Information Technology Reference
In-Depth Information
we have modelled user behaviour and defined the coalition formation model in order
to perform simulations, using the simulator presented in [16]. The paper also includes
some analysis of simulations.
Our approach allows any peer with idle bandwidth to participate in a coalition, up-
loading files for other peers in exchange for utility, and consequently greater down-
load bandwidth; And in addition, it provides, using the “core”, a fair utility to the
peers forming the coalition in relation to the bandwidth they supply. To achieve this,
a
Responsiveness Bonus
that reflects the peer's overall contribution to the system is
defined, and the game theory utility concept is used to calculate it.
The simulation results have shown that in relation to downloaded bytes, the coali-
tion mechanism prevents free-riders from obtaining more bytes as simulation time in-
creases. In addition, it reacts to the inclusion of adaptive users increasing by 20% the
total amount of downloaded bytes, so they benefit the system. In relation to download
time, coalitions are capable of getting the best average download times and stopping
free riders at the same time. Finally, we the analysis of Work Progress have shown that
equilibrium between offer and demand is better when using our mechanism. This helps
to keep the systems healthy.
Finally, we are working on the simulation of other approaches in order to be able to
compare our results with existing proposals. And we plan to generalise the proposed
coalition formation algorithm in order to include Quality of Service information. Our
idea is to form coalitions in such a way that they are able to provide or guarantee QoS
in different aspects depending on the service or application, i.e. real time constraints or
fault tolerance.
References
1. Belmonte, M.V., Conejo, R., Perez-de-la-Cruz, J.L., Triguero, F.: Coalitions among Intelli-
gent Agents: A Tractable Case. Computational Intelligence. An International Journal 22(1),
52-68 (2006)
2. Karakaya, M., Korpooglu, I., Ulusoy, O.: Free Riding in Peer-to-Peer Networks. In: IEEE
Internet Computing, pp. 92-98. IEEE Press (2009)
3. Golle, P., Leyton-Brown, K., Mironov, I., Lillibridge, M.: FIncentives for Sharing in Peer-to-
Peer Networks. In: ACM Conference on Electronic Commerce. ACM Press (2001)
4. Kahan, J. Rapaport, A.: Theories of Coalition Formation. Lawrence Erlbaum Associates Pub-
lishers (1984)
5. Ramaswamy, L., Liu, L.: A New Challenge to Peer-to-Peer File Sharing Systems. In: 6th
Hawaii International Conference on System Sciences (2003)
6. Sariou, S., Gummadi, P.K., Gribble, S.D.: A measurement study of peer-to-peer file sharing
systems. In: Proceedings of Multimedia Computing and Networking (2002)
7. Shneidman, J., Parkes, D.: Rationality and Self-Interest in Peer to Peer Networks. In:
Kaashoek, M.F., Stoica, I. (eds.) IPTPS 2003. LNCS, vol. 2735, pp. 139-148. Springer, Hei-
delberg (2003)
8. Karakaya, M., Korpooglu, I., Ulusoy, O.: Countrecting free riding in Peer-to-Peer networks.
Computer Networks 52, 675-694 (2008)
9. Bertsekas, D. Gallager, R.: Data Networks. Prentice-Hall (1992)
10. Ma, R.T.B., Lee, S.C.M., Luis, J.C.S., Yau, D.K.Y.: Ncentive and Service Differentiation in
P2P Networks: A Game Theoretic Approach. IEEE/ACM Transactions on Networking 14(5),
978-991 (2006)
