Building Robust Distributed Infrastructure Networks

Many competing designs for Distributed Hash Tables exist exploring multiple models of addressing, routing and network maintenance. Designing a general theoretical model and implementation of a Distributed Hash Table allows exploration of the possible properties of Distributed Hash Tables. We will propose a generalized model of DHT behavior, centered on utilizing Delaunay triangulation in a given metric space to maintain the networks topology. We will show that utilizing this model we can produce network topologies that approximate existing DHT methods and provide a starting point for further exploration. We will use our generalized model of DHT construction to design and implement more efficient Distributed Hash Table protocols, and discuss the qualities of potential successors to existing DHT technologies

New IR & Ranking Algorithm for Top-K Keyword Search on Relational Databases ‘Smart Search’

Database management systems are as old as computers, and the continuous research and development in databases is huge and an interest of many database venders and researchers, as many researchers work in solving and developing new modules and frameworks for more efficient and effective information retrieval based on free form search by users with no knowledge of the structure of the database. Our work as an extension to previous works, introduces new algorithms and components to existing databases to enable the user to search for keywords with high performance and effective top-k results. Work intervention aims at introducing new table structure for indexing of keywords, which would help algorithms to understand the semantics of keywords and generate only the correct CN‟s (Candidate Networks) for fast retrieval of information with ranking of results according to user‟s history, semantics of keywords, distance between keywords and match of keywords. In which a three modules where developed for this purpose. We implemented our three proposed modules and created the necessary tables, with the development of a web search interface called „Smart Search‟ to test our work with different users. The interface records all user interaction with our „Smart Search‟ for analyses, as the analyses of results shows improvements in performance and effective results returned to the user. We conducted hundreds of randomly generated search terms with different sizes and multiple users; all results recorded and analyzed by the system were based on different factors and parameters. We also compared our results with previous work done by other researchers on the DBLP database which we used in our research. Our final result analysis shows the importance of introducing new components to the database for top-k keywords search and the performance of our proposed system with high effective results.نظم إدارة قواعد البيانات قديمة مثل أجيزة الكمبيوتر، و البحث والتطوير المستمر في قواعد بيانات ضخم و ىنالك اىتمام من العديد من مطوري قواعد البيانات والباحثين، كما يعمل العديد من الباحثين في حل وتطوير وحدات جديدة و أطر السترجاع المعمومات بطرق أكثر كفاءة وفعالية عمى أساس نموذج البحث الغير مقيد من قبل المستخدمين الذين ليس لدييم معرفة في بنية قاعدة البيانات. ويأتي عممنا امتدادا لألعمال السابقة، ويدخل الخوارزميات و مكونات جديدة لقواعد البيانات الموجودة لتمكين المستخدم من البحث عن الكممات المفتاحية )search Keyword )مع األداء العالي و نتائج فعالة في الحصول عمى أعمى ترتيب لمبيانات .)Top-K( وييدف ىذا العمل إلى تقديم بنية جديدة لفيرسة الكممات المفتاحية )Table Keywords Index ،)والتي من شأنيا أن تساعد الخوارزميات المقدمة في ىذا البحث لفيم معاني الكممات المفتاحية المدخمة من قبل المستخدم وتوليد فقط الشبكات المرشحة (s’CN (الصحيحة السترجاع سريع لممعمومات مع ترتيب النتائج وفقا ألوزان مختمفة مثل تاريخ البحث لممستخدم، ترتيب الكمات المفتاحية في النتائج والبعد بين الكممات المفتاحية في النتائج بالنسبة لما قام المستخدم بأدخالو. قمنا بأقتراح ثالث مكونات جديدة )Modules )وتنفيذىا من خالل ىذه االطروحة، مع تطوير واجية البحث عمى شبكة اإلنترنت تسمى "البحث الذكي" الختبار عممنا مع المستخدمين. وتتضمن واجية البحث مكونات تسجل تفاعل المستخدمين وتجميع تمك التفاعالت لمتحميل والمقارنة، وتحميالت النتائج تظير تحسينات في أداء استرجاع البينات و النتائج ذات صمة ودقة أعمى. أجرينا مئات عمميات البحث بأستخدام جمل بحث تم أنشائيا بشكل عشوائي من مختمف األحجام، باالضافة الى االستعانة بعدد من المستخدمين ليذه الغاية. واستندت جميع النتائج المسجمة وتحميميا بواسطة واجية البحث عمى عوامل و معايير مختمفة .وقمنا بالنياية بعمل مقارنة لنتائجنا مع االعمال السابقة التي قام بيا باحثون آخرون عمى نفس قاعدة البيانات (DBLP (الشييرة التي استخدمناىا في أطروحتنا. وتظير نتائجنا النيائية مدى أىمية أدخال بنية جديدة لفيرسة الكممات المفتاحية الى قواعد البيانات العالئقية، وبناء خوارزميات استنادا الى تمك الفيرسة لمبحث بأستخدام كممات مفتاحية فقط والحصول عمى نتائج أفضل ودقة أعمى، أضافة الى التحسن في وقت البحث

Doctor of Philosophy

dissertationWe develop a novel framework for friend-to-friend (f2f) distributed services (F3DS) by which applications can easily offer peer-to-peer (p2p) services among social peers with resource sharing governed by approximated levels of social altruism. Our frame- work differs significantly from typical p2p collaboration in that it provides a founda- tion for distributed applications to cooperate based on pre-existing trust and altruism among social peers. With the goal of facilitating the approximation of relative levels of altruism among social peers within F3DS, we introduce a new metric: SocialDistance. SocialDistance is a synthetic metric that combines direct levels of altruism between peers with an altruism decay for each hop to approximate indirect levels of altruism. The resulting multihop altruism levels are used by F3DS applications to proportion and prioritize the sharing of resources with other social peers. We use SocialDistance to implement a novel flash file/patch distribution method, SocialSwarm. SocialSwarm uses the SocialDistance metric as part of its resource allocation to overcome the neces- sity of (and inefficiency created by) resource bartering among friends participating in a BitTorrent swarm. We find that SocialSwarm achieves an average file download time reduction of 25% to 35% in comparison with standard BitTorrent under a variety of configurations and conditions, including file sizes, maximum SocialDistance, as well as leech and seed counts. The most socially connected peers yield up to a 47% decrease in download completion time in comparison with average nonsocial BitTorrent swarms. We also use the F3DS framework to implement novel malware detection application- F3DS Antivirus (F3AV)-and evaluate it on the Amazon cloud. We show that with f2f sharing of resources, F3AV achieves a 65% increase in the detection rate of 0- to 1-day-old malware among social peers as compared to the average of individual scanners. Furthermore, we show that F3AV provides the greatest diversity of mal- ware scanners (and thus malware protection) to social hubs-those nodes that are positioned to provide strategic defense against socially aware malware

Scalability of findability: decentralized search and retrieval in large information networks

Amid the rapid growth of information today is the increasing challenge for people to survive and navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web challenge information retrieval in these environments. Collection of information in advance and centralization of IR operations are hardly possible because systems are dynamic and information is distributed. While monolithic search systems continue to struggle with scalability problems of today, the future of search likely requires a decentralized architecture where many information systems can participate. As individual systems interconnect to form a global structure, finding relevant information in distributed environments transforms into a problem concerning not only information retrieval but also complex networks. Understanding network connectivity will provide guidance on how decentralized search and retrieval methods can function in these information spaces. The dissertation studies one aspect of scalability challenges facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and investigates a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit. Experiments involving large scale benchmark collections provide evidence on the Clustering Paradox in the IR context. In an increasingly large, distributed environment, decentralized searches for relevant information can continue to function well only when systems interconnect in certain ways. Relying on partial indexes of distributed systems, some level of network clustering enables very efficient and effective discovery of relevant information in large scale networks. Increasing or reducing network clustering degrades search performances. Given this specific level of network clustering, search time is well explained by a poly-logarithmic relation to network size, indicating a high scalability potential for searching in a continuously growing information space

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

Diseño centrado en calidad para la difusión Peer-to-Peer de video en vivo

El uso de redes Peer-to-Peer (P2P) es una forma escalable para ofrecer servicios de video sobre Internet. Este documento hace foco en la definición, desarrollo y evaluación de una arquitectura P2P para distribuir video en vivo. El diseño global de la red es guiado por la calidad de experiencia (Quality of Experience - QoE), cuyo principal componente en este caso es la calidad del video percibida por los usuarios finales, en lugar del tradicional diseño basado en la calidad de servicio (Quality of Service - QoE) de la mayoría de los sistemas. Para medir la calidad percibida del video, en tiempo real y automáticamente, extendimos la recientemente propuesta metodología Pseudo-Subjective Quality Assessment (PSQA). Dos grandes líneas de investigación son desarrolladas. Primero, proponemos una técnica de distribución de video desde múltiples fuentes con las características de poder ser optimizada para maximizar la calidad percibida en contextos de muchas fallas y de poseer muy baja señalización (a diferencia de los sistemas existentes). Desarrollamos una metodología, basada en PSQA, que nos permite un control fino sobre la forma en que la señal de video es dividida en partes y la cantidad de redundancia agregada, como una función de la dinámica de los usuarios de la red. De esta forma es posible mejorar la robustez del sistema tanto como sea deseado, contemplando el límite de capacidad en la comunicación. En segundo lugar, presentamos un mecanismo estructurado para controlar la topología de la red. La selección de que usuarios servirán a que otros es importante para la robustez de la red, especialmente cuando los usuarios son heterogéneos en sus capacidades y en sus tiempos de conexión.Nuestro diseño maximiza la calidad global esperada (evaluada usando PSQA), seleccionado una topología que mejora la robustez del sistema. Además estudiamos como extender la red con dos servicios complementarios: el video bajo demanda (Video on Demand - VoD) y el servicio MyTV. El desafío en estos servicios es como realizar búsquedas eficientes sobre la librería de videos, dado al alto dinamismo del contenido. Presentamos una estrategia de "caching" para las búsquedas en estos servicios, que maximiza el número total de respuestas correctas a las consultas, considerando una dinámica particular en los contenidos y restricciones de ancho de banda. Nuestro diseño global considera escenarios reales, donde los casos de prueba y los parámetros de configuración surgen de datos reales de un servicio de referencia en producción. Nuestro prototipo es completamente funcional, de uso gratuito, y basado en tecnologías bien probadas de código abierto

Routing in anonymous networks as a means to prevent traffic analysis

Traditionally, traffic analysis is something that has been used to measure and keep track of a network's situation regarding network congestion, networking hardware failures, etc. However, largely due to commercial interests such as targeted advertisement, traffic analysis techniques can also be used to identify and track a single user's movements within the Internet. To counteract this perceived breach of privacy and anonymity, several counters have been developed over time, e.g. proxies used to obfuscate the true source of traffic, making it harder for others to pinpoint your location. Another approach has been the development of so called anonymous overlay networks, application-level virtual networks running on top of the physical IP network. The core concept is that by the way of encryption and obfuscation of traffic patterns, the users of such anonymous networks will gain anonymity and protection against traffic analysis techniques. In this master's thesis we will be taking a look at how message forwarding or packet routing in IP networks functions and how this is exploited in different analysis techniques to single out a visitor to a website or just someone with a message being forwarded through a network device used for traffic analysis. After that we will discuss some examples of anonymous overlay networks and see how well they protect their users from traffic analysis, and how do their respective models hold up against traffic analysis attacks from a malicious entity. Finally, we will present a case study about Tor network's popularity by running a Tor relay node and gathering information on how much data the relay transmits and from where does the traffic originate. CCS-concepts: - Security and privacy ~ Privacy protections - Networks ~ Overlay and other logical network structures - Information systems ~ Traffic analysi

Dynamic data placement and discovery in wide-area networks

The workloads of online services and applications such as social networks, sensor data platforms and web search engines have become increasingly global and dynamic, setting new challenges to providing users with low latency access to data. To achieve this, these services typically leverage a multi-site wide-area networked infrastructure. Data access latency in such an infrastructure depends on the network paths between users and data, which is determined by the data placement and discovery strategies. Current strategies are static, which offer low latencies upon deployment but worse performance under a dynamic workload. We propose dynamic data placement and discovery strategies for wide-area networked infrastructures, which adapt to the data access workload. We achieve this with data activity correlation (DAC), an application-agnostic approach for determining the correlations between data items based on access pattern similarities. By dynamically clustering data according to DAC, network traffic in clusters is kept local. We utilise DAC as a key component in reducing access latencies for two application scenarios, emphasising different aspects of the problem: The first scenario assumes the fixed placement of data at sites, and thus focusses on data discovery. This is the case for a global sensor discovery platform, which aims to provide low latency discovery of sensor metadata. We present a self-organising hierarchical infrastructure consisting of multiple DAC clusters, maintained with an online and distributed split-and-merge algorithm. This reduces the number of sites visited, and thus latency, during discovery for a variety of workloads. The second scenario focusses on data placement. This is the case for global online services that leverage a multi-data centre deployment to provide users with low latency access to data. We present a geo-dynamic partitioning middleware, which maintains DAC clusters with an online elastic partition algorithm. It supports the geo-aware placement of partitions across data centres according to the workload. This provides globally distributed users with low latency access to data for static and dynamic workloads.Open Acces

BCBU + handbook : a guide to establish virtual cross-border campus for BCBU network

Vertaisarviointia edeltävä käsikirjoitu

Private and censorship-resistant communication over public networks

Society’s increasing reliance on digital communication networks is creating unprecedented opportunities for wholesale surveillance and censorship. This thesis investigates the use of public networks such as the Internet to build robust, private communication systems that can resist monitoring and attacks by powerful adversaries such as national governments. We sketch the design of a censorship-resistant communication system based on peer-to-peer Internet overlays in which the participants only communicate directly with people they know and trust. This ‘friend-to-friend’ approach protects the participants’ privacy, but it also presents two significant challenges. The first is that, as with any peer-to-peer overlay, the users of the system must collectively provide the resources necessary for its operation; some users might prefer to use the system without contributing resources equal to those they consume, and if many users do so, the system may not be able to survive. To address this challenge we present a new game theoretic model of the problem of encouraging cooperation between selfish actors under conditions of scarcity, and develop a strategy for the game that provides rational incentives for cooperation under a wide range of conditions. The second challenge is that the structure of a friend-to-friend overlay may reveal the users’ social relationships to an adversary monitoring the underlying network. To conceal their sensitive relationships from the adversary, the users must be able to communicate indirectly across the overlay in a way that resists monitoring and attacks by other participants. We address this second challenge by developing two new routing protocols that robustly deliver messages across networks with unknown topologies, without revealing the identities of the communication endpoints to intermediate nodes or vice versa. The protocols make use of a novel unforgeable acknowledgement mechanism that proves that a message has been delivered without identifying the source or destination of the message or the path by which it was delivered. One of the routing protocols is shown to be robust to attacks by malicious participants, while the other provides rational incentives for selfish participants to cooperate in forwarding messages