Browsing by Subject "Peer-to-Peer networks"

Now showing 1 - 3 of 3

Open Access
A connection management protocol for promoting cooperation in Peer-to-Peer networks
(Elsevier BV, 2008-02-05) Karakaya, M.; Körpeoǧlu, I.; Ulusoy, Özgür
The existence of a high degree of free riding in Peer-to-Peer (P2P) networks is an important threat that should be addressed while designing P2P protocols. In this paper we propose a connection-based solution that will help to reduce the free riding effects on a P2P network and discourage free riding. Our solution includes a novel P2P connection type and an adaptive connection management protocol that dynamically establishes and adapts a P2P network topology considering the contributions of peers. The aim of the protocol is to bring contributing peers closer to each other on the adapted topology and to push the free riders away from the contributors. In this way contribution is promoted and free riding is discouraged. Unlike some other proposals against free riding, our solution does not require any permanent identification of peers or a security infrastructure for maintaining a global reputation system. It is shown through simulation experiments that there is a significant improvement in performance for contributing peers in a network that applies our protocol. © 2007 Elsevier B.V. All rights reserved.
Open Access
Counteracting free riding in Peer-to-Peer networks
(Elsevier BV, 2008-03) Karakaya, M.; Körpeoǧlu, I.; Ulusoy, O.
The existence of a high degree of free riding is a serious threat to Peer-to-Peer (P2P) networks. In this paper, we propose a distributed framework to reduce the adverse effects of free riding on P2P networks. Our solution primarily focuses on locating free riders and taking actions against them. We propose a framework in which each peer monitors its neighbors, decides if they are free riders, and takes appropriate actions. Unlike other proposals against free riding, our framework does not require any permanent identification of peers or security infrastructures for maintaining a global reputation system. Our simulation results show that the framework can reduce the effects of free riding and can therefore increase the performance of a P2P network. © 2007 Elsevier B.V. All rights reserved.
Open Access
Counteracting free riding in pure peer-to-peer networks
(2008) Karakaya, K. Murat
The peer-to-peer (P2P) network paradigm has attracted a significant amount of interest as a popular and successful alternative to traditional client-server model for resource sharing and content distribution. However, researchers have observed the existence of high degrees of free riding in P2P networks which poses a serious threat to effectiveness and efficient operation of these networks, and hence to their future. Therefore, eliminating or reducing the impact of free riding on P2P networks has become an important issue to investigate and a considerable amount of research has been conducted on it. In this thesis, we propose two novel solutions to reduce the adverse effects of free riding on P2P networks and to motivate peers to contribute to P2P networks. These solutions are also intended to lead to performance gains for contributing peers and to penalize free riders. As the first solution, we propose a distributed and localized scheme, called Detect and Punish Method (DPM), which depends on detection and punishment of free riders. Our second solution to the free riding problem is a connection-time protocol, called P2P Connection Management Protocol (PCMP), which is based on controlling and managing link establishments among peers according to their contributions. To evaluate the proposed solutions and compare them with other alternatives, we developed a new P2P network simulator and conducted extensive simulation experiments. Our simulation results show that employing our solutions in a P2P network considerably reduces the adverse effects of free riding and improves the overall performance of the network. Furthermore, we observed that P2P networks utilizing the proposed solutions become more robust and scalable.