Agent-Controlled Sharing of Distributed Resources in User Networks

In this chapter, we evaluate the feasibility of intelligent and distributed control of shared resources in user-managed networks. The user-managed network paradigm has become possible with the advent of broadband wireless networking technologies such as IEEE 802.11. In those networks, node cooperation can optimize the usage of shared external accesses to the Internet (set of links between the user network and the Internet). First, we provide an extensive introduction and the state of the art in related concepts such as multi-agent systems, user networks, peer to peer file exchanges and game theory. Then we present an evaluation of different agent-oriented distributed control schema, based on the concept of credit limits, on ideal mesh networks subjected to uniform traffic. Each node in the mesh network chooses to behave as a cooperator or a defector. Cooperators may assist in file exchange, whereas defectors try to get advantage of network resources without providing help in return. Finally, we present a realistic model of user network traffic and topology, and evaluate a new advanced agent-based distributed control scheme. The simulation results presented here confirm that it is possible to improve resource sharing in user networks using agents which check that file exchange services offered to neighbor nodes do not surpass appropriate credit limits and which take decisions autonomously from local information. As an external validation of our work, we have observed that popular P2P protocols like eMule, Kazaa and BitTorrent have been evolving towards the same credit-oriented strategies discussed in this chapter. 2 E. Costa-Montenegro et al. Fig. 1. User network with shared Internet links

[1]  Hui Zhang,et al.  A case for taxation in peer-to-peer streaming broadcast , 2004, PINS '04.

[2]  Tuomas Sandholm,et al.  Distributed rational decision making , 1999 .

[3]  Juan C. Burguillo,et al.  Agent-Driven Resource Optimization in User Networks: A Game Theoretical Approach , 2004, ACRI.

[4]  Alon Y. Halevy,et al.  Piazza: data management infrastructure for semantic web applications , 2003, WWW '03.

[5]  J.-Y. Le Boudec,et al.  Toward self-organized mobile ad hoc networks: the terminodes project , 2001, IEEE Commun. Mag..

[6]  Ariel Orda,et al.  Architecting noncooperative networks , 1995, Eighteenth Convention of Electrical and Electronics Engineers in Israel.

[7]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[8]  G. Weikum.  Querying the Internet with PIER , 2005 .

[9]  Scott Shenker,et al.  Internet indirection infrastructure , 2004, IEEE/ACM Transactions on Networking.

[10]  C. Badcock,et al.  Simulating Societies: The Computer Simulation of Social Phenomena , 1995 .

[11]  Ariel Orda,et al.  Competitive routing in multiuser communication networks , 1993, TNET.

[12]  Miguel Castro,et al.  Security for Structured Peer-to-peer Overlay Networks , 2004 .

[13]  S. Jarvenpaa,et al.  Are Contributions to P2P Technical Forums Private or Public Goods? – An Empirical Investigation , 2003 .

[14]  Eytan Adar,et al.  Free Riding on Gnutella , 2000, First Monday.

[15]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

[16]  Barbara Messing,et al.  An Introduction to MultiAgent Systems , 2002, Künstliche Intell..

[17]  Danny Bickson,et al.  The eMule Protocol Specification , 2005 .

[18]  Ion Stoica,et al.  Robust incentive techniques for peer-to-peer networks , 2004, EC '04.

[19]  Demetri Terzopoulos,et al.  Artificial life for computer graphics , 1999, CACM.

[20]  Nicholas R. Jennings,et al.  On Agent-Mediated Electronic Commerce , 2003, IEEE Trans. Knowl. Data Eng..

[21]  Alberto RibesAbstract,et al.  Multi agent systems , 2019, Proceedings of the 2005 International Conference on Active Media Technology, 2005. (AMT 2005)..

[22]  Pattie Maes,et al.  Agents that reduce work and information overload , 1994, CACM.

[23]  Scott Shenker,et al.  Complex Queries in Dht-based Peer-to-peer Networks , 2002 .

[24]  David P. Anderson,et al.  A new major SETI project based on Project Serendip data and 100 , 1997 .

[25]  Michael Wooldridge,et al.  Intelligent agents: theory and practice The Knowledge Engineering Review , 1995 .

[26]  Fausto Giunchiglia,et al.  Data Management for Peer-to-Peer Computing : A Vision , 2002, WebDB.

[27]  Diomidis Spinellis,et al.  Security applications of peer-to-peer networks , 2004, Comput. Networks.

[28]  Pattie Maes,et al.  Agents that reduce work and information overload , 1994, CACM.

[29]  Diomidis Spinellis,et al.  A survey of peer-to-peer content distribution technologies , 2004, CSUR.

[30]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[31]  Stergios I. Roumeliotis,et al.  Distributed Multi-Robot Localization , 2000, DARS.

[32]  Angelos D. Keromytis,et al.  SOS: secure overlay services , 2002, SIGCOMM '02.

[33]  Qi Zhang,et al.  Indra: a peer-to-peer approach to network intrusion detection and prevention , 2003, WET ICE 2003. Proceedings. Twelfth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2003..

[34]  Tore Risch,et al.  EDUTELLA: a P2P networking infrastructure based on RDF , 2002, WWW.

[35]  F. J. Gonzalez Castano,et al.  Agent-Controlled Sharing of Distributed Resources in User Networks , 2007 .

[36]  Francisco Javier González-Castaño,et al.  Distributed and centralized algorithms for large-scale IEEE 802.11b infrastructure planning , 2004, Proceedings. ISCC 2004. Ninth International Symposium on Computers And Communications (IEEE Cat. No.04TH8769).

[37]  Heinz Mühlenbein,et al.  Coordination of Decisions in a Spatial Agent Model , 2001, ArXiv.

[38]  Kevin Leyton-Brown,et al.  Incentives for sharing in peer-to-peer networks , 2001, EC '01.

[39]  Heterogeneity-Aware Peer-to-Peer Multicast , 2002 .

[40]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[41]  G. Hardin,et al.  The Tragedy of the Commons , 1968, Green Planet Blues.

[42]  Karthik Tamilmani,et al.  SWIFT: A System With Incentives For Trading , 2004 .

[43]  Ana Mas.  Agentes software y sistemas multiagente : conceptos, arquitecturas y aplicaciones , 2005 .

[44]  Miguel Castro,et al.  Scribe: a large-scale and decentralized application-level multicast infrastructure , 2002, IEEE J. Sel. Areas Commun..

[45]  F. Box,et al.  A heuristic technique for assigning frequencies to mobile radio nets , 1978, IEEE Transactions on Vehicular Technology.

[46]  Robert Hoffmann,et al.  Twenty Years on: The Evolution of Cooperation Revisited , 2000, J. Artif. Soc. Soc. Simul..

[47]  Moshe Tennenholtz,et al.  Adaptive Load Balancing: A Study in Multi-Agent Learning , 1994, J. Artif. Intell. Res..

[48]  Juan C. Burguillo,et al.  A Combined Global & Local Search (CGLS) Approach to Global Optimization , 2006, J. Glob. Optim..

[49]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[50]  Walter Willinger,et al.  On the Self-Similar Nature of Ethernet Traffic ( extended version ) , 1995 .