基于双层ID空间的Peer-to-Peer文件系统设计与实现

提出并实现了一种建立在Peer-to-Peer搜索策略上的自组织,自适应,高效和可靠的文件系统DISPES（Double ID Space Based Peer-to-peer File System)。它在双层ID空间中构造虚拟存储节点,不仅有效地取得了文件系统的负载均衡,提高系统利用率,而且保证了动态环境中文件的可靠,快速获取,试验数据表明,DISPFS在系统接近满负荷运行和文件插入/删除操作频繁的双重压力下依然保持优良的性能。     

Efficient Skyline Computation in Structured Peer-to-Peer Systems

An increasing number of large-scale applications exploit peer-to-peer network architecture to provide highly scalable and flexible services. Among these applications, data management in peer-to-peer systems is one of the interesting domains. In this paper, we investigate the multidimensional skyline computation problem on a structured peer-to-peer network. In order to achieve low communication cost and quick response time, we utilize the iMinMax(theta ) method to transform high-dimensional data to one-dimensional value and distribute the data in a structured peer-to-peer network called BATON. Thereafter, we propose a progressive algorithm with adaptive filter technique for efficient skyline computation in this environment. We further discuss some optimization techniques for the algorithm, and summarize the key principles of our algorithm into a query routing protocol with detailed analysis. Finally, we conduct an extensive experimental evaluation to demonstrate the efficiency of our approach.     

Towards Progressive and Load Balancing Distributed Computation: A Case Study on Skyline Analysis

Many latest high performance distributed computational environments come with high bandwidth in communication. Such high bandwidth distributed systems provide unprecedented opportunities for analyzing huge datasets, but simultaneously posts new technical challenges. For users, progressive query answering is important. For utility of systems,load balancing is critical. How we can achieve progressive and load balancing distributed computation is an interesting and promising research direction. As skyline anal...     

Efficient Distributed Skyline Queries for Mobile Applications

In this paper, we consider skyline queries in a mobile and distributed environment, where data objects are distributed in some sites (database servers) which are interconnected through a high-speed wired network, and queries are issued by mobile units (laptop, cell phone, etc.) which access the data objects of database servers by wireless channels. The inherent properties of mobile computing environment such as mobility, limited wireless bandwidth, frequent disconnection, make skyline queries more complicated. We show how to efficiently perform distributed skyline queries in a mobile environment and propose a skyline query processing approach, called efficient distributed skyline based on mobile computing (EDS-MC). In EDS-MC, a distributed skyline query is decomposed into five processing phases and each phase is elaborately designed in order to reduce the network communication, network delay and query response time. We conduct extensive experiments in a simulated mobile database system, and the experimental results demonstrate the superiority of EDS-MC over other skyline query processing techniques on mobile computing.     

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.     

An efficient peer-to-peer indexing tree structure for multidimensional data

As one of the most important technologies for implementing large-scale distributed systems, peer-to-peer (P2P) computing has attracted much attention in both research and industrial communities, for its advantages such as high availability, high performance, and high flexibility to the dynamics of networks. However, multidimensional data indexing remains as a big challenge to P2P computing, because of the inefficiency in search and network maintenance caused by the complicated existing index structures, which greatly limits the scalability of applications and dimensionality of the data to be indexed.We propose SDI (Swift tree structure for multidimensional Data Indexing), a swift index scheme with a simple tree structure for multidimensional data indexing in large-scale distributed systems. While keeping the query efficiency in O(logN) in terms of routing hops, SDI has extremely low maintenance costs which is proved through theoretical analysis. Furthermore, SDI overcomes the root-bottleneck problem existing in most other tree-based distributed indexing systems. Extensive empirical study verifies the superiority of SDI in both query and maintenance performance.     

Multiple query scheduling for distributed semantic caches

In distributed query processing systems, load balancing plays an important role in maximizing system throughput. When queries can leverage cached intermediate results, improving the cache hit ratio becomes as important as load balancing in query scheduling, especially when dealing with computationally expensive queries. The scheduling policies must be designed to take into consideration the dynamic contents of the distributed caching infrastructure. In this paper, we propose and discuss several distributed query scheduling policies that directly consider the available cache contents by employing distributed multidimensional indexing structures and an exponential moving average approach to predicting cache contents. These approaches are shown to produce better query plans and faster query response times than traditional scheduling policies that do not predict dynamic contents in distributed caches. We experimentally demonstrate the utility of the scheduling policies using MQO, which is a distributed, Grid-enabled, multiple query processing middleware system we developed to optimize query processing for data analysis and visualization applications.     

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.     

Shared-nothing并行数据库系统查询优化技术

查询优化是并行数据库系统的核心技术。该文介绍作者自行研制的一个Ｓｈａｒｅｄ－ｎｏｔｈｉｎｇ并行数据库系统ＰＢＡＳＥ／２中独特的两阶段优化策略。为了缩减并行相称优化庞大的搜索空间,ＰＢＡＳＥ／２将并行查询优化划分为顺序优化和并行化两个在阶段。在顺序优化阶段对并行化后的通信代价进行预先估算,将通信开销加入顺序优化的代价模型,同时对动态规划搜索算法进行了修正和扩展,保证了顺序优化阶段得到的最小代价计划在     

基于SkipGraph的P2P覆盖网信任证链发现

提出一种基于skip图P2P覆盖网模型的分布式信任证存储和发现机制。为保证索引和发现效率,采用RT1^r语言作为信任证描述语言,其语义属性作为skip图中的索引关键字,构造了基于关键字前缀相似和支持范围查询的P2P覆盖网。通过试验评测和分析,该机制具有较高的查询效率和负载均衡机制。     

P2P环境中的skyline查询综述

随着数据规模的增长以及网络技术的发展,对等网络(P2P)作为一种分布式信息共享与搜索的平台引起了越来越广泛的关注。基于对等网络高度动态、高度分散、扩展性强等特点,P2P上的skyline计算方法不仅需要满足集中式skyline计算方法的各种要求,还需要考虑减小网络通讯量、减少平均节点访问数、保持负载平衡等。文中对这个发展领域的最新技术进行了研究,并且描述了分布式skyline方法的目的和主要原理,概括了适用于P2P环境中的现有方法,并进行了性能比较分析。最后,给出了P2P环境skyline计算的未来发展方向。     

Fast retrieval of high-dimensional feature vectors in P2P networks using compact peer data summaries

The retrieval facilities of most peer-to-peer (P2P) systems are limited to queries based on a unique identifier or a small set of keywords. The techniques used for this purpose are hardly applicable for content based image retrieval (CBIR) in a P2P network. Furthermore, we will argue that the curse of dimensionality and the high communication overhead prevent the adaptation of multidimensional search trees or fast sequential scan techniques for P2P CBIR. In the present paper we will propose two compact data representations that can be distributed in a P2P network and used as the basis for a source selection. This allows for communicating with only a small fraction of all peers during query processing without deteriorating the result quality significantly. We will also present experimental results confirming our approach.     

P2P空间矢量数据索引网络路由机制的研究与实现

随着地理信息系统的普及,越来越多的用户希望在线获取空间服务和空间数据。P2P技术为矢量地理数据的处理提供了充分的计算能力和服务能力,在P2PGIS系统中,索引网络的路由效率是主要问题之一。文中在已有的理论模型基础之上,采用结构化P2P网络协议Chord,扩展和修改JXTA路由协议规范,整合分布式哈希表（DHT）技术,实现了一个高效的、负载均衡的P2P空间矢量数据索引网络。实验结果表明,该索引网络比集中式索引网络具有更高的矢量数据传输效率。     

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.     

Optimized skyline queries on road networks using nearest neighbors

Skyline queries are used with data extensive applications, such as mobile location-based services, to support multi-criteria decision-making and to prune the data space by returning the most “interesting” data points. Most interesting data points are the points, which are not dominated by any other point. Spatial network skyline query is a subset of the skyline query problem where data points are nodes in a road network and the attributes of the data points are network distance relative to a set of query points. Spatial network skyline query’s problem is the need to calculate the attributes with an expensive distance calculation operation. Previous works (Deng et al. Proceedings of the 23th international conference on data engineering, 796–805, 2007), Sharifzadeh et al. Proceedings of the 32nd international conference on very large databases, 751–762, 2009) that addressed this problem involved extensive network distance calculation between the query points and data points. A new algorithm that requires a remarkably less number of network distance calculations is proposed in this work. Our approach uses a progressive nearest neighbor algorithm to minimize the set of candidates then evaluates those candidates by only comparing them to a subset of discovered skyline points. Experiments showed the effectiveness of our algorithm compared to previous works.     

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.     

数据广播环境下基于数据共享的位置相关skyline查询

数据广播环境下位置相关skyline查询是同时涉及空间位置属性和非空间多维属性的一类新的skyline查询类型,可广泛地应用于地理信息系统、城市规划、智能交通等领域。与传统环境下的位置相关skyline查询相比,数据广播环境下位置skyline查询面临一些新的问题,如广播信道的线性特性、移动设备资源受限性等。针对这些问题,本文提出了基于数据共享的位置相关查询算法,该方法通过共享邻近移动设备缓存的查询结果来改进查询算法的性能。广泛的实验结果显示,在移动设备密度较大的对等网络中,本文提出的算法具有较明显的优势,能显著地提升查询性能。     

分布式数据流查询处理的P2P中间件研究

随着Web的大规模应用,分布式数据流的数量迅速增长,其查询处理面临极大的挑战。该文开发了分布式数据流响应查询的P2P中间件原型,利用基于内容路由所提供的可扩展性、通信负载平衡及动态适应性等特性,能有效地处理相似查询,支持内积查询。模拟实验表明该索引机制能减少网络连接的计算资源,提高数据流查询处理效率。     

Continuous Skyline Queries for Moving Objects

The literature on skyline algorithms has so far dealt mainly with queries of static query points over static data sets. With the increasing number of mobile service applications and users, however, the need for continuous skyline query processing has become more pressing. A continuous skyline query involves not only static dimensions, but also the dynamic one. In this paper, we examine the spatiotemporal coherence of the problem and propose a continuous skyline query processing strategy for moving query points. First, we distinguish the data points that are permanently in the skyline and use them to derive a search bound. Second, we investigate the connection between the spatial positions of data points and their dominance relationship, which provides an indication of where to find changes in the skyline and how to maintain the skyline continuously. Based on the analysis, we propose a kinetic-based data structure and an efficient skyline query processing algorithm. We concisely analyze the space and time costs of the proposed method and conduct an extensive experiment to evaluate the method. To the best of our knowledge, this is the first work on continuous skyline query processing     

C-Chord：一种改进的Chord路由算法

Chord是一种典型的资源查找路由协议,具有负载均衡、可扩展性和灵活性等特点,广泛应用于P2P系统,但查找效率并不高。为了提高查找效率,提出了一种改进的多层次C—Chord路由算法,通过多层的集群结构组织,先优化路由表,然后改进资源查询过程,最后结合有效的维护机制,使查询效率得以提高。仿真实验表明,这种改进的Chord路由算法查询效率明显高于传统的Chord算法。而且C-Chord路由算法可以把传统的P2P系统扩展成适应大规模的分布式系统,网络的稳定性和健壮性更好。