BitTorrent系统中一种近似全局最少优先的文件块选择策略*

提出了一种近似全局最优的文件块选择策略——种子覆盖网。在BitTorrent系统中,所有种子自组成一个应用层覆盖网,每个种子保存已上传文件块信息;种子响应请求时通过种子覆盖网查找下载者感兴趣且上传数目最少的文件块上传。模拟实验表明,与纯局部最少优先策略和SmartSeed策略相比较,在采用种子覆盖网策略的BT系统中,节点平均下载时间缩短了25%~35%,并且下载第一块和最后一块的平均等待时间缩短了40%~60%。     

一种缩短下载时间优先的自适应BitTorrent激励协议

BitTorrent激励机制的目标是保证节点上传和下载之间的公平性,但相比公平性而言,实际应用中的节点更优先考虑的是文件下载时间,据此文中提出了一种缩短文件下载时间优先的自适应BitTorrent激励协议AIPS.文中首先基于Markov模型对BitTorrent现有激励机制的效果给出了定量分析,分析了激励机制下的文件传输结构,并用概率分析方法给出了该传输结构下最小化文件下载时间的条件.应用分析结果文中定义了一个以缩短文件下载时间为效用的博弈,在该博弈达到Nash平衡时各节点采用的策略就是激励协议AIPS.模拟实验表明文中提出的AIPS较现有的BitTorrent激励协议能明显提高文件共享系统性能,提高文件下载效率.     

BitTorrent下基于活跃度的传输节点选择算法

近年来,对等网络（peer to peer,P2P）因其高效的分片和分发等机制,已成为大数据高效分发的关键支撑技术。针对P2P文件分发系统BitTorrent中Tracker服务器端节点选择算法没有考虑节点活跃度的问题,提出了一种基于活跃度的Tracker服务器端节点选择算法。该算法选择出活跃度高的节点来建立一个更高效的分发网络,使之更能符合请求节点的需求,帮助请求节点更加高效地完成下载任务。实验结果表明,改进后的节点选择算法可以缩短文件的下载时间,提高网络的分发效率,提升系统的性能。     

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。     

基于GPU的RUB算法研究与实现

GPU通用计算已经在很多领域中得到应用,包括金融、石油、天文学、流体力学、信号处理、电磁仿真、模式识别、视频压缩等领域。将GPU通用计算应用到P2P协议中,通过使用全局存储器和共享存储器两种方法把BitTorrent协议中的随机邻居节点选择算法和随机文件块选择算法（RUB）映射到GPU上,用GPU加速了BitTorrent协议文件块的分发。     

P2P网络中自适应节点选择策略

以Bittorrent应用为背景,对P2P网络中传统的节点选择策略进行了研究分析,指出了传统节点选择策略中存在的随机选择节点连接与交互以及交互过程中节点带宽利用率偏低的问题.对Tracker以外的节点来源如DHT、PEX节点来源的情况进行分析,以自身上传带宽利用率和网络中各节点的空闲带宽为参考,以减少带宽资源浪费、提高带宽利用率为目的.针对节点选择各阶段特点,设计并实现自适应节点选择机制,实验表明在对原系统的公平性影响很小的情况下,自适应机制能有效的减少网络中带宽资源浪费并将自身上传节点带宽利用率提高8.45％.小规模节点环境下(100节点)平均缩短节点下载完成时间6.7％,大规模下载环境下(500节点)平均缩短下载完成时间36.3％.有效的提高了系统中文件的获得和分发效力.     

一种嵌入式BitTorrent优化策略

BitTorrent（BT）的Optimistic Unchoke算法为BT下载带来了一定程度的不公平性。利用该缺陷,消极上节点可以通过维护大量的伙伴节点来获得较高的下载速率。普通BT客户端维护伙伴节点的机制不适合于内存和网络连接数受限的嵌入式平台。论述了一种针对嵌入式BT的伙伴节点维护策略。该策略通过有效维护大量的可用节点,在满足嵌入式平台内存和网络连接数受限、上传速率低的条件下,利用Optimistic Unchoke机制来增加获得节点服务的概率,从而提高客户端的下载性能。     

请求下降邻域叠加选取分布式P2P 视频点播调度

为实现对等架构的低成本视频流传输和实时播放要求,提出基于请求下降叠加选 取的分布式P2P 视频点播调度算法。首先,基于叠加技术构建P2P 视频点播的技术指标,充分 考虑输入邻域节点、输出邻域节点和媒体服务器负载3 组优化指标,构建叠加架构和分布式算 法流程;其次,利用请求下降策略对发送节点和服务节点选取进行改进,解决可能出现的带宽 低利用率和无效的视频播放问题;最后,通过BitTorrent 视频点播系统对所提算法的有效性进 行了验证。     

BT邻居结点算法验证平台的设计与实现

为提高BitTorrent系统的文件分布性能,提出了一个优化的邻居结点选择算法.首先通过n叉树的结构模型分析BitTorrent系统,然后选择与请求结点拥有相近文件块数的结点作为邻居结点.为了证验该算法的可行性,基于BitTorrent文件共享系统的工作原理,设计了一个基于离散事件驱动的串行模拟器BTSim,详细介绍了该模拟器的设计思想和各个模块的具体实现.最后,使用模拟器对不同算法进行比较,比较结果表明了该算法的有效性.     

一种基于节点全局信任值的BitTorrent系统区分服务机制

BitTorrent系统中节点的搭便车行为严重影响系统的健壮性和稳定性.针对BitTorrent系统中搭便车行为抑制机制存在的不足,提出一种基于节点全局信任值的区分服务机制.在该机制中,Tracker服务器依据节点反馈的本地信任值计算节点全局信任值,依据全局信任值识别贡献节点与搭便车节点,对两类节点采取区分服务策略:为贡献节点与搭便车节点分别返回其同类对等节点,使搭便车节点无法与贡献节点建立连接进而获取文件资源;在贡献节点中又进一步区分高贡献节点和普通贡献节点,引入返回比例因子为其提供差异服务,使高贡献节点获得更快的下载速度.实验表明,该机制能有效隔离并惩罚搭便车节点,奖励高贡献节点.     

Optimizing transmission time of scalable coded images in peer-to-peer networks

In this paper, we study how to optimize image transmission time in peer-to-peer networks by considering the property of bitstreams generated by image coding algorithms. Images can be either scalable coded or nonscalable coded. Since transmission of nonscalable coded images is well understood, we focus on the transmission of scalable coded images in this paper. Because scalable coding embeds lower bit-rate bitstreams into higher bit-rate bitstreams, there exists a many-to-one relationship between supplying and requesting peers. When a requesting peer asks for an image coded in a particular bit rate, multiple peers with the same image but coded in different bit rates can supply to the requesting peer. This enables us to assign the task of image transmission to multiple supplying peers, split the traffic among these peers, and then reduce overall transmission time. Therefore, when we transmit scalable coded images over peer-to-peer networks, it is important to design optimal peer assignment algorithms to minimize the overall transmission time for the requesting peer. In this paper, we first formally define the peer assignment problem and then establish a sufficient condition on the optimality of peer assignment. Based on this condition, we propose an optimal peer assignment algorithm in continuous space (OPA-CS) and then derive a suboptimal peer assignment algorithm in integer space (SOPA-IS). Finally, we carry out extensive experiments to verify the superior performance of the proposed peer assignment algorithms by comparing with two simple heuristic schemes.     

双端协作的P2P流媒体节点选择机制

针对P2P流媒体系统现有节点选择方法仅在请求节点执行且功能单一的问题,提出超级节点和请求节点双端协作的节点选择机制。在超级节点端,根据路由相似的思想提出面向网络拓扑聚集性的候选节点选择算法。在请求节点端,综合考虑系统动态性与异构性,提出基于枚举的服务节点选择算法,保证流服务质量,融入动态冗余思想以提高健壮性。仿真结果表明,该机制能更好地改进系统的网络拓扑聚集性,提高流服务质量和健壮性。     

无线自组网中节点协作的纳什均衡研究

根据自私节点的特性,提出节点协作的博弈模型。针对单阶段博弈及采取礼尚往来策略、冷酷策略、单步触发策略的重复博弈,分析并比较实现节点协作的纳什均衡条件。结果表明,单阶段博弈中自私节点的纳什均衡类似于囚徒困境,重复博弈采用礼尚往来策略时,实现最佳纳什均衡的临界值最小,相比其他策略更易实现协作。     

Web search results caching service for structured P2P networks

This paper proposes a two-level P2P caching strategy for Web search queries. The design is suitable for a fully distributed service platform based on managed peer boxes (set-top-box or DSL/cable modem) located at the edge of the network, where both boxes and access bandwidth to those boxes are controlled and managed by an ISP provider. Our solution significantly reduces user query traffic going outside of the ISP provider to get query results from the respective Web search engine. Web users are usually very reactive to worldwide events which cause highly dynamic query traffic patterns leading to load imbalance across peers. Our solution contains a strategy to quickly ease imbalance on peers and spread communication flow among participating peers. Each peer maintains a local result cache used to keep the answers for queries originated in the peer itself and queries for which the peer is responsible for by contacting the Web search engine on-demand. When query traffic is predominantly routed to a few responsible peers our strategy replicates the role of “being responsible for” to neighboring peers so that they can absorb query traffic. This is a fairly slow and adaptive process that we call mid-term load balancing. To achieve a short-term fair distribution of queries we introduce a location cache in each peer which keeps pointers to peers that have already requested the same queries in the recent past. This lets these peers share their query answers with newly requesting peers. This process is fast as these popular queries are usually cached in the first DHT hop of a requesting peer which quickly tends to redistribute load among more and more peers.     

Hybrid fluid modeling approach for performance analysis of P2P live video streaming systems

In this paper a hybrid modeling approach with different modeling formalisms and solution methods is employed in order to analyze the performance of peer to peer live video streaming systems. We conjointly use queuing networks and Fluid Stochastic Petri Nets, developing several performance models to analyze the behavior of rather complex systems. The models account for: network topology, peer churn, scalability, peer average group size, peer upload bandwidth heterogeneity and video buffering, while introducing several features unconsidered in previous performance models, such as: admission control for lower contributing peers, control traffic overhead and internet traffic packet loss. Our analytical and simulation results disclose the optimum number of peers in a neighborhood, the minimum required server upload bandwidth, the optimal buffer size and the influence of control traffic overhead. The analysis reveals the existence of a performance switch-point (i.e. threshold) up to which system scaling is beneficial, whereas performance steeply decreases thereafter. Several degrees of degraded service are introduced to explore performance with arbitrary percentage of lost video frames and provide support for protocols that use scalable video coding techniques. We also find that implementation of admission control does not improve performance and may discourage new peers if waiting times for joining the system increase.     

Dynamic Bandwidth Auctions in Multioverlay P2P Streaming with Network Coding

In peer-to-peer (P2P) live streaming applications such as IPTV, it is natural to accommodate multiple coexisting streaming overlays, corresponding to channels of programming. In the case of multiple overlays, it is a challenging task to design an appropriate bandwidth allocation protocol, such that these overlays efficiently share the available upload bandwidth on peers, media content is efficiently distributed to achieve the required streaming rate, as well as the streaming costs are minimized. In this paper, we seek to design simple, effective, and decentralized strategies to resolve conflicts among coexisting streaming overlays in their bandwidth competition and combine such strategies with network-coding-based media distribution to achieve efficient multioverlay streaming. Since such strategies of conflict are game theoretic in nature, we characterize them as a decentralized collection of dynamic auction games, in which downstream peers bid for upload bandwidth at the upstream peers for the delivery of coded media blocks. With extensive theoretical analysis and performance evaluation, we show that these local games converge to an optimal topology for each overlay in realistic asynchronous environments. Together with network-coding-based media dissemination, these streaming overlays adapt to peer dynamics, fairly share peer upload bandwidth to achieve satisfactory streaming rates, and can be prioritized.     

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.     

Adaptive topology formation for peer-to-peer video streaming

In this paper we propose an adaptive P2P video streaming framework to address the challenges due to bandwidth heterogeneity and peer churn on the Internet. This adaptive streaming framework consists of two major components, source rate adaptation and adaptive overlay topology formation, to maximize the video quality and fully utilize the overall peer upload capacity. In the source rate adaptation, the video server adapts the video source rate automatically based on the local measurement of peers’ download rates, so that the P2P network is not overloaded beyond its bandwidth capacity and peers are able to achieve smooth video playback. To combat bandwidth heterogeneity, we propose to construct a desirable link-level homogeneous overlay topology using a Markov chain Monte Carlo method, so that peers achieve an equal per-connection upload/download bandwidth. In this link-level homogeneous network, video flows do not encounter any bottlenecks along the delivery paths, and peers achieve high download rates to ensure smooth video playback. We also design a fully distributed algorithm to implement the dual mechanisms of the adaptive topology formation and the source rate maximization. To evaluate the performance of our streaming framework, we conduct both mathematical analysis and extensive simulations. The simulation results confirm our analysis and show that the proposed distributed algorithm is able to maximize the video playback quality with fast convergence.     

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.     

一种新的P2P流媒体数据分配算法评价准则

在多对单传输模式下,数据分配算法是P2P流媒体系统关键技术之一.本文介绍了国内外的分配算法,从缓冲延迟、数据块连续性、出错纠正功能、节点限制等多个角度提出了新的数据分配算法的评价指标,并提出综合评价准则的计算方法.通过仿真实验,表明了各个算法在不同的环境下各有优劣,并为新算法的研究提供了有效的途径.