Mastering selfishness and heterogeneity in mobile P2P content distribution networks with multiple source download in cellular networks

The performance of Peer-to-Peer (P2P) content distribution networks depends highly on the coordination of the peers. This is especially true for cellular networks with mobile and often selfish users, as the resource constraints on accessible bandwidth and battery power are even more limitating in this context. Thus, it is a major challenge to identify mobile network specific problems and to develop sophisticated cooperation strategies to overcome these difficulties. Cooperation strategies, which are able to cope these problems, are the foundation for efficient mobile file exchange. The detailed performance of the strategies are determined by the peer capabilities and the peer behavior, such as the number of parallel upload connections, the selfishness, or the altruistic re-distribution of data. The purpose of this work is to evaluate and investigate different cooperation strategies which are based on multiple source download and select the best one for mobile scenarios with even leeching peers, i.e. peers which depart as soon as they have finished their download. The question arises whether the cooperation strategy can smoothen the overall performance degradation caused by a selfish peer behavior. As performance indicators the efficiency, fairness, and robustness of the cooperation strategies are applied. The considered scenarios comprise best-case (altruistic peers) and worst-case scenarios (selfish peers). We further propose a new cooperation strategy to improve the file transfer even when mainly selfish peers are present, the CycPriM (cyclic priority masking) strategy. The strategy allows an efficient P2P based content distribution using ordered chunk delivery with only local information available at a peer.     

BitTorrent系统中一种自适应阻塞算法

BitTorrent系统主要采用tit-for-tat阻塞算法作为节点选择算法,即节点选择当前向自己提供上传最快的一些节点作为上传服务对象。但是该阻塞算法导致新连接节点间过长的等待和节点在下载完成前夕过少的上传连接问题。提出了一种自适应阻塞的改进算法,当节点上传连接过少时自适应的增加上传连接。模拟实验表明,自适应阻塞算法在对系统公平性影响很小的前提下,有效地缩短节点等待时间、增加上传连接数量以及加快节点获取首块资源的速度,从而提高系统文件分发性能。     

面向对等社区的信誉证据服务

对等社区是一类支持网络节点对等的进行信息交换和交易的分布式系统。单个网络节点通常参与多个对等社区,但是现有信誉系统仅根据社区内部证据计算节点信誉,忽略了信誉只有综合考虑其参与的所有社区中的证据才能得到这一社会特性。提出了一种新的信誉组合服务体系结构RepCom在众多社区间实现相关信誉证据的安全收集和管理。RepCom引入一种信誉权威网络实现证据的发布、搜索和获取,并利用逻辑引擎实现基于社区的证据信任策略。RepCom有助于构造全新的通用信誉管理服务,使信誉能够反映节点在不同社区的全局行为。     

SELF-ORGANIZING PEER-TO-PEER SOCIAL NETWORKS

Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.     

GBTM：一种P2P系统中基于群组的信任模型

目前在P2P网络中,缺乏有效的机制来提高系统的安全性,存在许多恶意行为,信任模型已经成为P2P应用研究的一个重要课题。文中对基于信任机制的P2P网络进行研究,根据节点的兴趣、爱好建立不同群组,节点总体信任度由节点之间直接信任度、组与节点之间信任度、组间信任度以及多重参数合成,并通过针对诋毁恶意节点攻击、协同作弊攻击两种不同的攻击模式下的仿真实验表明,该模型具有较高的下载成功,并且能使节点负载处于可控范围内。     

P2P开放网络资源共享信誉系统的研究与实现

网络信誉系统是一个用于综合运算、记录并发布各个客户端以往行为表现的系统。在P2P开放网络资源共享系统中，网络信誉系统起到了两个重要的作用：向用户提供信息以决定对方是否可信，激励交易双方在交易中保持良好的表现以提高自身的信誉度。该文介绍了P2P开放网络与信誉管理系统的概念，分析了现有的信誉系统、模型及其算法。在此基础上设计了新的模型，该模型以信任链方式查询节点信誉度，提出把信誉度分层的方法，通过Java实现了该系统，展望了网络信誉系统的发展方向。     

Adaptive Search Radius – Using hop count to reduce P2P traffic

Peer-to-Peer (P2P) file sharing accounts for a very significant part of the Internet’s traffic, affecting the performance of other applications and translating into significant peering costs for ISPs. It has been noticed that, just like WWW traffic, P2P file sharing traffic shows locality properties, which are not exploited by current P2P file sharing protocols.We propose a peer selection algorithm, Adaptive Search Radius (ASR), where peers exploit locality by only downloading from those other peers which are nearest (in network hops). ASR ensures swarm robustness by dynamically adapting the distance according to file part availability. ASR aims at reducing the Internet’s P2P file sharing traffic, while decreasing the download times perceived by users, providing them with an incentive to adopt this algorithm. We believe ASR to be the first locality-aware P2P file sharing system that does not require assistance from ISPs or third parties nor modification to the server infrastructure.We support our proposal with extensive simulation studies, using the eDonkey/eMule protocol on SSFNet. These show a 19 to 29% decrease in download time and a 27 to 70% reduction in the traffic carried by tier-1 ISPs. ASR is also compared (favourably) with Biased Neighbour Selection (BNS), and traffic shaping. We conclude that ASR and BNS are complementary solutions which provide the highest performance when combined. We evaluated the impact of P2P file sharing traffic on HTTP traffic, showing the benefits on HTTP performance of reducing P2P traffic.A plan for introducing ASR into eMule clients is also discussed. This will allow a progressive migration to ASR enabled versions of eMule client software.ASR was also successfully used to download from live Internet swarms, providing significant traffic savings while finishing downloads faster.     

On the expected file download time of the random time-based switching algorithm in P2P networks

The expected file download time of the random time-based switching algorithm for peer selection and file downloading in a peer-to-peer (P2P) network is still unknown. The main contribution of this paper is to analyze the expected file download time of the time-based switching algorithm for file sharing in P2P networks when the service capacity of a source peer is totally correlated over time, namely, the service capacities of a source peer in different time slots are a fixed value. A recurrence relation is developed to characterize the expected file download time of the time-based switching algorithm. It is proved that for two or more heterogeneous source peers and sufficiently large file size, the expected file download time of the time-based switching algorithm is less than and can be arbitrarily less than the expected download time of the chunk-based switching algorithm and the expected download time of the permanent connection algorithm. It is shown that the expected file download time of the time-based switching algorithm is in the range of the file size divided by the harmonic mean of service capacities and the file size divided by the arithmetic mean of service capacities. Numerical examples and data are presented to demonstrate our analytical results.     

Performance analysis and improvement for BitTorrent‐like file sharing systems

In this paper, we present a simple mathematical model for studying the performance of the BitTorrent ( http://www.bittorrent.com ) file sharing system. We are especially interested in the distribution of peers in different states of the download job progress. With the model we find that the distribution of the download peers follows an asymmetric U‐shaped curve under the stable state, due to BitTorrent's unchoking strategies. In addition, we find that the seeds' departure rate and the download peers' abort rate will influence the peer distribution in different ways notably. We also analyze the content availability under the dying process of the BitTorrent file sharing system. We find that the system's stability deteriorates with decreasing and unevenly distributed online peers, and BitTorrent's built‐in ‘tit‐for‐tat’ unchoking strategy could not help to preserve the integrity of the file among the download peers. We propose an innovative ‘tit‐for‐tat’ unchoking strategy which enables more peers to finish the download job and prolongs the system's lifetime. By playing our innovative strategy, download peers could cooperate to improve the stability of the system by making a trade‐off between the current downloading rate and the future service availability. Finally, experimental results are presented to validate our analytical results and support our proposals. Copyright © 2007 John Wiley & Sons, Ltd.     

P2P文件共享网络中信任管理系统的设计

针对P2P文件共享网络,设计了一个信任管理系统来评估、分发网络中各个实体的信任信息,并利用信任指导协作实体的选择,以隔离恶意实体,改善网络性能.之后的仿真实验证明了系统的有效性.     

Interest-Intended Piece Selection in BitTorrent-like peer-to-peer file sharing systems

BitTorrent is a popular peer-to-peer file sharing system and a target file shared through BitTorrent is partitioned into pieces and downloaded from multiple peers in parallel in order to shorten the download process. However, due to peer dynamics in P2P networks, rare pieces may be lost and thus lead to the so-called last piece problem. BitTorrent employs rarest-first piece selection algorithm to deal with this problem, but its efficacy is limited because each peer only has a local view of piece rareness. In this paper, we propose an Interest-Intended Piece Selection (IIPS) algorithm aiming at better alleviating the last piece problem while maintaining stable cooperation between peers. IIPS is named interest intended in that every IIPS peer favors pieces that, if downloaded, would increase the probability of being interesting to its cooperating peers. Simulation results show that IIPS achieves less occurrences of piece loss under tough conditions and slightly outperforms the BitTorrent’s rarest-first algorithm in terms of higher piece diversity.     

Analysis of file download time in peer-to-peer networks with stochastic and time-varying service capacities

The service capacities of a source peer at different times in a peer-to-peer (P2P) network exhibit temporal correlation. Unfortunately, there is no analytical result which clearly characterizes the expected download time from a source peer with stochastic and time-varying service capacity. The main contribution of this paper is to analyze the expected file download time in P2P networks with stochastic and time-varying service capacities. The service capacity of a source peer is treated as a stochastic process. Analytical results which characterize the expected download time from a source peer with stochastic and time-varying service capacity are derived for the autoregressive model of order 1. Simulation results are presented to validate our analytical results. Numerical data are given to show the impact of the degree of correlation and the strength of noise on the expected file download time. For any chunk allocation method, an analytical result of the expected parallel download time from a source peer with stochastic and time-varying service capacity is derived. It is shown that the algorithm which chooses chunk sizes proportional to the expected service capacities has better performance than the algorithm which chooses equal chunk sizes. It is also shown that multiple source peers do reduce the parallel download time significantly.     

Overlay architectures for file distribution: Fundamental performance analysis for homogeneous and heterogeneous cases

Peer-to-peer networks have been commonly used for tasks such as file sharing or file distribution. We study a class of cooperative file distribution systems where a file is broken up into many chunks that can be downloaded independently. The different peers cooperate by mutually exchanging the different chunks of the file, each peer being client and server at the same time. While such systems are already in widespread use, little is known about their performance and scaling behavior. We develop analytic models that provide insights into how long it takes to deliver a file to N clients given a distribution architecture. Our results indicate that even for the case of heterogeneous client populations it is possible to achieve download times that are almost independent of the number of clients and very close to optimal.     

A Queuing Model for Evaluating the Transfer Latency of Peer-to-Peer Systems

This paper presents a queuing model to evaluate the latency associated with file transfers or replications in peer-to-peer (P2P) computer systems. The main contribution of this paper is a modeling framework for the peers that accounts for the file size distribution, the search time, load distribution at peers, and number of concurrent downloads allowed by a peer. We propose a queuing model that models the nodes or peers in such systems as M/G/1/K processor sharing queues. The model is extended to account for peers which alternate between online and offline states. The proposed queuing model for the peers is combined with a single class open queuing network for the routers interconnecting the peers to obtain the overall file transfer latency. We also show that in scenarios with multipart downloads from different peers, a rate proportional allocation strategy minimizes the download times.     

基于信任的对等网络拓扑构造

在对等网络中．通常使用信任和声望机制来建立节点间的信任关系，以指导用户选择可信的协作节点．本文给出了一个基于信任的对等网络拓扑构造机制，使节点可以通过交互经验和其他节点的反馈采建立对目标节点的信任，并相应地更新同目标节点的链接关系，以便利之后的交互，并提高整个网络的交互性能．仿真实验测试了本文给出的方案．并证明了其效率．     

一种半全局化的P2P信誉度模型

提出了一种新颖的信誉管理机制，首先给出了一套客观的信誉跟踪评价标准，然后根据各个节点的能力与行为表现将它们划分成两类：信誉值和能力均很出众的精英节点，一般的或新加入系统的普通节点。精英节点享有一定特权并组成结构化的网络，普通节点组成无结构的网络。接着用一种半全局化的方法来计算和存储各节点的信誉值。最后，通过实验证明此机制的有效性和健壮性。     

On enhancing reputation management using Peer-to-Peer interaction history

Cooperation incentive mechanisms are an essential ingredient to the success of Peer-to-Peer (P2P) systems as they restraint the phenomenon of free-riding. We introduce an enhancement on reputation-based cooperation incentives used by the eDonkey2000 (ED2K) P2P file sharing network. This enhancement, called History-based Reputation System (HRS), can achieve better detection and control of free-riders, and by doing so enhances the scalability and fairness of the P2P system. HRS does not need the help of dedicated servers and/or central authorities, thus avoiding a single-point of failure. In addition, simulation results show that HRS achieves higher average download rate and smaller average download time for altruistic peers in a file sharing P2P system.     

Stochastic Optimization for Content Sharing in P2P Systems

Available resources in peer-to-peer (P2P) systems depend strongly on resource contributions made by individual peers. Empirical data shows that in the absence of incentives, a majority of the participating peers do not contribute resources. Modeling interactions between individual peers is often difficult as the number of peers in the system can be very large, and the relationships among them can be very complex. In this paper, we propose a new solution for P2P systems, where peers upload and download content to and from the contributing peers based on agreed-upon/determined sharing rates. We propose a P2P solution that deters free-riders by imposing constraints on participating peers; specifically, a peer is allowed access to new content only as long as its own content contribution exceeds an adaptively set threshold. The constraints are enforced either by a central authority (e.g., a tracker) or by a decentralized coalition of peers in a swarm, social network, etc. We derive optimal upload policies for the peers given their estimated future download requirements and their previous contribution (credit) to the other peers. Our results show considerable improvement in the cost-benefit tradeoff for peers that deploy such an optimal policy as compared to heuristic upload policies. We also propose mechanisms based on which the coalition of peers can provide incentives or penalties to participating peers to adjust their policies such that the availability of content and/or number of peers contributing content is maximized.     

The problem of upload competition in peer‐to‐peer systems with incentive mechanisms

As peer‐to‐peer (P2P) file‐sharing systems revolve around cooperation, the design of upload incentives has been one of the most important topics in P2P research for more than a decade. Several deployed systems, such as private BitTorrent communities, successfully manage to foster cooperation by banning peers when their sharing ratio becomes too low. Interestingly, recent measurements have shown that such systems tend to have an oversupply instead of an undersupply of bandwidth designers that have been obsessed with since the dawn of P2P. In such systems, the ‘selfish peer’ problem is finally solved, but a new problem has arisen: because peers have to keep up their sharing ratios, they now have to compete to upload. In this paper, we explore this new problem and show how even highly cooperative peers might in the end not survive the upload competition. On the basis of recent measurements of over half a million peers in private P2P communities, we propose and analyze several algorithms for uploader selection under oversupply. Our algorithms enable sustained sharing ratio enforcement and are easy to implement in both existing and new systems. Overall, we offer an important design consideration for the new generation of P2P systems in which selfishness is no longer an issue. Copyright © 2012 John Wiley & Sons, Ltd.