Incentives for sharing in peer-to-peer networks
Proceedings of the 3rd ACM conference on Electronic Commerce
Search and replication in unstructured peer-to-peer networks
ICS '02 Proceedings of the 16th international conference on Supercomputing
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Routing Indices For Peer-to-Peer Systems
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Exchange-Based Incentive Mechanisms for Peer-to-Peer File Sharing
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
P2P contracts: a framework for resource and service exchange
Future Generation Computer Systems - Special issue: P2P computing and interaction with grids
Free Riding on Gnutella Revisited: The Bell Tolls?
IEEE Distributed Systems Online
Taxonomy of trust: categorizing P2P reputation systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing
IEEE Transactions on Parallel and Distributed Systems
Counteracting free riding in Peer-to-Peer networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
An empirical study of free-riding behavior in the maze p2p file-sharing system
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
Cooperating with free riders in unstructured P2P networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
| Hi-index | 0.00 |
Free riders in Peer-to-peer (P2P) networks are the nodes only consume services but provide little or nothing. They seriously degrade the fault-tolerance and scalability of the P2P networks. A Cluster-Based Incentive Mechanism (CBIM) is proposed in this paper to prevent free riding problem in P2P networks regardless of their topologies and service diversity. Nodes with asymmetric interests are organized in clusters that consist of service exchange rings. A node in a ring can receive a service from its predecessor by providing a requested service to its successor. Free riders can not complete their requested services since a ring will collapse once free riding is detected. We firstly identify five design requirements, namely, adaptability, service diversity, reward and penalty, altruism and performance. Second, we describe the cluster formation process and a graph theory based ring identification algorithm. Finally, we describe our coarse-grained probability-based free riding prevention algorithm. Through a set of simulations, we find that the CBIM is feasible and outperforms other incentive mechanisms.