基于拥塞控制的非结构化P2P网络的路由负载均衡策略

非结构化P2P(unstructured peer-to-peer network)对等网络中的节点资源定位的路由查询是对等网络研究中的一个主要难题,特别是当网络中客户端节点由于其频繁加入、离开导致网络结构动态变化所带来的资源查询难题.提出了一种新的基于拥塞控制的路由查询方法来实现动态网络下的资源查询.该方法分两部分实现:首先是网络资源的分组与节点重连策略.该策略使得具有同等资源的节点相互连接,并周期性地调整节点上的节点连接数量以减少同组资源节点上的负载.通过以上策略,使得网络的拓扑结构自动地从随机网络结构进化到以资源组为单位的聚类网络,从而使得网络中形成网络资源组间的查询负载均衡.另一方面,组内的节点之间的路由负载均衡是通过节点间协同学习实现的.采用协同Q-学习方法,所研究的方法不仅从节点上学习其处理能力、连接数和资源的个数等参数,还将节点的拥塞状态作为协同Q-学习的重要参数,并建立模型.通过这种技术,同一组节点上的资源查询被有目的地引导,以避开那些组内拥塞的节点,从而最终实现资源组内节点之间的查询均衡.仿真实验结果表明,相比常用的random walk资源查找方法,该研究所实现的资源定位方法能够更迅速地实现网络的资源查询.仿真结果还表明,相比random walk方法,所提出的方法在网络高强度查询和网络节点动态加入和退出的情况下进行查询具有更高的鲁棒性和适应性.     

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。     

GridVine: An Infrastructure for Peer Information Management

GridVine is a semantic overlay infrastructure based on a peer-to-peer (P2P) access structure. Built following the principle of data independence, it separates a logical layer - in which data, schemas, and schema mappings are managed - from a physical layer consisting of a structured P2P network supporting decentralized indexing, key load-balancing, and efficient routing. The system is decentralized, yet fosters semantic interoperability through pair-wise schema mappings and query reformulation. GridVine's heterogeneous but semantically related information sources can be queried transparently using iterative query reformulation. The authors discuss a reference implementation of the system and several mechanisms for resolving queries collaboratively.     

基于语义覆盖网的P2P信息共享系统研究

现有P2P信息共享系统存在仅支持粗粒度、弱语义共享以及系统效率低等局限性,限制了其更大规模、更高层次的应用。基于资源相似节点通过信息聚类聚集在同一主题域,实现节点资源有序组织的思想,提出了一种基于语义覆盖网的P2P信息共享系统,建立由资源层、信息服务中心层、语义覆盖网络层和应用层四个层次组成的系统框架结构,并阐述了系统流程。分析表明,该系统有效优化了网络性能,可扩展性好,可以胜任不同的网络规模。     

Location awareness in unstructured peer-to-peer systems

Peer-to-peer (P2P) computing has emerged as a popular model aiming at further utilizing Internet information and resources. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a serious topology mismatch between the P2P overlay network and the physical underlying network. The topology mismatch problem brings great stress in the Internet infrastructure. It greatly limits the performance gain from various search or routing techniques. Meanwhile, due to the inefficient overlay topology, the flooding-based search mechanisms cause a large volume of unnecessary traffic. Aiming at alleviating the mismatching problem and reducing the unnecessary traffic, we propose a location-aware topology matching (LTM) technique. LTM builds an efficient overlay by disconnecting slow connections and choosing physically closer nodes as logical neighbors while still retaining the search scope and reducing response time for queries. LTM is scalable and completely distributed in the sense that it does not require any global knowledge of the whole overlay network. The effectiveness of LTM is demonstrated through simulation studies.     

一种基于分组的语义对等网络

以语义网络理论为基础,结合GCNET拓扑结构,提出一种基于分组的语义对等网络——Semantic GCNET,充分利用GCNET网络具有小世界特征的优点,确保其搜索限制在与查询主题相关的局部节点子集中,解决其他一些语义对等网络对主题群搜索低效的问题,克服一些语义对等网络仅支持精确匹配查找的缺点。实验结果表明,Semantic GCNET具有高效的语义查询性能和查全率。     

MANET adaptive structured P2P overlay

This paper presents an efficient structured P2P overlay over MANET which better matches to the physical network in term of routing. This feature is achieved by locally building up the minimum-spanning tree (MST) at each peer using the information of the peer’s logical neighbors which are either directly connected (1-hop) or 2-hops away. Using this interconnection structure among the peers, we design a new algorithm to distribute the contents information in the overlay by partitioning the identifier (ID) space among the peers. In this algorithm, each peer maintains a disjoint portion of the ID space. The ID space at a peer may be non-contiguous and each contiguous part is consecutive to the ID space of its directly connected neighbor peers. To route the file-lookup query, each peer builds up a binary search tree (BST) using the knowledge of the ID space of itself and of its directly connected neighbor peers. Simulation results show that our approach outperforms the existing approaches in term of routing overhead, average file-discovery delay, false-negative ratio and average path-stretch value.     

A scalable P2P platform for the knowledge grid

The knowledge grid needs to operate with a scalable platform to provide large-scale intelligent services. A key function of such a platform is to efficiently support various complex queries in a dynamic large-scale network environment. This paper proposes a platform to support index-based path queries by incorporating a semantic overlay with an underlying structured P2P network that provides object location and management services. Various distributed indexing structures can be dynamically formed by publishing, semantic objects as indexing nodes. Queries are forwarded along the chains of semantic object pointers to search for objects. We investigate the deployment of a scalable distributed trie index for broadcast queries on key strings, propose a decentralized load balancing method for solving the problem of uneven load distribution incurred by heterogeneity of loads and node capacities and by the distributed trie index, and give an approach for improving the availability of the semantic overlay and its trie index. Experiments demonstrate the scalability of the proposed platform.     

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.     

QUERY ROUTING IN A PEER-TO-PEER SEMANTIC LINK NETWORK

A semantic link peer-to-peer (P2P) network specifies and manages semantic relationships between peers' data schemas and can be used as the semantic layer of a scalable Knowledge Grid. The proposed approach consists of an automatic semantic link discovery method, a tool for building and maintaining P2P semantic link networks (P2PSLNs), a semantic-based peer similarity measurement for efficient query routing, and the schema mapping algorithms for query reformulation and heterogeneous data integration. The proposed approach has three important aspects. First, it uses semantic links to enrich the relationships between peers' data schemas. Second, it considers not only nodes but also the XML structure in measuring the similarity between schemas to efficiently and accurately forward queries to relevant peers. Third, it copes with semantic and structural heterogeneity and data inconsistency so that peers can exchange and translate heterogeneous information within a uniform view.     

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system,in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers.Such queries are based on local filter query statistics,and require as less communication cost as possible,which makes it more difficult than the existing distributed k-NN queries.Especially,we hope to reduce candidate peers and degrade communication cost.In this paper,we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries.Our approach is especially suitable for continuous k-NN queries when updating peers,including changing ranges of peers,dynamically leaving or joining peers,and updating data in a peer. In addition,simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR.)-based query approaches,especially for continuous queries.     

面向P2P文件共享应用的相似度计算模型

P2P文件共享应用逐渐成为互联网中的主流应用,它们都部署了各自的内容分发网络用于文件的发布与查找。基于内容分发网络,提出了一个节点间相似度计算模型。模型充分挖掘了节点拥有的文件的元信息,在进行相似度计算时将文件名、文件长度、文件类型按照不同的权重进行计算。将模型的求参问题形式化为一个有约束的最优化问题,并以eMule应用为例,对其模型参数进行了确定。相似度计算模型引入了节点的语义信息,可应用于改善内容分发网络的物理拓扑,从而提高其查询性能与路由性能。     

模式异构P2P网络中支持复杂查询的策略

结构化P2P重叠网络不能高效支持模式异构环境下的复杂查询,这限制了它在基于模式的P2P系统中的应用,使其在可扩展性和路由性能等方面的优势得不到充分利用.通过用关键字作为模式元素的索引键和垂直分区关系元组,设计了用结构化重叠网络索引模式和数据的方法,提出了在这两级索引上支持复杂查询处理的算法.定性分析和比较表明该方法较现有成果更接近P2P数据管理的理想目标.     

SSW: A Small-World-Based Overlay for Peer-to-Peer Search

Peer-to-peer (P2P) systems have become a popular platform for sharing and exchanging voluminous information among thousands or even millions of users. The massive amount of information shared in such systems mandates efficient semantic-based search instead of key-based search. The majority of existing proposals can only support simple key-based search rather than semantic-based search. This paper presents the design of an overlay network, namely, semantic small world (SSW), that facilitates efficient semantic-based search in P2P systems. SSW achieves the efficiency based on four ideas: 1) semantic clustering, where peers with similar semantics organize into peer clusters, 2) dimension reduction, where to address the high maintenance overhead associated with capturing high-dimensional data semantics in the overlay, peer clusters are adaptively mapped to a one-dimensional naming space, 3) small world network, where peer clusters form into a one-dimensional small world network, which is search efficient with low maintenance overhead, and 4) efficient search algorithms, where peers perform efficient semantic-based search, including approximate point query and range query in the proposed overlay. Extensive experiments using both synthetic data and real data demonstrate that SSW is superior to the state of the art on various aspects, including scalability, maintenance overhead, adaptivity to distribution of data and locality of interest, resilience to peer failures, load balancing, and efficiency in support of various types of queries on data objects with high dimensions.     

A new and effective hierarchical overlay structure for Peer-to-Peer networks

The tremendous growth of public interest in Peer-to-Peer (P2P) networks in recent years has initiated a lot of research work on how to design efficient overlay structures for P2P systems. Scalable overlay networks such as Chord, CAN, Pastry, and Tapestry provide no control over where data is stored and the location of the peers and resources is determined by the hash values of their identifiers and keys respectively. As a result, these overlays cannot support range queries and other proximity-aware complex queries directly.In this paper, we present a hierarchical P2P overlay network called SkipCluster, which is capable of supporting both exact-match and multi-dimensional range queries efficiently without consumption of extra memory space. SkipCluster is derived from skip graphs and SkipNet, but it has a two-tier hierarchical architecture.In both tiers, peers are connected in sequence according to the order of their peer IDs, and related resources are stored near each other without hashing of their resource keys. We design a novel data structure called Triple Linked List (TLL) to store each super-peer’s pointers in the higher tier, which can be used to find the longest prefix and speed up query routing of inter-cluster. In the lower tier, each intra-cluster peer’s routing table contains pointers with exponentially incremental distance. Experimental results show that SkipCluster can speed up both exact-match and range queries in different network sizes.     

LESSON: A system for lecture notes searching and sharing over Internet

In this paper, we present a system LESSON for lecture notes searching and sharing, which is dedicated to both instructors and students for effectively supporting their Web-based teaching and learning activities. The LESSON system employs a metasearch engine for lecture notes searching from Web and a peer-to-peer (P2P) overlay network for lecture notes sharing among the users. A metasearch engine provides an unified access to multiple existing component search engines and has better performance than general-purpose search engines. With the help of a P2P overlay network, all computers used by instructors and students can be connected into a virtual society over the Internet and communicate directly with each other for lecture notes sharing, without any centralized server and manipulation. In order to merge results from multiple component search engines into a single ranked list, we design the RSF strategy that takes rank, similarity and features of lecture notes into account. To implement query routing decision for effectively supporting lecture notes sharing, we propose a novel query routing mechanism. Experimental results indicate that the LESSON system has better performance in lecture notes searching from Web than some popular general-purpose search engines and some existing metasearch schemes; while processing queries within the system, it outperforms some typical routing methods. Concretely, it can achieve relatively high query hit rate with low bandwidth consumption in different types of network topologies.     

Building and Querying a P2P Virtual World

Peer-to-Peer (P2P) systems are known to provide excellent scalability in a networked environment. One peer is introduced to the system by each participant. However current P2P applications can only provide file sharing and other forms of relatively simple data communications, and, in this paper, we demonstrate how this limitation can be bridged by indexing and querying a 3D virtual-world on a dynamic distributed network. We present an algorithm for 3D range queries as well as an algorithm for nearest neighbor queries. We also show how to build such a complex application from the ground level of a P2P routing algorithm.     

A flabellate overlay network for multi-attribute search

Peer-to-peer (P2P) technology provides a popular way of distributing resources, sharing, and locating in a large-scale distributed environment. However, most of the current existing P2P systems only support queries over a single resource attribute, such as file name. The current multiple resource attribute search methods often encounter high maintenance cost and lack of resilience to the highly dynamic environment of P2P networks. In this paper, we propose a Flabellate overlAy Network (FAN), a scalable and structured underlying P2P overlay supporting resource queries over multi-dimensional attributes. In FAN, the resources are mapped into a multi-dimensional Cartesian space based on the consistent hash values of the resource attributes. The mapping space is divided into non-overlapping and continuous subspaces based on the peer’s distance. This paper presents strategies for managing the extended adjacent subspaces, which is crucial to network maintenance and resource search in FAN. The algorithms of a basic resource search and range query over FAN are also presented in this paper. To alleviate the load of the hot nodes, a virtual replica network (VRN) consisting of the nodes with the same replicates is proposed for replicating popular resources adaptively. The queries can be forwarded from the heavily loaded nodes to the lightly loaded ones through VRN. Theoretical analysis and experimental results show that FAN has a higher routing efficiency and lower network maintenance cost over the existing multi-attribute search methods. Also, VRN efficiently balances the network load and reduces the querying delay in FAN while invoking a relatively low overhead.     

An adaptive overlay network inspired by social behaviour

Nature is a great source of inspiration for scientists, because natural systems seem to be able to find the best way to solve a given problem by using simple and robust mechanisms. Studying complex natural systems, scientists usually find that simple local dynamics lead to sophisticated macroscopic structures and behaviour. It seems that some kind of local interaction rules naturally allow the system to auto-organize itself as an efficient and robust structure, which can easily solve different tasks. Examples of such complex systems are social networks, where a small set of basic interaction rules leads to a relatively robust and efficient communication structure. In this paper, we present PROSA, a semantic peer-to-peer (P2P) overlay network inspired by social dynamics. The way queries are forwarded and links among peers are established in PROSA resemble the way people ask other people for collaboration, help or information. Behaving as a social network of peers, PROSA naturally evolves to a small world, where all peers can be reached in a fast and efficient way. The underlying algorithm used for query forwarding, based only on local choices, is both reliable and effective: peers sharing similar resources are eventually connected with each other, allowing queries to be successfully answered in a really small amount of time. The resulting emergent structure can guarantee fast responses and good query recall.     

A self-similar super-peer overlay construction scheme for super large-scale P2P applications

Unstructured peer-to-peer (P2P) overlay networks with two-layer hierarchy, comprising an upper layer of super-peers and an underlying layer of ordinary peers, are used to improve the performance of large-scale P2P applications like content distribution and storage. In order to deal with continuous growth of participating peers, a scalable and efficient super-peer overlay topology is essential. However, there is relatively little research conducted on constructing such super-peer overlay topology. In the existed solutions, the number of connections required to be maintained by a super-peer is in direct proportion to the total number of super-peers. For super large-scale P2P applications, i.e. the number of participating peer is over 1,000,000, these solutions are not scalable and impractical. Therefore, in this paper, we propose a scalable hierarchical unstructured P2P system in which a self-similar square network graph (SSNG) is proposed to construct and maintain the super-peer overlay topology adaptively. The SSNG topology is a constant-degree topology in which each node maintains a constant number of neighbor nodes. Moreover, a simple and efficient message forwarding algorithm is presented to ensure each super-peer to receive just one flooding message. The analytical results showed that the proposed SSNG-based overlay is more scalable and efficient than the perfect difference graph (PDG)-based overlay proposed in the literature.