移动P2P网络基于博弈论方法的协作激励机制

在移动P2P网络中,部分自私的移动节点只是大量地消耗已有网络资源而不提供自己的资源。考虑到移动P2P网络的资源有限性以及部分节点具有自私行为的特点,提出了一种基于博弈论的协作激励机制。该机制根据移动节点的不同贡献大小来提供不同网络服务质量,最大限度地鼓励了每个移动节点参与协作和共享。同时,详细描述和分析了协作激励机制中的网络资源分配策略,并且证明了该协作激励机制的博弈存在一个稳定的纳什（Nash）均衡。通过仿真实验发现,该激励机制有效地激发了移动节点间的协作,优化了整个网络的性能。同现有的协作激励策略相比,提高了数据包转发率等。     

TRUST BY ASSOCIATION: A META‐REPUTATION SYSTEM FOR PEER‐TO‐PEER NETWORKS

Trust mechanisms are used in peer‐to‐peer (P2P) networks to help well‐behaving peers find other well‐behaving peers with which to trade. Unfortunately, these trust mechanisms often do little to keep badly behaving peers from entering and taking advantage of the network, which makes the resulting network difficult or impossible to use for legitimate purposes such as e‐commerce. We propose trust by association, a way of tying peers together in invitation‐only P2P networks in such a way as to encourage the removal of badly behaving peers. We use invitations to create a structure within the otherwise ad hoc P2P network. Using this structure, we create a meta‐reputation system where we measure a peer’s trustworthiness not only by its own behavior, but also by the behavior of the peers it has invited to join. The connection created between the peers takes advantage of the external social relationship that must exist before a peer can be invited into the network. The result is a P2P network where, rather than just trying to marginalize badly behaving peers, there is incentive to kick them out of the network. We present results from a simple simulation showing that our approach works well in general when combined with and compared to an existing trust mechanism.     

On Game Theoretic Peer Selection for Resilient Peer-to-Peer Media Streaming

Peer-to-peer (P2P) media streaming quickly emerges as an important application over the Internet. A plethora of approaches have been suggested and implemented to support P2P media streaming. In our study, we first classified existing approaches and studied their characteristics by looking at three important quantities: number of upstream peers (parents), number of downstream peers (children), and average number of links per peer. In existing approaches, peers are assigned with a fixed number of parents without regard to their contributions, measured by the amount of outgoing bandwidths. Obviously, this is an undesirable arrangement as it leads to highly inefficient use of the P2P links. This observation motivates us to model the peer selection process as a cooperative game among peers. This results in a novel peer selection protocol such that the number of upstream peers of a peer is related to its outgoing bandwidth. Specifically, peers with larger outgoing bandwidth are given more parents, which make them less vulnerable to peer dynamics. Simulation results show that the proposed protocol improves delivery ratio using similar number of links per peer, comparing with existing approaches under a wide range of system parameters.     

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.     

An incentive mechanism for message relaying in unstructured peer-to-peer systems

Distributed message relaying is an important function of a peer-to-peer system to discover service providers. Existing search protocols in unstructured peer-to-peer systems create huge burden on communications, cause long response time, or result in unreliable performance. Moreover, with self-interested peers, these systems are vulnerable to the free-riding problem. In this paper we present an incentive mechanism that not only mitigates the free-riding problem, but also achieves good system efficiency in message relaying for peer discovery. In this mechanism promised rewards are passed along the message propagation process. A peer is rewarded if a service provider is found via a relaying path that includes this peer. The mechanism allows peers to rationally trade-off communication efficiency and reliability while maintaining information locality. We provide some analytic insights to the symmetric Nash equilibrium strategies of this game, and an approximate approach to calculate this equilibrium. Experiments show that this incentive mechanism brings a system utility generally higher than breadth-first search and random walks, based on both the estimated utility from our approximate equilibrium and the utility generated from learning in the incentive mechanism.     

A quorum-based protocol for searching objects in peer-to-peer networks

Peer-to-peer (P2P) system is an overlay network of peer computers without centralized servers, and many applications have been developed for such networks such as file sharing systems. Because a set of peers dynamically changes, design and verification of efficient protocols is a challenging task. In this paper, we consider an object searching problem under a resource model such that there are some replicas in a system and the lower bound of the ratio /spl rho/=n'/n is known in advance, where n' is a lower bound of the number of peers that hold original or replica for any object type and n is the total number of peers. In addition, we consider object searching with probabilistic success, i.e., for each object search, object must be found with at least probability 0相似文献   

On incentivizing upload capacity in P2P-VoD systems: Design,analysis and evaluation

Free riding has long been a serious problem in peer-to-peer (P2P) systems due to the selfish behavior of individual users. To conquer this problem, a key design issue of the P2P systems is to appropriately incentivize users to contribute resources. In P2P Video-on-Demand (VoD) applications, content providers need to incentivize the peers to dedicate bandwidth and upload data to one other so as to alleviate the upload workload of their content servers. In this paper, we design a simple yet practical incentive mechanism that rewards each peer based on its dedicated upload bandwidth. We use a mean field interaction model to characterize the distribution of number of peers in different video segments, based on which we characterize the content providers’ uploading cost as a function of the peers’ contribution. By using a game theoretic framework, we analyze the interaction between a content provider’s rewarding strategy and the peers’ contributing behaviors and derive a unique Stackelberg equilibrium. We further analyze the system efficiency in terms of the price of anarchy and study the long term behavior of the system under a repeated game setting. Via extensive simulations, we validate the stability and efficiency of our incentive scheme.     

基于纳什议价的对等网络资源分配

针对对等(P2P)网络中普遍存在的自由下载问题,提出保证节点最小服务质量的一种基于纳什议价的资源分配方案。首先,建立保证节点最小服务质量的理论模型,分析表明合作博弈的节点议价权力与其最大贡献能力正相关,非合作博弈节点的议价权力与其最大贡献能力负相关,因此,合作节点比非合作节点获得更多的资源;其次,证明了合作博弈中节点的相对议价权力越大,节点获得的资源越多,收益越大,反之亦然。最后,通过仿真验证系统保证节点获得最小服务质量的前提下,合作节点获得的资源与节点的初始资源分配和纳什议价权力等因素相关;初始资源分配与节点的最大贡献能力呈正相关,并随着节点数目的增加而减少;议价权力随着节点数目的增加而下降,节点获得的资源随着节点议价权力的增加而增加。该方案与经典保证公平性的平均资源分配方案相比,合作节点能获得更多的资源。仿真结果验证了理论分析中在保证节点服务质量前提下,节点议价权力越大,获得的资源越多。     

PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities

Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.     

DGTM: a dynamic grouping based trust model for mobile peer-to-peer networks

The special characteristics of the mobile environment, such as limited bandwidth, dynamic topology, heterogeneity of peers, and limited power, pose additional challenges on mobile peer-to-peer (MP2P) networks. Trust management becomes an essential component of MP2P networks to promote peer transactions. However, in an MP2P network, peers frequently join and leave the network, which dynamically changes the network topology. Thus, it is difficult to establish long-term and effective trust relationships among peers. In this paper, we propose a dynamic grouping based trust model (DGTM) to classify peers. A group is formed according to the peers’ interests. Within a group, mobile peers share resources and tend to keep stable trust relationships. We propose three peer roles (super peers, relay peers, and ordinary peers) and two novel trust metrics (intragroup trust and intergroup trust). The two metrics are used to accurately measure the trust between two peers from the same group or from different groups. Simulations illustrate that our proposed DGTM always achieves the highest successful transaction rate and the best communication overhead under different circumstances.     

面向P2P特定信息的主动监测模型研究

针对传统的主动监测模型不能对P2P特定信息进行监测的问题,提出了一种面向P2P特定信息的主动监测模型。该模型的各个模块都以P2P特定信息为中心,对P2P特定信息传播网络进行监测,收集与P2P特定信息相关的节点列表及节点状态信息;创新性地将Peer Exchange（PEX）扩展消息用于主动测量模型,不但可以得到节点之间的连接关系,而且提高了主动监测效率。针对PEX扩展消息的引入,分析模型的各项性能指标。实验结果表明,在主动监测模型中引入PEX扩展消息技术,能够大幅度提高节点列表获取的效率和速度,并能够增加获取节点的覆盖率。     

基于Gnutella协议与划分技术的P2P网络模型的设计与实现*

Peer-to-Peer是一种很有发展潜力的网络技术,在对等计算、协同工作、搜索引擎、文件交换等领域有很好的应用前景。在传统的P2P网络模型中,网络上的所有主机不管它们所处的距离远近,它们的地位都是一样的,这在实际应用中却行不通。针对这种情况,在新的模型中将网络划分为不同的子网,子网内与子网外的主机分别对待。在子网内,采用IP多播技术自动定位主机节点;在子网外,则采用手工输入和自动发现相结合的方法来定位主机节点。在查询机制中,也对内部网络和外部网络采用了不同的查询方法并用Java实现了该模型。     

HAMS: Scalable peer-to-peer multimedia streaming model in heterogeneous networks

In a peer-to-peer (P2P) overlay network, a large number and various types of peer processes are interconnected in networks and are cooperating by using multimedia contents like movies and music. Here, multimedia contents are in nature distributed to peers in various ways like downloading and caching to the peers. Multimedia streaming is a key technology to realize multimedia applications in networks. In multimedia streaming applications, multimedia contents are required to be reliable and continuously delivered to processes in a real-time manner. Some contents peer may not send packets of a content at a required rate due to limited computation resource and a communication channel may not support enough Quality of Service (QoS) due to congestions and faults. Thus, P2P overlay networks are in nature heterogeneous. In this paper, we newly discuss a heterogeneous asynchronous multi-source streaming (HAMS) model where multiple contents peers transmit packets of a multimedia content to a requesting leaf peer to increase the throughput, reliability, and scalability in P2P overlay networks. Here, some pair of channels between contents and leaf peers may support different QoS. Peers may be faulty and some pair of contents peers may have different transmission rates. Finally, we show the HAMS model can support higher throughput and shorter transmission time than the other models in the evaluation.     

Counteracting free riding in Peer-to-Peer networks

The existence of a high degree of free riding is a serious threat to Peer-to-Peer (P2P) networks. In this paper, we propose a distributed framework to reduce the adverse effects of free riding on P2P networks. Our solution primarily focuses on locating free riders and taking actions against them. We propose a framework in which each peer monitors its neighbors, decides if they are free riders, and takes appropriate actions. Unlike other proposals against free riding, our framework does not require any permanent identification of peers or security infrastructures for maintaining a global reputation system. Our simulation results show that the framework can reduce the effects of free riding and can therefore increase the performance of a P2P network.     

A note on competitive diffusion through social networks

We introduce a game-theoretic model of diffusion of technologies, advertisements, or influence through a social network. The novelty in our model is that the players are interested parties outside the network. We study the relation between the diameter of the network and the existence of pure Nash equilibria in the game. In particular, we show that if the diameter is at most two then an equilibrium exists and can be found in polynomial time, whereas if the diameter is greater than two then an equilibrium is not guaranteed to exist.     

Predicting the level of cooperation in a Peer-to-Peer live streaming application

The Peer-to-Peer (P2P) architecture has been successfully used to reduce costs and increase the scalability of Internet live streaming systems. However, the effectiveness of these applications depends largely on user (peer) cooperation. In this article we use data collected from SopCast, a popular P2P live application, to show that there is high correlation between peer centrality—out-degree, out-closeness, and betweenness—in the P2P overlay graph and peer cooperation. We use this finding to propose a new regression-based model to predict peer cooperation from its past centrality. Our model takes only peer out-degrees as input, as out-degree has the strongest correlation with peer cooperation. Our evaluation shows that our model has good accuracy and does not need to be trained too often (e.g., once each 16 min). We also use our model to sketch a mechanism to detect malicious peers that report artificially inflated cooperation aiming at, for example, receiving better quality of service.     

An Eigentrust dynamic evolutionary model in P2P file-sharing systems

Many reputation systems have been proposed to distinguish malicious peers and to ensure the quality of the service in P2P file sharing systems. Most of those reputation systems implicitly assumed that normal peers are always altruistic and provide their resources unconditionally when requested. However, as independent decision makers in real networks, peers can be completely altruistic (always cooperative, ALLC), purely selfish (always defective, ALLD), or reciprocal (R). In addition, those systems do not provide an effective method to reduce free-riders in P2P networks. To address these two problems, in this paper, we propose an EigenTrust evolutionary game model based on the renowned EigenTrust reputation model. In our model, we use evolutionary game theory to model strategic peers and their transaction behaviors, which is close to the realistic scenario. Many experiments have been designed and performed to study the evolution of strategies and the emergence of cooperation under our proposed EigenTrust evolutionary model. The simulation results showed that rational users are inclined to cooperate (enthusiastically provide resources to other peers) even under some conditions in which malicious peers try to destroy the system.     

JXTA Overlay中节点自启动算法改进

在P2P网络中,新的节点通过连接入网点加入网络,在无法连接时,JXTA通过节点自启动策略连入网络,但目前的实现可能造成网络波动。通过改进自启动策略,充分利用边缘节点收集的集合点信息,并以PeerSim为基础进行了仿真,结果显示改进后的算法能很好的促进网络收敛,使网络快速达到稳定状态。     

Resolving the Topology Mismatch Problem in Unstructured Peer-to-Peer Networks

Prior studies show that more than 70 percent of communication paths in a popular unstructured peer-to-peer (P2P) system (i.e., Gnutella) do not exploit the physical network topology, leading to the topology mismatch problem, and thus, lengthen communication between participating peers. While previous efforts in solving overlay topology matching problems do not guarantee the bounds of performance metrics (e.g., the communication delay between any two overlay peers and the broadcasting scope of any participating peer), in this paper, we present a novel topology matching algorithm that has provable performance qualities. In our proposal, each participating node creates and manages a constant number of overlay connections to other peers in a distributed manner. In rigorous performance analysis, we show that 1) the expected overlay communication delay between any two nodes in our P2P network is a constant; 2) in addition, any joining node has the exponential broadcasting scope in expectation; 3) furthermore, a participating node takes a polylogarithmic overhead to exploit the physical network locality and maintain its flooding scope. Together with extensive simulations, we present our proposal that significantly outperforms two recent solutions, i.e., THANCS and mOverlay, in terms of overlay communication latency and/or broadcasting scope.     

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.