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。     

Chord2: A two-layer Chord for reducing maintenance overhead via heterogeneity

Empirical studies have shown that participating nodes in peer-to-peer (P2P) systems are not equivalent. Some nodes, known as “super peers”, are more powerful and stable than the others. Such heterogeneity has been taken into account in the design of P2P systems in two ways: by employing super peers to serve as index servers for query, and by routing through super peers to speed up query. In this paper, we use super peers to reduce maintenance cost in Chord—a DHT network which, like other DHT-based systems, is often praised for its guaranteed search feature but has relatively higher maintenance overhead than Gnutella-like unstructured P2P networks.     

H-Trust: A Group Trust Management System for Peer-to-Peer Desktop Grid

Peer-to-Peer Desktop Grid (P2PDG) has emerged as a pervasive cyber-infrastructure tackling many large-scale applications with high impacts. As a burgeoning research area, P2PDG can support numerous applications, including scientific computing, file sharing, web services, and virtual organization for collaborative activities and projects. To handle trustworthiness issues of these services, trust and reputation schemes are proposed to establish trust among peers in P2PDG. In this paper, we propose a robust group trust management system, called H-Trust, inspired by the H-index aggregation technique. Leveraging the robustness of the H-index algorithm under incomplete and uncertain circumstances, H-Trust offers a robust personalized reputation evaluation mechanism for both individual and group trusts with minimal communication and computation overheads. We present the H-Trust scheme in five phases, including trust recording, local trust evaluation, trust query phase, spatial-temporal update phase, and group reputation evaluation phases. The rationale for its design, the analysis of the algorithm are further investigated. To validate the performance of H-Trust scheme, we designed the H-Trust simulator HTrust-Sim to conduct multi-agent-based simulations. Simulation results demonstrate that H-Trust is robust and can identify and isolate malicious peers in large scale systems even when a large portion of peers are malicious.     

Characterizing Economic and Social Properties of Trust and Reputation Systems in P2P Environment

Considering the fact that P2P （Peer-to-Peer） systems are self-organized and autonomous, social-control mechanism （like trust and reputation） is essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest and malicious peer behaviors. So, naturally, we advocate that P2P systems that gradually act as an important information infrastructure should be multi-disciplinary research topic, and reflect certain features of our society. So, from economic and social perspective, this paper designs the incentive-compatible reputation feedback scheme based on well-known economic model, and characterizes the social features of trust network in terms of efficiency and cost. Specifically, our framework has two distinctive purposes： first, from high-level perspective, we argue trust system is a special kind of social network, and an accurate characterization of the structural properties of the network can be of fundamental importance to understand the dynamics of the system. Thus, inspired by the concept of weighted small-world, this paper proposes new measurements to characterize the social properties of trust system, that is, high global and local efficiency, and low cost; then, from relative low-level perspective, we argue that reputation feedback is a special kind of information, and it is not free. So, based on economic model, VCG （Vickrey-Clarke-Grove）-like reputation remuneration mechanism is proposed to stimulate rational peers not only to provide reputation feedback, but truthfully offer feedback. Furthermore, considering that trust and reputation is subjective, we classify the trust into functional trust and referral trust, and extend the referral trust to include two factors： similarity and truthfulness, which can efficiently reduce the trust inference error. The preliminary simulation results show the benefits of our proposal and the emergence of certain social properties in trust network.     

A simple analytical framework to analyze search strategies in large-scale peer-to-peer networks

This paper presents an analytical framework to study search strategies in large-scale decentralized unstructured peer-to-peer (P2P) networks. The peers comprising the P2P network and their application-level connections are modeled as generalized random graphs (GRGs) whose simple and efficient analysis is accomplished using the generating function of the graph’s degree distribution. The framework we defined allows the computation of several interesting performance indexes to be used to compare different search strategies: in particular, the average number of messages sent throughout the P2P network and the probability that a query is successful are used as examples. Furthermore, assuming that the cumulative distribution function (CDF) of the time required by a peer to positively reply to a query is known, we show how to derive the CDF of the time it takes for a randomly chosen peer to obtain at least one positive reply from other peers. The approach is validated through simulation showing that the accuracy of the proposed model improves as the size of the P2P network increases making it a suitable tool for the analysis of search strategies in large-scale systems.     

Skyframe: a framework for skyline query processing in peer-to-peer systems

This paper looks at the processing of skyline queries on peer-to-peer (P2P) networks. We propose Skyframe, a framework for efficient skyline query processing in P2P systems, which addresses the challenges of quick response time, low network communication cost and query load balancing among peers. Skyframe consists of two querying methods: one is optimized for network communication while the other focuses on query response time. These methods are different in the way in which the query search space is defined. In particular, the first method uses a high dominating point that has a large dominating region to prune the search space to achieve a low cost in network communication. On the other hand, the second method relaxes the search space in order to allow parallel query processing to speed up query response. Skyframe achieves query load balancing by both query load conscious data space splitting/merging during the join/departure of nodes and dynamic load migration. We further show how to apply Skyframe to both the P2P systems supporting multi-dimensional indexing and the P2P systems supporting single-dimensional indexing. Finally, we have conducted extensive experiments on both real and synthetic data sets over two existing P2P systems: CAN (Ratnasamy in A scalable content-addressable network. In: Proceedings of SIGCOMM Conference, pp. 161–172, 2001) and BATON (Jagadish et al. in A balanced tree structure for peer-to-peer networks. In: Proceedings of VLDB Conference, pp. 661–672, 2005) to evaluate the effectiveness and scalability of Skyframe.     

Improving peer-to-peer search performance through intelligent social search

As a large amount of information is added onto the Internet on a daily basis, the efficiency of peer-to-peer (P2P) search has become increasingly important. However, how to quickly discover the right resource in a large-scale P2P network without generating too much network traffic remains highly challenging. In this paper, we propose a novel P2P search method, by applying the concept of social grouping and intelligent social search; we derive peers into social groups in a P2P network to improve search performance. Through a super-peer-based architecture, we establish and maintain virtual social groups on top of a P2P network. The interactions between the peers in the P2P network are used to incrementally build the social relationships between the peers in the associated social groups. In such a P2P network, a search query is propagated along the social groups in the overlay social network. Our preliminary experiments have demonstrated that our method can significantly shorten search routes and result in a higher peer search performance. In addition, our method also enhances the trustworthiness of search results because searches go through trusted peers.     

纯Peer to Peer环境下有效的Top-k查询

目前大多数的Peer-to-Peer(P2P)系统只支持基于文件标识的搜索,用户不能根据文件的内容进行搜索.Top-k查询被广泛地应用于搜索引擎中,获得了巨大的成功.可是,由于P2P系统是一个动态的、分散的系统,在纯的P2P环境下进行top-k查询是具有挑战性的.提出了一种基于直方图的分层top-k查询算法.首先,采用层次化的方法实现分布式的top-k查询,将结果的合并和排序分散到P2P网络中的各个节点上,充分利用了网络中的资源.其次,根据节点返回的结果为节点构建直方图,利用直方图估计节点可能的分数上限,对节点进行选择,提高了查询效率.实验证明,top-k查询提高了查询效果,而直方图则提高了查询效率.     

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。     

An advertisement-based peer-to-peer search algorithm

Most of the existing search algorithms for unstructured peer-to-peer (P2P) systems share one common approach: the requesting node sends out a keyword search query and the query message is repeatedly routed and forwarded to other peers in the overlay network. Due to multiple hops involved in query forwarding, the search may result in a long delay before it is answered. Furthermore, some incapable nodes may be overloaded when the query traffic becomes intensive or bursty.     

Multifactor hierarchical fuzzy trust evaluation on peer-to-peer networks

Decentralized Peer-to-Peer (P2P) networks offer not only opportunities but also threats. Due to the autonomy, self-interest and heterogeneousness of peers, the interaction outcomes are uncertain. One way to minimize the threats in such an open environment is exploiting the reputation method to evaluate the trustworthiness and predict the future behaviors of peers. While most of the existing reputation-based trust models focus on preventing network from the malicious peers, peers’ capabilities to fulfill the tasks are mostly ignored. In this paper, we present a novel trust model MHFTrust which quantifies and compares the trustworthiness of peers based on hierarchical fuzzy system. Six capability factors are identified to describe the peers’ trust on the capability, and one security factor, named “Malicious behavior” is used to evaluate the peers’ trust on security. Our trust model consisted of local-trust computation based on fuzzy techniques and global reputation aggregation, which integrates feedback from other peers to produce a global reputation for each peer. Credibility and weight of feedback are introduced to facilitate the computation of global reputation. It is shown in simulation that our trust model greatly improves the efficiency of P2P system, while the number of inauthentic files on the network is significantly decreased.     

一种对等网中基于相互信任的两层信任模型

在P2P 系统中,声誉模型是建立节点间信任关系的重要方法之一,但现有的P2P 声誉模型几乎都是纯分散式的,具有信任收敛慢、信任管理复杂和网络开销大等缺点.在TLT(two-level trust)中,节点自发组织为信任簇,信任评价以簇为单位.每个簇由簇首和成员节点组成,簇首和成员节点之间是一种相互信任的关系:簇首为了提高自身的簇间服务信任,利用簇内服务信任观察成员节点的服务性能,过滤恶意的成员节点;成员节点为了提高服务声誉和接受更好的服务,利用代理信任考察簇首的管理能力.分析和仿真结果表明:在TLT 中,节点的信任值收敛快,恶意行为能够被快速识别;TLT 可扩展性好,如信任管理简单和网络开销小.     

Reducing network traffic in unstructured P2P systems using Top-k queries

A major problem of unstructured P2P systems is their heavy network traffic. This is caused mainly by high numbers of query answers, many of which are irrelevant for users. One solution to this problem is to use Top-k queries whereby the user can specify a limited number (k) of the most relevant answers. In this paper, we present FD, a (Fully Distributed) framework for executing Top-k queries in unstructured P2P systems, with the objective of reducing network traffic. FD consists of a family of algorithms that are simple but effective. FD is completely distributed, does not depend on the existence of certain peers, and addresses the volatility of peers during query execution. We validated FD through implementation over a 64-node cluster and simulation using the BRITE topology generator and SimJava. Our performance evaluation shows that FD can achieve major performance gains in terms of communication and response time. Recommended by: Sunil Prabhakar Work partially funded by the ARA Massive Data of the Agence Nationale de la Recherche.     

P2P环境下数据管理系统上的Top-k查询

目前大多数P2P系统只提供文件的共享,缺乏数据管理能力.基于关系数据库上的关键搜索,本文提出了一种在P2P环境下共享数据库的新框架,其中每个节点上的数据库被看成是一个文档集,用户不用考虑数据库的模式结构信念,简化了不同节点数据库模式间的映射过程,能更好地适应P2P的分散和动态特性.将基于直方图的分层Top-k查询算法扩展到P2P环境下的数据库管理系统上,文档集和数据库的查询被统一起来,一致对待.在查询处理期间,直方图可以自动更新,同时根据查询结果,邻居节点可以自调整,具有自适应性.实验结果表明,基于关键词的数据库共享突破了传统的数据库共享模式,简化了数据访问方式,而基于直方图的Top-k查询算法提高了查询效率.     

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。     

An Effective P2P Search Scheme to Exploit File Sharing Heterogeneity

Although the original intent of the peer-to-peer (P2P) concept is to treat each participant equally, heterogeneity widely exists in deployed P2P networks. Peers are different from each other in many aspects, such as bandwidth, CPU power, and storage capacity. Some approaches have been proposed to take advantage of the query forwarding heterogeneity such that the high bandwidth of powerful nodes can be fully utilized to maximize the system capacity. In this paper, we suggest using the query answering heterogeneity to directly improve the search efficiency of P2P networks. In our proposed differentiated search (DiffSearch) algorithm, the peers with high query answering capabilities will have higher priority to be queried. Because the query answering capabilities are extremely unbalanced among peers, a high query success rate can be achieved by querying only a small portion of a network. The search traffic is significantly reduced due to the shrunken search space. Our trace analysis and simulation show that the DiffSearch algorithm can save up to 60 percent of search traffic     

Linking identical neighborly partitions for efficient high-dimensional similarity search in unstructured peer-to-peer systems

Peer-to-Peer (P2P) computing has recently attracted a great deal of research attention. In a P2P system, a large number of nodes can potentially be pooled together to share their resources, information, and services. However, existing unstructured P2P systems lack support for content-based search over data objects which are generally represented by high-dimensional feature vectors. In this paper, we propose an efficient and effective indexing mechanism to facilitate high-dimensional similarity query in unstructured P2P systems, named Linking Identical Neighborly Partitions (LINP), which combines both space partitioning technique and routing index technique. With the aid of LINP, each peer can not only process similarity query efficiently over its local data, but also can route the query to the promising peers which may contain the desired data. In the proposed scheme, each peer summarizes its local data using the space partitioning technique, and exchanges the summarized index with its neighboring peers to construct routing indices. Furthermore, to improve the system performance with peer updates, we propose an extension of the LINP, named LINP⁺, where each peer can reconfigure its neighboring peers to keep relevant peers nearby. The performance of our proposed scheme is evaluated over both synthetic and real-life high-dimensional datasets, and experimental results show the superiority of our proposed scheme.     

一种实现高效副本发布与查询的DHT覆盖网

在对等计算应用中,副本复制技术是提升查询命中率、提升查询速度、维护负载均衡的一种有效方法,然而它也提升了在存储空间和流量上的代价.研究如何在结构化的P2P覆盖网中,通过拓扑优化手段减少复制中的冗余流量和冗余副本.首先在网络中选择支配集节点作为超级节点,设计一个层次化的、体现节点邻近度的P2P覆盖网,然后基于多hash函数,开发对应的复制技术以实现低代价的副本查询.该方法能够有效地在网络中分散副本,提升查询命中率,减少冗余消息和所需存储空间.给出了性能指标的理论分析,并通过仿真验证了该方法的优越性.     

P2P文件共享系统中的分组信誉驱动机制

在P2P文件共享系统中,常会出现许多有策略的欺骗行为,而现有的信任模型并不能完全消除交易的风险。综合局部信任机制和全局信任机制,根据节点间相关的共享记录数据提出一种新的信誉计算方法,并进一步提出受信誉驱动的分组组织管理和节点搜索算法。仿真结果证明该信誉驱动机制能搜索到信誉值高的节点作为交易对象,并能有效降低系统面对合谋恶意节点和具有交易策略的恶意节点攻击时的交易风险。     

PSON: A scalable P2P file sharing system with efficient complex query support

A desired P2P file sharing system is expected to achieve the following design goals: scalability, routing efficiency and complex query support. In this paper, we propose a powerful P2P file sharing system, PSON, which can satisfy all the three desired properties. PSON is essentially a semantic overlay network of logical nodes. Each logical node represents a cluster of peers that are close to each other. A powerful peer is selected in each cluster to support query routing on the overlay network while the less powerful peers are responsible for the maintenance of shared contents. To facilitate query routing, super peers are organized in form of a balanced binary search tree. By exploiting the concept of semantics, PSON can support complex queries in a scalable and efficient way. In this paper, we present the basic system design such as the semantic overlay construction, query routing and system dynamics. A load balancing scheme is proposed to further enhance the system performance. By simulation experiments, we show that PSON is scalable, efficient and is able to support complex queries.