基于贡献度的自适应P2P流媒体数据调度算法

在P2P流媒体系统中,数据调度算法是决定视频播放质量和系统性能的核心部分。针对当前P2P流媒体数据调度算法未能考虑节点带宽和服务能力的差异,从而造成对系统资源利用不充分的问题,提出一种基于贡献度的自适应(CBA)流媒体数据调度算法。算法定义节点贡献度来衡量节点的数据上传和可用带宽情况,预先向部分节点传输准备数据。并根据数据块优先级、带宽估计情况和节点贡献度等信息进行自适应调整,确定数据块请求的提供方和次序。仿真实验表明,CBA算法能充分地利用节点可用带宽,降低流媒体的启动延迟和服务器负载,改善系统的整体性能。     

P2P-VCG:一种基于博弈论的带宽分配方案

在引入虚拟货币的前提下,目前的P2P系统没有提供有效的带宽分配和计费方案,因此无法在服务开销和用户收益两个方面达到最优.以用户总体收益为研究点,利用博弈论中的VCG(Vickrey-Clarke-groves)算法规划P2P网络中的带宽分配和计费,并且视客户节点为执行带宽分配的主体,可以很好地克服上述问题,这种基于客户节点的带宽分配方案更能反映P2P网络的分布式特性.该带宽分配算法和基于VCG的计费机制达到了近似系统最优和用户激励两个目标,并且可以在实际系统中得到应用     

支持高视频播放率的层次化P2P流媒体系统

目前的P2P流媒体系统具有自组织、容错性和匿名性等优点,但是在健壮性和对高视频播放率的有效支持方面还存在一些问题。本文提出了一种层次化P2P流媒体系统(HPSS)来支持高视频播放率,节点根据带宽和延迟分组聚类,在系统中形成多级层次结构,从视频源服务器来取得视频数据。通过积极地平衡聚类中的上传能力,既能够有效地解决P2P系统中支持高视频播放率的问题,提供接近一个P2P系统能够达到的最大流媒体速率,同时保证系统具有良好的健壮性,在聚类的头节点失效的情况下,不降低整个系统的流媒体速率。最后通过仿真实验证明了HPSS的上述优点。     

一种基于节点可选度的P2P点播流媒体数据调度算法

当前的P2P(Peer-to-Peer)点播流媒体系统中数据调度算法未能充分利用每个用户节点自身的特性.在分析典型数据调度算法基础上提出一种基于节点可选度的数据调度算法(SSP算法).该算法一方面在调度下载数据块时综合考虑了邻居节点带宽能力及其所拥有的数据信息.另一方面对服务节点的请求处理过程进行了优化.SSP算法有利于提高用户节点播放视频的连续性,降低流媒体服务器的负载压力,从而改善P2P点播流媒体系统的整体服务质量.仿真结果和实际应用表明算法性能良好,适用于用户节点能力差异较大的P2P点播流媒体环境.     

基于Donet的P2P流媒体直播优化调度算法

为了提高P2P流媒体系统的整体性能,改善节点的播放质量,针对现有调度算法启动延迟大和节点带宽利用率不高问题,提出了一种可动态调节各节点中待请求紧急数据的流媒体直播优化调度算法(LOSA).该算法不仅考虑了流媒体直播的时间特性,同时还考虑了如何减少紧急数据请求的等待时间以及对Peer节点上传带宽的充分利用.实验结果表明,LOSA算法缩短了终端用户观看视频的延迟,提高了媒体流的连续性.     

一种分层P2 P流媒体系统重叠网的构建策略

基于Peer-to-Peer(P2P)技术的流媒体应用具有部署效率高及可扩展性好等突出优势。而采用分层视频编码技术的P2P流媒体系统把原视频流分解为多个视频层数据进行分发,让节点能够选择与自己带宽资源相匹配的视频质量,使其很好地适应节点的异构性。但是各分层视频数据传输的路径存在较大差异,使重叠网构建策略面临更大的挑战。因此定义了基于分层视频编码技术环境下的P2P流媒体重叠网络构建问题,并证明该问题是一个NP难问题。提出了一种构建重叠网的集中启发式算法,同时还提出了一种基于视频组(Streaming Group)的分布式重叠网络构建策略。通过大规模网络仿真实验验证了基于该分布式重叠网构建策略的分层流媒体系统具备低服务器带宽占用、高数据获取率等优点。     

分布式代理记忆机制的P2P网络研究

为了解决节点频繁离线、信任机制缺乏和带宽有限等问题对P2P网络服务质量的影响,提出了一种分布式代理记忆机制的P2P网络模型。在该模型中,数据被分成若干个数据块,节点访问结束后对数据块的服务进行评价,数据块内容和服务评价更新存储于邻域节点及后继节点;节点访问信息时,根据本地策略优化搜索代理记忆;对服务评价较低的代理记忆进行定期更新与清除。该模型通过数据块分布式代理记忆和数据动态更新的方法,有效地提高了数据可用性,阻止了病毒文件的传播,减轻了带宽压力,提高了搜索效率,增强了系统的安全性和网络性能。     

P2P流媒体系统激励机制设计与分析

在P2P系统中,由于大量自私节点的存在,导致系统中存在公共的悲剧和搭便车现象.如何使节点能够自发的共享自身所拥有的数据资源严重困扰着P2P系统.针对这一问题,提出一种基于博弈论的P2P视频点播激励机制.通过采用差分服务方式,引入贡献值这一概念来激励节点积极上传资源;并基于博弈论的知识对所提机制进行分析,证明所提机制存在纳什均衡并求解出该纳什均衡.模拟实验和相关数据分析表明,该策略能有效的激励节点上传视频数据,改进了P2P网络中的资源共享,从而最大化系统的效用.     

基于请求响应控制机制的数据调度策略

现有P2P流媒体系统的调度策略大多在请求端进行数据调度,在响应端则采用简单的先来先服务或最小时限优先响应的响应策略,其缺点是优先级较高的请求在响应时未必被优先响应。为此,综合考虑数据块的紧迫性、稀缺性以及请求节点的带宽,提出一种基于请求响应控制机制的数据调度策略(DSBRC)。与现有的数据调度策略相比,DSBRC提高系统上行带宽利用率,同时缩短节点启动时延和提高节点播放质量。     

P2P网络多视点立体视频传输的数据块调度策略

立体视频数据量大、编码结构复杂,因此视频数据块的重要性和紧急程度对视频的播放质量有更大的影响作用。综合考虑立体视频播放质量和网络传输效率,提出一种联合优先级和随机传输的P2P数据块调度算法。依据数据块的重要性、紧急性和稀有性计算传输优先级别,同时评估邻居节点传输能力,利用多余带宽传输随机数据块。该算法能够提供优越的视频播放质量,并能够使数据块均匀分布,保证系统传输性能。仿真实验通过分析视频PSNR、启动延迟、节点吞吐量和数据到达率等指标,证明了该算法的有效性。     

Joint bandwidth allocation,data scheduling and incentives for scalable video streaming over peer-to-peer networks

The overall performance of a peer-to-peer (P2P) scalable streaming system largely depends on the strategies employed in bandwidth allocation, data scheduling and incentives. In this paper, we develop a credit-based content-aware bandwidth auction model for scalable streaming in P2P networks. It formulates multi-overlay multi-layer bandwidth request and allocation problems as auction games. Each peer in the games acts as both auctioneer and player. Being a auctioneer, it maximizes the total revenue (credits) by selling upload bandwidth; Being a player, it uses the credits earned in bandwidth sales to sequentially bid for layer bandwidth so as to maximize the received video quality. Also, a content-aware bidding strategy is proposed, under which the required bandwidth quantity from a peer is determined by the informative video chunks and the marginal net utility that peer could provide, as well as the available credits and the maximum layer bit rate. The convergence of the proposed auction algorithm is mathematically proved. Finally, the performance of the proposed scheme is verified by simulation results.     

Security enforcement in wireless sensor networks: A framework based on non-cooperative games

This paper focuses on the design of security enforcement mechanisms for the prevention of denial of service (DoS) attacks in wireless sensor networks. In the first part, we identify the requirement for security enforcement using auction theory, which allows us to detect non-cooperative nodes. Our novel scheme for preventing DoS attacks is called Secure Auction based Routing (SAR). In the proposed protocol, nodes prefer to participate in forwarding incoming packets and gaining reputation in the network. Nodes willing to do so must compete against each other, and the competition is based on auction theory. The amount of bid that each node offers is equal to its utility value; and the price that a winner of a bid pays is a reduction in its original battery power. Since a node’s truthful bidding is shown to be a dominant strategy, in order to prevent DoS attack, nodes that do not bid truthfully should be isolated.In the second part, we formulate the attack–defense problem as a non-cooperative, two-player, non-zero-sum game between an attacker and a wireless sensor network. We show that this game achieves Nash equilibrium, thus leading to a defense strategy for the network. We propose two novel schemes. The first one is called Utility based Dynamic Source Routing (UDSR), which incorporates the total utility of each en-route node in data packets, where utility is the difference between gain and cost for each node. The second scheme is based on a watch-list, where each node earns a rating from its neighbors, based on its previous cooperation in the network. Simulation results show that the proposed game theoretic framework significantly increases the chance of success in defense strategy for the wireless sensor network.     

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.     

基于网络编码的对等网流媒体网络中优化的带宽分配策略

针对采用了网络编码技术的对等网(P2P)流媒体系统应用,提出一种基于负载转移的节点带宽资源均衡策略,尽可能避免节点选择邻居节点并请求带宽资源的随意性形成的节点过载。在策略中,当某些节点过载后将选取部分带宽资源负载较轻的节点作为负载转移节点,同时将请求节点所需数据通过阶梯型带宽分配方式推送给这些选择出的负载转移节点。数值仿真表明,这种负载转移的策略能够有效降低过载节点的带宽资源占用,避免网络热区的出现。     

User density sensitive P2P streaming in wireless mesh networks

Link rate allocation is very important for supporting high video playback rate in Peer-to-Peer video streaming. Although many studies can be found on resource allocation in P2P streaming in wired networks, very few studies have studied the problem in wireless networks, especially in Wireless multi-hop Mesh Networks (WMNs), which is still challenging. To maximize the users’ satisfaction of P2P streaming in WMNs, this paper focuses on link rate allocation problem and proposes a fully distributed algorithm to efficiently utilize the upload and download bandwidth of wireless mesh nodes. We first build an efficient P2P streaming system based on the experimental results from real deployment of our wireless mesh testbed. Then we design an efficient distributed algorithm based on the solution to a linear optimization model, which optimizes towards a user-density-related objective to decide the best streaming rates among peers. Our scheme is resilient to network dynamics that is characteristic in wireless multi-hop peer-to-peer networks. The simulation experiments demonstrate the significant performance enhancement by using the proposed rate allocation algorithm in WMNs.     

Quantum computation based bundling optimization for combinatorial auction in freight service procurements

Combinatorial auction is a useful trade manner for transportation service procurements in e-marketplaces. To enhance the competition of combinatorial auction, a novel auction mechanism of two-round bidding with bundling optimization is proposed. As the recommended the auction mechanism, the shipper/auctioneer integrates the objects into several bundles based on the bidding results of first round auction. Then, carriers/bidders bid for the object bundles in second round. The bundling optimization is described as a multi-objective model with two criteria on price complementation and combination consistency. A Quantum Evolutionary Algorithm (QEA) with β-based rotation gate and the encoding scheme based on non-zero elements in complementary coefficient matrix is developed for the model solution. Comparing with a Contrast Genetic Algorithm, QEA can achieve better computational performances for small and middle size problems.     

P2P流媒体数据块的优化调度策略

在基于数据驱动的P2P流媒体系统中,流媒体数据在参与应用的节点间进行分发,导致流媒体播放质量降低。针对流媒体数据块的分发调度问题,提出一种数据块分发调度策略,通过在调度中考虑节点所需数据块对其流媒体播放质量的影响,以期在合理利用节点有限带宽资源的同时,实现流媒体播放质量的优化。仿真实验结果表明,该策略在改善流媒体播放质量方面具有较明显的优势。     

基于区块链的密封式投标拍卖方案

随着互联网技术的飞速发展,传统拍卖正逐渐转变为电子拍卖,其中隐私保护越来越受到关注。针对当前电子投标拍卖系统中出现的问题,如竞买人隐私存在被泄露的风险、第三方拍卖中心的费用昂贵、第三方拍卖中心可能与竞买人勾结等,提出一种基于区块链智能合约技术的密封式投标拍卖方案。该方案充分利用区块链的去中心化、防篡改和可信赖性等特征构建了一个无第三方的拍卖环境,并通过区块链上的安全保证金策略约束竞买人的行为,从而提高密封式电子拍卖的安全性。同时该方案利用Pedersen承诺保护竞买人的竞拍价格不被泄露,并通过Bulletproofs零知识证明协议验证中标价格的正确性。安全性分析和实验结果表明,提出的拍卖方案满足安全性要求,各个阶段的时间消耗均在可接受范围内,满足日常拍卖要求。     

无收据的密封式电子拍卖协议

提出一个高效的无收据密封式电子拍卖协议，无收据的意义是在协议进行过程中没有可以作为“收据”的公开数据，从而能够更好地保证竞拍者的安全。与现有的无收据密封式电子拍卖协议相比，该文的协议在竞拍价格变化较大的情况下，效率有很大的提高。     

一种保护标价安全的电子拍卖方案

电子拍卖的一个热点问题是保护标价的秘密性，因为存在第三方不可信任或相互勾结．提出了一个实用的保护标价安全的电子拍卖方案，除了中标价以外，它在任何勾结攻击情况下都能保证投标者标价的秘密性，可以公开验证中标价的正确性，效率远远高于最近Brandt提出的方案．其实现只需要O（log2υ）轮通信，其中υ是标价的范围．投标者注册使用数字签名后能保证协议的不可伪造性、抗重放攻击性和不可否认性．协议中使用零知识证明的安全性保证了系统的鲁棒性．