursued in order for the community to take full advantage of it. As such; the framework was modified from a peer-to-peer architecture to a more traditional web service approach. Following this change multiple data processing services were added. These services include such things as coordinate transformations and sub setting of data. Observatory (VHO), assisted with integrating the new architecture into the VHO. This allows anyone using the VHO to search for data, to then pass that data through our processing services prior to downloading it. As a second attempt at demonstrating the new system, a collaboration was established with the Collaborative Sun Earth Connector (CoSEC) group at Lockheed Martin. This group is working on a graphical user interface to the Virtual Observatories and data processing software. The intent is to provide a high-level easy-to-use graphical interface that will allow access to the existing Virtual Observatories and data processing services from one convenient application. Working with the CoSEC group we provided access to our data processing tools from within their software. This now allows the CoSEC community to take advantage of our services and also demonstrates another means of accessing our system

    Collaborative e-science architecture for Reaction Kinetics research community

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    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
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