Distributed Reasoning in a Peer-to-Peer Setting: Application to the Semantic Web

In a peer-to-peer inference system, each peer can reason locally but can also solicit some of its acquaintances, which are peers sharing part of its vocabulary. In this paper, we consider peer-to-peer inference systems in which the local theory of each peer is a set of propositional clauses defined upon a local vocabulary. An important characteristic of peer-to-peer inference systems is that the global theory (the union of all peer theories) is not known (as opposed to partition-based reasoning systems). The main contribution of this paper is to provide the first consequence finding algorithm in a peer-to-peer setting: DeCA. It is anytime and computes consequences gradually from the solicited peer to peers that are more and more distant. We exhibit a sufficient condition on the acquaintance graph of the peer-to-peer inference system for guaranteeing the completeness of this algorithm. Another important contribution is to apply this general distributed reasoning setting to the setting of the Semantic Web through the Somewhere semantic peer-to-peer data management system. The last contribution of this paper is to provide an experimental analysis of the scalability of the peer-to-peer infrastructure that we propose, on large networks of 1000 peers

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

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

Semantic Co-Browsing System Based on Contextual Synchronization on Peer-to-Peer Environment

In this paper, we focus on a personalized information retrieval system based on multi-agent platform. Especially, they are capable of sharing information between them, for supporting collaborations between people. Personalization module has to be exploited to be aware of the corresponding user's browsing contexts (e.g., purposes, intention, and goals) at the specific moment. We want to recommend as relevant information to the estimated user context as possible, by analyzing the interaction results (e.g., clickstreams or query results). Thereby, we propose a novel approach to self-organizing agent groups based on contextual synchronization. Synchronization is an important requirement for online collaborations among them. This synchronization method exploits contextual information extracted from a set of personal agents in the same group, for real-time information sharing. Through semantically tracking of the users' information searching behaviors, we model the temporal dynamics of personal and group context. More importantly, in a certain moment, the contextual outliers can be detected, so that the groups can be automatically organized again with the same context. The co-browsing system embedding our proposed method was shown 52.7 % and 11.5 % improvements of communication performance, compared to single browsing system and asynchronous collaborative browsing system, respectively

Intelligent query processing in P2P networks: semantic issues and routing algorithms

P2P networks have become a commonly used way of disseminating content on the Internet. In this context, constructing efficient and distributed P2P routing algorithms for complex environments that include a huge number of distributed nodes with different computing and network capabilities is a major challenge. In the last years, query routing algorithms have evolved by taking into account different features (provenance, nodes' history, topic similarity, etc.). Such features are usually stored in auxiliary data structures (tables, matrices, etc.), which provide an extra knowledge engineering layer on top of the network, resulting in an added semantic value for specifying algorithms for efficient query routing. This article examines the main existing algorithms for query routing in unstructured P2P networks in which semantic aspects play a major role. A general comparative analysis is included, associated with a taxonomy of P2P networks based on their degree of decentralization and the different approaches adopted to exploit the available semantic aspects.Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

Naming and discovery in networks : architecture and economics

In less than three decades, the Internet was transformed from a research network available to the academic community into an international communication infrastructure. Despite its tremendous success, there is a growing consensus in the research community that the Internet has architectural limitations that need to be addressed in a effort to design a future Internet. Among the main technical limitations are the lack of mobility support, and the lack of security and trust. The Internet, and particularly TCP/IP, identifies endpoints using a location/routing identifier, the IP address. Coupling the endpoint identifier to the location identifier hinders mobility and poorly identifies the actual endpoint. On the other hand, the lack of security has been attributed to limitations in both the network and the endpoint. Authentication for example is one of the main concerns in the architecture and is hard to implement partly due to lack of identity support. The general problem that this dissertation is concerned with is that of designing a future Internet. Towards this end, we focus on two specific sub-problems. The first problem is the lack of a framework for thinking about architectures and their design implications. It was obvious after surveying the literature that the majority of the architectural work remains idiosyncratic and descriptions of network architectures are mostly idiomatic. This has led to the overloading of architectural terms, and to the emergence of a large body of network architecture proposals with no clear understanding of their cross similarities, compatibility points, their unique properties, and architectural performance and soundness. On the other hand, the second problem concerns the limitations of traditional naming and discovery schemes in terms of service differentiation and economic incentives. One of the recurring themes in the community is the need to separate an entity\u27s identifier from its locator to enhance mobility and security. Separation of identifier and locator is a widely accepted design principle for a future Internet. Separation however requires a process to translate from the identifier to the locator when discovering a network path to some identified entity. We refer to this process as identifier-based discovery, or simply discovery, and we recognize two limitations that are inherent in the design of traditional discovery schemes. The first limitation is the homogeneity of the service where all entities are assumed to have the same discovery performance requirements. The second limitation is the inherent incentive mismatch as it relates to sharing the cost of discovery. This dissertation addresses both subproblems, the architectural framework as well as the naming and discovery limitations

An Overview of Search Strategies in Distributed Environments

[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

Ontology-based Search Algorithms over Large-Scale Unstructured Peer-to-Peer Networks

Peer-to-Peer(P2P) systems have emerged as a promising paradigm to structure large scale distributed systems. They provide a robust, scalable and decentralized way to share and publish data.The unstructured P2P systems have gained much popularity in recent years for their wide applicability and simplicity. However efficient resource discovery remains a fundamental challenge for unstructured P2P networks due to the lack of a network structure. To effectively harness the power of unstructured P2P systems, the challenges in distributed knowledge management and information search need to be overcome. Current attempts to solve the problems pertaining to knowledge management and search have focused on simple term based routing indices and keyword search queries. Many P2P resource discovery applications will require more complex query functionality, as users will publish semantically rich data and need efficiently content location algorithms that find target content at moderate cost. Therefore, effective knowledge and data management techniques and search tools for information retrieval are imperative and lasting. In my dissertation, I present a suite of protocols that assist in efficient content location and knowledge management in unstructured Peer-to-Peer overlays. The basis of these schemes is their ability to learn from past peer interactions and increasing their performance with time.My work aims to provide effective and bandwidth-efficient searching and data sharing in unstructured P2P environments. A suite of algorithms which provide peers in unstructured P2P overlays with the state necessary in order to efficiently locate, disseminate and replicate objects is presented. Also, Existing approaches to federated search are adapted and new methods are developed for semantic knowledge representation, resource selection, and knowledge evolution for efficient search in dynamic and distributed P2P network environments. Furthermore,autonomous and decentralized algorithms that reorganizes an unstructured network topology into a one with desired search-enhancing properties are proposed in a network evolution model to facilitate effective and efficient semantic search in dynamic environments

Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System

Resource Discovery (RD) is a key issue in Internet-based distributed sytems such as grid. RD is about locating an appropriate resource/service type that matches the user's application requirements. This is very important, as resource reservation and task scheduling are based on it. Unfortunately, RD in grid is very challenging as resources and users are distributed, resources are heterogeneous in their platforms, status of the resources is dynamic (resources can join or leave the system without any prior notice) and most recently the introduction of a new type of grid called intergrid (grid of grids) with the use of multi middlewares. Such situation requires an RD system that has rich interoperability, scalability, decentralization and dynamism features. However, existing grid RD systems have difficulties to attain these features. Not only that, they lack the review and evaluation studies, which may highlight the gap in achieving the required features. Therefore, this work discusses the problem associated with intergrid RD from two perspectives. First, reviewing and classifying the current grid RD systems in such a way that may be useful for discussing and comparing them. Second, propose a novel RD framework that has the aforementioned required RD features. In the former, we mainly focus on the studies that aim to achieve interoperability in the first place, which are known as RD systems that use semantic information (semantic technology). In particular, we classify such systems based on their qualitative use of the semantic information. We evaluate the classified studies based on their degree of accomplishment of interoperability and the other RD requirements, and draw the future research direction of this field. Meanwhile in the latter, we name the new framework as semantic-based scalable decentralized dynamic RD. The framework further contains two main components which are service description, and service registration and discovery models. The earlier consists of a set of ontologies and services. Ontologies are used as a data model for service description, whereas the services are to accomplish the description process. The service registration is also based on ontology, where nodes of the service (service providers) are classified to some classes according to the ontology concepts, which means each class represents a concept in the ontology. Each class has a head, which is elected among its own class I nodes/members. Head plays the role of a registry in its class and communicates with I the other heads of the classes in a peer to peer manner during the discovery process. We further introduce two intelligent agents to automate the discovery process which are Request Agent (RA) and Description Agent (DA). Eaclj. node is supposed to have both agents. DA describes the service capabilities based on the ontology, and RA I carries the service requests based on the ontology as well. We design a service search I algorithm for the RA that starts the service look up from the class of request origin first, then to the other classes. We finally evaluate the performance of our framework ~ith extensive simulation experiments, the result of which confirms the effectiveness of the proposed system in satisfying the required RD features (interoperability, scalability, decentralization and dynamism). In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-qased service search and selection algorithm. Vll