非结构化P2P系统的Gnutella模型研究

对等(P2P)计算是未来网络是P2P网络实现的最为关键的问题.以Gnutella为例,研究了非结构化P2P系统近年来的搜索优化技术.根据现代Gnutella网络的特点,提出了一种有助于改进非结构化P2P系统扩展性的搜索机制.     

聚集系数在对等网路由搜索算法中的应用

针对对等网搜索技术结构化拓扑中不支持复杂查询以及非结构化拓扑中搜索的可扩展性差等问题,该文提出一种新的搜索算法,将现有的对等网拓扑结构进行改良,让结点以flood方式与DHT方式结合起来进行信息搜索。该算法以域为基础,域内根据聚集度来提高对普通结点进行搜索的命中率,域间使用Chord协议来完成搜索。通过这样的结合提高搜索的效率以及响应的速度。实验结果验证了搜索算法的有效性。为进一步的研究提供了有力的理论分析基础。     

基于对等网络的全文信息检索

基于P2P方式的信息检索系统相对集中式信息检索系统具有成本低、可扩展性好、容错性强等优点，可充分挖掘网络边缘资源，并可提供个性化的信息服务．然而如何在纯P2P环境下实现全文检索并定位目标资源是困难的．当前，采用广播查询的非结构化P2P(如Gnutella)和采用分布式Hash表方式的结构化P2P(如CAN)都不能直接实现全文检索．针对这个问题，提出了基于质心法的结构化P2P全文检索方法，并建立模拟程序，对检索的性能与效果做了初步的验证．实验结果表明了该方法的有效性．     

一种基于蚁群算法的非结构化P2P网络搜索算法

在类似Gnutella的分散的非结构化P2P网络中，如何降低消息开销，提高搜索效率，是解决其扩展性问题的关键。引入蚁群算法的思想，提出一个非结构化P2P网络搜索算法。此算法利用蚂蚁留下信息素的正反馈机制，有效地指导搜索的方向，将查询消息包尽量发往目标可能存在的区域，从而减少冗余消息包的产生，得到更好的搜索输出。     

SSON：一种基于结构化P2P网络路由的语义覆盖网络结构

本文基于结构化P2P网络路由机制,采用基于主题划分的方法,提出了基于结构化P2P网络路由的语义覆盖网络SSON。SSON通过结构化P2P网络的标识符映射机制,根据资源类别将结点组织成层次化的覆盖网络,该覆盖网络结构确保搜索限制在与查询主题相关的局部结点子集中。该结构充分利用了结构化P2P网络的优点,解决了基于非结构化P2P网络建立的语义覆盖网络的对主题群的搜索低效问题,同时克服了结构化P2P网络仅支持精确匹配查找的缺点,为结构化P2P网络提供了可靠、高效的语义查询机制,极大地提高了查全率。     

主题重叠网络的构造与搜索算法研究

结构化P2P网络虽然具有扩展性良好的数据查找机制,但只支持基于键的准确匹配搜索.为提供更丰富的数据查询能力,本文提出一种基于主题重叠网络的结构化P2P搜索算法--主题重叠网络搜索算法(TONS).其基本思想是在结构化P2P网络之上,将结点按主题组织成分层的重叠网络,使含有相似主题的结点相互链接在一起;利用主题中继结点所具有的全局导航能力,TONS能够基于内容将查询限定在P2P网络的局部范围内,并且通过在重叠网络中随机添加一些长距离链接,使重叠网络具有Small-World特性,改善TONS的搜索性能.实验结果表明,TONS大大提高了搜索的查全率,减少了P2P网络信息搜索时的平均路径距离和平均消息数目.     

EIR：具有超级结点的非结构化P2P中多维数据搜索框架研究

在具有超级结点的非结构化P2P系统中，研究了复杂多维数据的查询搜索策略，提出了一个应用于具有超级结点的非结构化P2P网络的综合框架，在该框架中，能够实现对多维数据共享、索引以及查询等操作的处理。以R^＊-tree索引树为基础，提出了一种能够应用于P2P的扩展R^＊-tree索引树，即EIR-tree树，研究了系统中集群信息的收集与维护、EIR-tree树的构建与维护等方法和措施。     

一种基于蚁群算法的非结构化P2P网络搜索算法

在类似Gnutella的分散的非结构化P2P网络中,如何降低消息开销,提高搜索效率,是解决其扩展性问题的关键。引入蚁群算法的思想,提出一个非结构化P2P网络搜索算法。此算法利用蚂蚁留下信息素的正反馈机制,有效地指导搜索的方向,将查询消息包尽量发往目标可能存在的区域,从而减少冗余消息包的产生,得到更好的搜索输出。     

基于Gnutella协议的DDoS攻防方法研究

对Gnutella协议进行了分析,发现Gnutella协议Query-QueryHit查询回复机制的不安全性,而GnuteUa又是使用HttP作为其文件传输协议.本文分析了利用这两个特点来对非Gnutella结点(Web服务器)实施DDoS攻击的过程,提出了基于确认的安全列表算法来防范Gnutella结点被用来对Web服务器实施DDoS攻击.     

一种新的基于Flooding的资源发现机制

洪泛机制(Flooding)由于其简单性而被广泛应用于目前的非结构化P2P文件共享系统中,尽管它在内容搜索方面有很高的效率,但同时产生了大量的冗余消息,严重制约了网络的可扩展性。本文提出一种新的基于Flooding的资源发现机制,通过在本地结点维护兴趣簇、簇内结点索引等信息列表来改善Flooding机制的缺点。     

Associative search in peer to peer networks: Harnessing latent semantics

The success of a P2P file-sharing network highly depends on the scalability and versatility of its search mechanism. Two particularly desirable search features are scope (ability to find infrequent items) and support for partial-match queries (queries that contain typos or include a subset of keywords). While centralized-index architectures (such as Napster) can support both these features, existing decentralized architectures seem to support at most one: prevailing unstructured P2P protocols (such as Gnutella and FastTrack) deploy a “blind” search mechanism where the set of peers probed is unrelated to the query; thus they support partial-match queries but have limited scope. On the other extreme, the recently-proposed distributed hash tables (DHTs) such as CAN and CHORD, couple index location with the item’s hash value, and thus have good scope but can not effectively support partial-match queries. Another hurdle to DHTs deployment is their tight control of the overlay structure and the information (part of the index) each peer maintains, which makes them more sensitive to failures and frequent joins and disconnects.We develop a new class of decentralized P2P architectures. Our design is based on unstructured architectures such as Gnutella and FastTrack, and retains many of their appealing properties including support for partial match queries, and relative resilience to peer failures. Yet, we obtain orders of magnitude improvement in the efficiency of locating rare items. Our approach exploits associations inherent in human selections to steer the search process to peers that are more likely to have an answer to the query. We demonstrate the potential of associative search using models, analysis, and simulations.     

Assisted Peer-to-Peer Search with Partial Indexing

In the past few years, peer-to-peer (P2P) networks have become a promising paradigm for building a wide variety of distributed systems and applications. The most popular P2P application till today is file sharing, e.g., Gnutella, Kazza, etc. These systems are usually referred to as unstructured, and search in unstructured P2P networks usually involves flooding or random walking. On the other hand, in structured P2P networks (DHTs), search is usually performed by looking up a distributed inverted index. The efficiency of the search mechanism is the key to the scalability of a P2P content sharing system. So far, neither unstructured nor structured P2P networks alone can solve the search problem in a satisfactory way. In this paper, we propose to combine the strengths of both unstructured and structured P2P networks to achieve more efficient search. Specifically, we propose to enhance search in unstructured P2P overlay networks by building a partial index of shared data using a structured P2P network. The index maintains two types of information: the top interests of peers and globally unpopular data, both characterized by data properties. The proposed search protocol, assisted search with partial indexing, makes use of the index to improve search in three ways: first, the index assists peers to find other peers with similar interests and the unstructured search overlay is formed to reflect peer interests. Second, the index also provides search hints for those data difficult to locate by exploring peer interest locality, and these hints can be used for second-chance search. Third, the index helps to locate unpopular data items. Experiments based on a P2P file sharing trace show that the assisted search with a lightweight partial indexing service can significantly improve the success rate in locating data than Gnutella and a hit-rate-based protocol in unstructured P2P systems, while incurring low search latency and overheads.     

RDF-Chord: A hybrid PDMS for P2P systems

Peer-to-peer (P2P) computing has gained great attention in both research and industrial communities. Although many P2P systems, such as CAN, Pastry, Chord, and Tapstry have been proposed, they only support exact-match lookups. To overcome the limitation, a new area of P2P research, called peer data management system (PDMS), has emerged. In PDMS, metadata were used for annotating resources to support complex queries. This paper proposed a hybrid PDMS called RDF-Chord. In RDF-Chord, a set of keys is ingeniously designed to significantly reduce the search spaces. In experiments, it shows that RDF-Chord is highly scalable and efficient, especially in range queries.     

SELF-ORGANIZING PEER-TO-PEER SOCIAL NETWORKS

Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.     

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.     

基于代理节点的无结构对等网查询机制

在基于洪泛的无结构对等网中,尽管被查询文件的流行度不同,查询消息仍以同样的方式处理,从而产生大量不必要的消息.为了提高查询效率,该文提出一种基于代理节点的查询机制.一个查询消息被源节点转发给多个代理节点,它们连同源节点发起多个小洪泛.源节点通过调整小洪泛的数量控制查询过程.与Gnutella中的洪泛查询相比,新的查询机制在保持相似成功率的同时最多减少56%的带宽消耗,在保持相同命中数目的同时将响应时间缩短15%.     

Semantic partitioning of peer-to-peer search space

Peer-to-peer (P2P) networks are beginning to form the infrastructure of future applications. Computers are organized in P2P overlay networks to facilitate search queries with reasonable cost. So, scalability is a major aim in design of P2P networks. In this paper, to obtain a high factor of scalability, we partition network search space using a consistent static shared upper ontology. We name our approach semantic partition tree (SPT). All resources and queries are annotated using the upper ontology and queries are semantically routed in the overlay network. Also, each node indexes addresses of other nodes that possess contents expressible by the concept it maintains. So, our approach can be conceived as an ontology-based distributed hash table (DHT). Also, we introduce a lookup service for the network which is very scalable and independent of the network size and just depends on depth of the ontology tree. Further, we introduce a broadcast algorithm on the network. We present worst case analysis of both lookup and broadcast algorithms and measure their performance using simulation. The results show that our scheme is highly scalable and can be used in real P2P applications.     

A congestion-aware search protocol for heterogeneous peer-to-peer networks

Peer-to-Peer (P2P) file sharing is the hottest, fastest growing application on the Internet. When designing Gnutella-like applications, the most important consideration is the scalability problem, because P2P systems typically support millions of users online concurrently. Gnutella suffers from poor scaling due to its flooding-based search, resulting in excessive amounts of repeated query messages. Therefore, a good search protocol plays an important role in a system’s scalability. However, congestion, due to large query loads from users, definitely impacts on the performance of search protocols, and this consideration has received little attention from the research community. In this paper, we propose a congestion-aware search protocol for unstructured P2P networks. Our protocol consists of three parts—Congestion-Aware Forwarding, Random Early Stop and Emergency Signaling. The aim of our protocol is to integrate congestion control and object discovery functionality so that the search protocol can achieve good performance under congested networks and flash crowds. We perform extensive simulations to study our proposed protocol. The results show that our protocol can significantly reduce the hit delay while maintaining the high hit rate and also the congestion problems such as query loss and the peer overloading problem can be effectively alleviated.     

HPC5: An efficient topology generation mechanism for Gnutella networks

In this paper, we propose a completely distributed topology generation mechanism named HPC5 for Gnutella network. A Gnutella topology will be efficient and scalable if it generates less number of redundant queries. This can be achieved if it consists of a fewer number of short length cycles. Based on this principle, our protocol directs each peer to select neighbors in such a way that any cyclic path present in the overlay network will not generate any redundant query. We show that our approach can be deployed into the existing Gnutella network without disturbing any of its parameters. We also show that the probability of inconsistencies arising during topology generation, using our mechanism, which may lead to the formation of a small number of short length cycles is very low. However, we have also proposed an inconsistency handling protocol that detects such short length cycles and effectively removes them. We implemented a Gnutella prototype to compare and validate the efficiency of our protocol over existing Gnutella. Simulation results indicate that our mechanism outperforms existing Gnutella in terms of network coverage (the number of unique peers explored during query propagation in limited flooding) and message complexity. Structural analysis indicates that the proposed enhancement conserves the robustness of existing Gnutella network. Finally, we draw comparisons of the proposed protocol with a state-of-the-art topology optimization protocol named Distributed Cycle Minimization Protocol (DCMP); the simulation results indicate that HPC5 outperforms DCMP in terms of message overhead and network coverage.     

利用Gnutella网络的拓扑特性改进其可扩展性

分布式P2P网络Gnutella模型拓扑节点的分布不仅呈现典型的“幂规律”(PowerLaw),而且还具有明显的“小群体”(SmallWorld)特征。但是其对等机共享信息查询的搜索、定位路由协议仅使用“洪泛”算法,因此存在可扩展性问题。论文针对Gnutella网络拓扑节点具有的这些分布特性,提出了一种充分利用这些特性,基于“最大聚集度优先”的查询包路由改进策略,经模拟分析其协议的性能后证明,该策略能有效地提高Gnutella网络的可扩展性。