Fair resource allocation in peer-to-peer networks (extended version)

Eger, Kolja; Killat, Ulrich

doi:10.1016/j.comcom.2007.05.039

Cited by 22 publications

(17 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In reality, it is hard to measure both c j and µ j accurately, and hence it is difficult to pre-allocate F j . Even if we were able to allocate each F j precisely proportional to µ j c j , the possible temporal correlation of fluctuation in the service capacity of each source peer will result in a strict inequality in (11) and so does the heterogeneity in the average capacity with different source peers for the inequality in (14). The naive "connect-and-wait" strategy for each of the parallel connections is thus unlikely to achieve an equality in (8), and therefore we need to consider different algorithms to achieve such equality if at all possible.…”

Section: Achievable Minimum Average Download Timementioning

confidence: 99%

See 1 more Smart Citation

On the Performance of Content Delivery under Competition in a Stochastic Unstructured Peer-to-Peer Network

Chiu¹,

Eun

2010

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

Abstract-Peer-to-peer (P2P) network is widely used for transferring large files nowadays. Measurement results show that most downloading peers are patient as the average download session is usually very long. It is sometimes even longer than downloading from a dedicated server using a modem. Existing results in the literature indicate that the stochastic fluctuation and the heterogeneity in the service capacity of each peer are two of the major reasons that make the average download time far longer than expected. In those studies, it has been often assumed that there is only one downloading peer in the network, ignoring the interaction and competition among peers. In this paper, we investigate the impact of the interaction and competition among peers on downloading performance under stochastic, heterogeneous, unstructured P2P settings, thereby greatly extending the existing results on stochastic P2P networks made only under a single downloading peer in the network. To analyze the average download time in a P2P network with multiple competing downloading peers, we first introduce the notion of system utilization tailored to a P2P network. We investigate the relationship between the average download time, system utilization and the level of competition among downloading peers in a stochastic P2P network. We then derive an achievable lower bound on the average download time and propose algorithms to give the peers the minimum average download time. Our result can much improve the download performance compared to earlier results in the literature. The performance of the different algorithms is compared under NS-2 simulations. Our results also provide theoretical explanation to the inconsistency of performance improvement by using parallel connections (parallel connections sometimes do not outperform a single connection) observed in some measurement studies.

show abstract

Section: Achievable Minimum Average Download Timementioning

confidence: 99%

“…Accordingly, many incentive algorithms have been developed so as to encourage peers to contribute to the network [8], [9], [10], [11], [12], [13]. However, even if all peers in the network are altruistic, we are still far away from enjoying the performance predicted by [5], [14].…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Content Delivery under Competition in a Stochastic Unstructured Peer-to-Peer Network

Chiu¹,

Eun

2010

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

show abstract

“…For example, Eger and Killat (2007) applied resource pricing into P2P networks to ensure fair allocation of resources based on the congestion pricing principle known from IP networks. Zghaibeh and Harmantzis (2008) proposed a lottery-based pricing mechanism to enhance the sharing level in P2P networks and help increase the number of objects disseminated.…”

Section: Related Workmentioning

confidence: 99%

“…Generally, pricing mechanisms mainly concentrate on motivating users to share resource with others and not declining other users' requests by relating their behaviors to a financial utility or mechanism. Several interesting pricing approaches have been presented for P2Ps in recent years, for example, the lottery-based scheme (Zghaibeh and Harmantzis, 2008), the Lagrangian multiplier method (Eger and Killat, 2007;Koutsopoulos and Iosifidis, 2010;Neely and Golubchik, 2011), the microeconomics-based approach (Kumar et al, 2011;Analoui and Rezvani, 2011), auction-based mechanisms Zuo and Zhang, 2013), and game-based ones (Park and Van Der Schaar, 2010;Nakano and Okaie, 2010;Okaie and Nakano, 2012;Kang and Wu, 2015;Lin et al, 2015). In this paper we propose a pricing scheme to achieve reasonable resource allocation in P2P file-sharing networks.…”

mentioning

confidence: 99%

A scheme of resource allocation and stability for peer–to–peer file–sharing networks

Sun

Chengguo

et al. 2016

International Journal of Applied Mathematics and Computer Science

View full text Add to dashboard Cite

Peer-to-peer (P2P) networks offer a cost-effective and easily deployable framework for sharing content. However, P2P file-sharing applications face a fundamental problem of unfairness. Pricing is regarded as an effective way to provide incentives to peers to cooperate. In this paper we propose a pricing scheme to achieve reasonable resource allocation in P2P file-sharing networks, and give an interpretation for the utility maximization problem and its sub-problems from an economic point of view. We also deduce the exact expression of optimal resource allocation for each peer, and confirm it with both simulation and optimization software. In order to realize the optimum in a decentralized architecture, we present a novel price-based algorithm and discuss its stability based on Lyapunov stability theory. Simulation results confirm that the proposed algorithm can attain an optimum within reasonable convergence times.

show abstract

“…[6] proposes a service differentiated peer selection algorithm that gives peers with higher contributions more flexibility in choosing neighbors, thus obtain better viewing quality. Some measurement and theoretical studies on P2P incentives can be found in [5,19]. We use taxation mechanisms to strike the right balance between social welfare and individual welfare.…”

Section: Related Workmentioning

confidence: 99%

Mesh-based peer-to-peer layered video streaming with taxation

Guo

Liu

2010

Proceedings of the 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video

View full text Add to dashboard Cite

Recent advance in scalable video coding (SVC) makes it possible for users to receive the same video with different qualities. To adopt SVC in P2P streaming, two key design questions need to be answered: 1) layer subscription: how many layers each peer should receive? 2) layer scheduling: how to deliver to peers the layers they subscribed? From the system point of view, the most efficient solution is to maximize the aggregate video quality on all peers, i.e., the social welfare. From individual peer point of view, the solution should be fair. Fairness in P2P streaming should additionally take into account peer contributions to make the solution incentive-compatible. In this paper, we show that taxation mechanisms can be devised to strike the right balance between social welfare and individual peers' welfare. We develop practical taxationbased P2P layered streaming designs, including layer subscription strategy, chunk scheduling policy, and mesh topology adaptation. Extensive trace-driven simulations show that the proposed designs can effectively drive layered P2P streaming systems to converge to the desired operating points in a distributed fashion.

show abstract

Fair resource allocation in peer-to-peer networks (extended version)

Cited by 22 publications

References 10 publications

On the Performance of Content Delivery under Competition in a Stochastic Unstructured Peer-to-Peer Network

On the Performance of Content Delivery under Competition in a Stochastic Unstructured Peer-to-Peer Network

A scheme of resource allocation and stability for peer–to–peer file–sharing networks

Mesh-based peer-to-peer layered video streaming with taxation

Contact Info

Product

Resources

About