一种基于小波分析的景象匹配算法研究

对于一些领域的景象匹配,传统的匹配算法已经无法满足要求.提出了一种基于小波分析分层搜索的景象匹配方法,它采用由粗到细的分层匹配方法,在每个层上采用不同的方法,并基于MATLAB实验平台对方法进行了仿真实验并与传统的匹配算法进行了比较.结果表明基于小波分析分层搜索的景象匹配方法较传统的匹配方法无论在速度上还是在精度上都具有明显的优势.提出的算法可以有效地改善传统匹配算法中的不足之处,在景象匹配领域,具有一定的可行性.     

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.     

集中式P2P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P2P环境下进行top-k查询是具有挑战性的.提出了一种在集中式P2P系统中的基于中心文档的层次化的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,将节点返回的结果录入到中心文档中,然后确定其分数上限,对节点进行选择,提高了查询效率.     

基于图连通支配集的子图匹配优化算法

在子图匹配过程中,随着图规模不断增长,匹配时间呈现指数爆炸的趋势.对此,提出一种基于图连通支配集的子图匹配优化算法VF-SMDS.根据贪心算法构建查询图的最小连通支配子图;通过代价模型计算最小连通支配子图节点的匹配代价,构建最优k查询节点匹配序列;通过支配节点的结构特征缩小查询节点搜索空间范围,在数据图中遍历到满足要求的节点,得到最终答案集.实验将VF-SMDS与GADDI、SPath、VF2++、VF3和SubISO方法进行对比.实验结果表明,在处理较大规模子图匹配问题时,VF-SMDS查询效率更高.     

非结构化对等计算系统中多维范围搜索

对等计算数据管理中的一个重要问题是如何有效地支持多维数据空间上的相似性搜索.现有的非结构化对等计算数据共享系统仅支持简单的查询处理方法,即匹配查询处理.将近似技术和路由索引结合在一起,设计了一种简单、有效的索引结构EVARI(扩展近似向量路由索引).利用EVARI,每个节点不仅可以在本地共享的数据集上处理范围查询,而且还可以将查询转发给最有希望获得查询结果的邻居节点.为了建立EVARI,每个节点使用空间划分技术概括本地的共享内容,并与邻居节点交换概要信息.而且,每个节点都可以重新配置自己的邻居节点,使得相关节点位置相互邻近,优化了系统资源配置,提升了系统性能.仿真实验证明了该方法的良好性能.     

有效的结构化P2P信息检索

在分析了以往P2P系统信息检索基础上,针对结构化P2P检索存在的问题,提出了一种有效的结构化P2P信息检索.结合利用向量空间模型(VSM)技术和位置敏感散列(LSH)技术,使得语义内容相似的文挡易于分布在相同的节点上,提高了搜索速度.同时采用了本体知识,增强对用户请求的语义理解,提高了搜索性能.     

一种快速的最小路径活动轮廓模型

本文提出了一种新颖的适用于轮廓提取的最小路径活动轮廓模型，该方法需要4个步骤：(1)用户通过交互界面在预提取的边界上或边界附近设置一些初始化的点。(2)在两个端点之间定义一个观测窗。(3)利用基于二次曲线的图形搜索法来寻找边缘。(4)“扭动”程序用来校正边缘，且可以降低对初始点选择的搜索敏感度。其中，后三个步骤是自动执行的。在此方法中，观测窗能系统地为以后的图形搜索提供新的节点连接。此方法不同于传统的图形搜索中的逐行或逐列法。此外，这种图形搜索法也提出了一种用于设计“扭动”程序的方法，此程序通过观测窗中产生的一些近似垂直于自身的置换矢量来达到优化轮廓线的目的。本文提出的最小路径活动轮廓模型加快了搜索速度，且减少了传统图形搜索法中频繁出现的“公制误差”，例如动态规划最小路径方法(DPMP)。     

基于关键字关联及节点兴趣的搜索机制

P2P节点用户的搜索内容在一定程度上体现了用户的兴趣.为此,提出一种基于关键字关联和节点兴趣的P2P信息搜索机制.该机制注重关键字之间关系的学习,通过用户操作发现节点兴趣.在搜索中利用关键字的语义关系增加命中目标,提高搜索成功率.根据节点兴趣缩小搜索范围、降低搜索开销.实验结果表明,采用快速建立索引表的方法和反馈机制能...     

一种大规模网络上的服务组合流程搜索方法

集中式的自动服务组合和非平凡服务发现能够根据给定的、具有特定输入输出的请求搜索出一系列满足要求的服务组合,是当前服务计算领域的研究热点.针对集中式结构带来的性能瓶颈和单点故障问题,提出了一种利用基于内容的分布式发布订阅技术实现大规模网络环境下的无中心自动服务组合方法,称之为流程搜索.基于内容的分布式发布订阅系统能够根据发布消息和订阅消息之间的内容匹配关系,将发布者提供的消息通过一系列中介节点转发给感兴趣的订阅者.它可以为服务接口之间的可互操作性判定以及查询路由提供支持.将服务模型映射为发布订阅的消息模型,并利用基于内容的路由设计形成分布式环境下的搜索算法,并基于PADRES系统开发了一个PreSee原型系统.模拟实验显示,无中心控制的方法相对于集中式的架构而言,可以有效降低系统延迟,提高整个系统的效率.     

P2P内容搜索的信息相似值计算方法

随着P2P网络的迅速发展,其用户数量不断增加,信息交互也越发频繁。为了降低内容搜索的复杂度和搜索时间,提出了一种以信息相似值为依据的计算方法。这种计算方法将无规则P2P网络中的节点按照节点的信息相似值划分为不同的域。在信息搜索时,将搜索的关键字与域头节点信息向量进行匹配,算法将整网搜索转化成域内或相邻域搜索,并根据用户兴趣值返回搜索结果。实验证明,这种信息相似值的计算方法在降低搜索时间的基础上,有较高的搜索命中率和查询准确率。     

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。     

P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic

P2P systems are very important for future distributed systems and applications. In such systems, the computational burden of the system can be distributed to peer nodes of the system. Therefore, in decentralized systems users become themselves actors by sharing, contributing and controlling the resources of the system. This characteristic makes P2P systems very interesting for the development of decentralized applications. Data replication techniques are commonplace in P2P systems. Data replication means storing copies of the same data at multiple peers thus improving availability and scalability. The trustworthiness of peers also is very important for safe communication in P2P system. The trustworthiness of a peer can be evaluated based on the reputation and actual behaviour of peers to provide services to other peers. In this paper, we propose two fuzzy-based systems for data replication and peer trustworthiness for JXTA-Overlay P2P platform. The simulation results have shown that in the first system, replication factor increases proportionally with increase of number of documents per peer, replication percentage and scale of replication per peer parameters and the second system can be used successfully to select the most reliable peer candidate to execute the tasks.     

基于超节点的Chord系统

Chord是一种比较成功的结构化P2P路由算法,但是网络节点性能的差异,影响了整个系统的效率;网络中一部分节点的频繁加入和退出所引起的系统震荡也影响了系统的性能;同时,结构化系统不提供相关节点的匿名性,也是结构化系统的一个不足之处.本文利用节点性能的差异,提出了基于超级节点的Chord路由算法,在Chord系统中形成节点簇,不但提高了系统的效率,而且能够有效地处理系统震荡问题,同时,为Chord系统提供了一定的匿名性.     

Adaptive approach to restraining content pollution in peer-to-peer networks

Peer-to-Peer (P2P) networks face the challenge of frequent pollution attacks. In such attacks, malicious peers pollute the network by sharing mislabeled, corrupt or infected content in an attempt to disrupt the system and waste network resources. When faced by such phenomenon, regular peers get discouraged from participating in the P2P network as they find less value in the system. In this work, we investigate the amount of resources required to restrain pollution attacks by means of content validation. We introduce multiple adaptive techniques that can minimize the spread of polluted content, while at the same time reduce the cost of content validation for peers participating in the network. Furthermore, the proposed pollution-restraint techniques are resistant to collusion from malicious peers, and they do not contribute to excessive communication overhead in the P2P network.     

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.     

Measurement and enhancement of BitTorrent-based video file swarming

BitTorrent, the most popular P2P file sharing application over the Internet, has also been widely used for video file distribution, albeit in a download-and-play mode. In this paper, we extensively examine the characteristics of BT swarms with different contents through a large-scale measurement. Our study especially focuses on the existing video file swarms, trying to understand the potentials and challenges of providing streaming service in BitTorrent. Our results from intra-swarm, inter-swarm and AS-level measurements demonstrate that the video file swarms in the BitTorrent system are quite different from the non-video swarms. In particular, the preference bias terminates the long-term relationship between peers and raises a significant challenge to develop BT based streaming service. Fortunately, we find that most peer sets in video file swarms are good enough to support streaming service. Strong relationship between video file swarms is also observed from the inter-swarm measurement. This inter-swarm relationship can provide extra peer information for video file swarms. Therefore, the organization of existing peer information could be the key to mitigate the preference bias. To this end, a hypercomplex based virtual channel mechanism is proposed. We find that, quaternions can provide efficient and meaningful approximation in the bitfield operations. Using quaternion based three space rotation, our approach can help peers to avoid preference bias during the data delivery. This is especially helpful at the beginning of the downloading since the peer only has few local pieces. More importantly, this mechanism is transparent and friendly to the existing BT swarms with both video and non-video contents.     

A comprehensive study of the use of advertisements as incentives in P2P streaming systems

P2P streaming systems, such as PPLive and PPStream, have become popular services with the widespread deployment of broadband networks. However, P2P streaming systems still face free-riding problems, similar to those that have been observed in P2P file sharing systems. Thus, one important problem in providing streaming services is that of providing appropriate incentives for peers to contribute their upload capacity. To this end, we propose the use of advertisements as an incentive for peers to contribute upload capacity. In the proposed framework, peers enjoy the same quality of streamed media, with the difference in quality of service being achieved through different amounts of advertisements viewed, based on the resource contributions to the system. Moreover, since calculating peers’ contributions accurately is important to successfully deploying such systems, we design a token-based framework to address this problem. An extensive simulation-based study is performed to evaluate the proposed approach. The results demonstrate that our approach provides appropriate incentives for peers to contribute their resources. Furthermore, we explore several characteristics of the token-based mechanism which can provide system developers with insight into efficient development of such systems.     

OAZE: A network-friendly distributed zapping system for peer-to-peer IPTV

IPTV systems attracting millions of users are now commonly deployed on peer-to-peer (P2P) infrastructures and provide an appealing alternative to multicast-based systems. Typically, a P2P overlay network is associated with each channel, composed of users who receive, watch and redistribute this channel. Yet, channel surfing (aka as zapping) involves switching overlays and may introduce delays, potentially hurting the user experience when compared to multicast-based IPTV. In this paper, we present a distributed system called OAZE (Overlay Augmentation for Zapping Experience) which speeds up the switching process and reduces the overall cross-domain traffic generated by the IPTV system. In OAZE, each peer maintains connections to other peers, not only in a given channel, but also in a subset of all channels to which the associated user is likely to zap. More specifically, we focus on the channel assignment problem, i.e. determining, in a given P2P overlay, the optimal distribution of the responsibility to maintain contact peers to other channels. We propose an approximate algorithm providing guaranteed performances, and a simpler and more practical one. Our experimental results show that OAZE leads to substantial improvements on the connections between peers, resulting in less switching delay and lower network cost; it then represents an appealing add-on for existing P2P IPTV systems.     

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.     

Reputation management algorithms for DHT-based peer-to-peer environment

This paper addresses the problem of integration of reputation management mechanisms into data look-up and routing processes to cope with some specific security problems in peer-to-peer (P2P) networks based on Distributed Hash Tables (DHT). The goal is to find a mode for “good” peers to cooperate in order to withstand malicious activity of single malevolent peers and their collusions as well.We start from consideration of individual instruments for reputation evaluation that every single peer should be provided with to autonomously define the level of its own trust towards others. We also propose a possible scenario of integration of some existing reputation management techniques and routing mechanisms in a P2P network based on the popular Kademlia algorithm. Then, we present an interaction algorithm that allows peers to obtain the global trust value for each single node through exchanging opinions in the form of local trust values independently calculated by every peer with other members of the community. Such collaboration between peers is indispensable to cope with malicious activity of inconsistent nature specific to DHT-based environment. To render the algorithm resilient to the presence of malicious participants we propose to apply solutions for Byzantine Agreement to exchange opinions among peers. We also provide mathematical evaluations concerning the complexity and computational costs of the proposed algorithm that evidence apparent improvements over the previous one.