PSON: A scalable P2P file sharing system with efficient complex query support

A desired P2P file sharing system is expected to achieve the following design goals: scalability, routing efficiency and complex query support. In this paper, we propose a powerful P2P file sharing system, PSON, which can satisfy all the three desired properties. PSON is essentially a semantic overlay network of logical nodes. Each logical node represents a cluster of peers that are close to each other. A powerful peer is selected in each cluster to support query routing on the overlay network while the less powerful peers are responsible for the maintenance of shared contents. To facilitate query routing, super peers are organized in form of a balanced binary search tree. By exploiting the concept of semantics, PSON can support complex queries in a scalable and efficient way. In this paper, we present the basic system design such as the semantic overlay construction, query routing and system dynamics. A load balancing scheme is proposed to further enhance the system performance. By simulation experiments, we show that PSON is scalable, efficient and is able to support complex queries.     

一种基于P2P的移动对象查询框架

近年来,时空数据查询方法的研究成为人们普遍关注的研究热点.但大部分研究主要集中在集中式环境,在分布式环境下对海量时空数据进行高效的轨迹查询和窗口查询是一件十分有意义且具有挑战性的工作.设计了一种基于P2P的解决方案,提出了对移动对象运动空间进行双层划分的方法来同时支持两种查询.应用网格过滤技术有效地解决了数据频繁更新的问题.对运动空间进行高效的划分,具有比空间填充曲线方法更好的负载平衡性,同时设计了高效的Overlay--SmartChord来支持窗口查询.实验结果表明,和现有方案相比所提方案可以有效减少更新通信量,负载平衡性和路由效率有显著提高.     

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。     

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.     

Approaching neighbor proximity and load balance for range query in P2P networks

We present a platform for building a range-queriable system. A distinguishing characteristic of the platform is that objects are not bound to any particular node. Rather, they can be freely moved between neighboring nodes to balance load as long as some ordering between objects in different nodes is respected. Decoupling the link between nodes and objects allows the overlay network to be constructed independently of object placement, focusing only on its own concerns, e.g. proximity and balanced load in routing. The main focus then is to present several heuristics for proximity-aware node joining to reduce communication costs in the platform. These heuristics are based on a novel process called hierarchical neighborhood search, which utilizes the overlay links to provide incoming nodes an overview of the network topology, thereby to guide them to find their neighborhood in the overlay. The experimental results show that some of the heuristics are very effective; they can reduce as much as 80% of the communication costs for neighboring nodes, and 40% overall.     

基于模式P2P系统复杂查询处理研究*

通过以关系名的同义关键字作为模式信息的索引键以及垂直分区关系元组,设计了用结构化重叠网络索引模式和数据的方法.基于这两级索引,提出了支持多属性复杂查询的算法.定性分析和比较表明,该方法比相关工作更接近P2P数据管理的理想目标.     

Zone indexing: Optimizing the balance between searching and indexing in a loosely structured overlay

While structured peer-to-peer systems are efficient in terms of overhead, they still lack the unstructured system’s flexibility and ability to support a wide range of complex queries. This paper examines systems supporting complex queries, deterministic operation, and a fair load distribution between nodes. The aim is to minimize the bandwidth and node load using an optimal level of indexing. The paper first theoretically examines the optimal balance of search and index messages using a search/index space model. This balance is fundamentally determined by the frequency of search requests and index updates. Based on this study, the paper proposes a novel loosely structured peer-to-peer system, Zone indexing, that can balance between index update traffic and search traffic in order to minimize the bandwidth overhead. Nodes are organized into a ring structure. The ring is divided into overlapping zones, within which index updates are distributed. We present an overlay maintenance algorithm with low-cost join and leave operations and a high churn resistance. We further propose a method to dynamically adjust the zone size in order to maintain optimal performance when the network size or user behavior changes. Additionally, we propose a method to limit the search delay by introducing parallel searching. The proposed solutions are evaluated mathematically and the analysis is verified with simulation.     

Main Memory Evaluation of Monitoring Queries Over Moving Objects

In this paper we evaluate several in-memory algorithms for efficient and scalable processing of continuous range queries over collections of moving objects. Constant updates to the index are avoided by query indexing. No constraints are imposed on the speed or path of moving objects or fraction of objects that move at any moment in time. We present a detailed analysis of a grid approach which shows the best results for both skewed and uniform data. A sorting based optimization is developed for significantly improving the cache hit-rate. Experimental evaluation establishes that indexing queries using the grid index yields orders of magnitude better performance than other index structures such as R*-trees.     

Efficient Processing of Continual Range Queries for Location-Aware Mobile Services

Efficient processing of continual range queries is important in providing location-aware mobile services. In this paper, we study a new main memory-based approach to indexing continual range queries to support location-aware mobile services. The query index is used to quickly answer the following question continually: “Which moving objects are currently located inside the boundaries of individual queries?” We present a covering tile-based (COVET) query index. A set of virtual tiles are predefined, each with a unique ID. One or more of the virtual tiles are used to strictly cover the region defined by an individual range query. The query ID is inserted into the ID lists associated with the covering tiles. These covering tiles touch each other only at the edges. A COVET index maintains a mapping between a covering tile and all the queries that contain that tile. For any object position, search is conducted indirectly via the covering tiles. More importantly, a COVET-based query index allows query evaluation to take advantage of incremental changes in object locations. Computation can be saved for those objects that have not moved outside the boundaries of covering tiles. Simulations are conducted to evaluate the effectiveness of the COVET index and compare virtual tiles of different shapes and sizes.     

A distributed resource discovery algorithm for P2P grids

Centralized or hierarchical administration of the classical grid resource discovery approaches is unable to efficiently manage the highly dynamic large-scale grid environments. Peer-to-peer (P2P) overlay represents a dynamic, scalable, and decentralized prospect of the grids. Structured P2P methods do not fully support the multi-attribute range queries and unstructured P2P resource discovery methods suffer from the network-wide broadcast storm problem. In this paper, a decentralized learning automata-based resource discovery algorithm is proposed for large-scale P2P grids. The proposed method supports the multi-attribute range queries and forwards the resource queries through the shortest path ending at the grid peers more likely having the requested resource. Several simulation experiments are conducted to show the efficiency of the proposed algorithm. Numerical results reveal the superiority of the proposed model over the other methods in terms of the average hop count, average hit ratio, and control message overhead.     

Popularity-aware prefetch in P2P range caching

Unstructured peer-to-peer infrastructure has been widely employed to support large-scale distributed applications. Many of these applications, such as location-based services and multimedia content distribution, require the support of range selection queries. Under the widely-adopted query shipping protocols, the cost of query processing is affected by the number of result copies or replicas in the system. Since range queries can return results that include poorly-replicated data items, the cost of these queries is usually dominated by the retrieval cost of these data items. In this work, we propose a popularity-aware prefetch-based approach that can effectively facilitate the caching of poorly-replicated data items that are potentially requested in subsequent range queries, resulting in substantial cost savings. We prove that the performance of retrieving poorly-replicated data items is guaranteed to improve under an increasing query load. Extensive experiments show that the overall range query processing cost decreases significantly under various query load settings.     

The Interspace: concept navigation across distributed communities

Within the next decade, computing technology will transform the Internet into the Interspace, an information infrastructure that supports semantic indexing and concept navigation across widely distributed community repositories. With the Interspace, the global information infrastructure will, for the first time, directly support interaction with abstraction. This infrastructure uses technologies that go beyond searching individual repositories to analyze and correlate knowledge across multiple sources and subjects. The Interspace will offer distributed services to transfer concepts across domains, just as Arpanet used distributed services to transfer files across machines and the Internet uses distributed services to transfer objects across repositories. The Community Architectures for Network Information Systems Laboratory has developed a working Interspace prototype that uses scalable technologies for concept extraction and navigation. They have successfully tested these technologies, which compute contextual frequency of document phrases within a community repository, on discipline-scale, real-world collections     

在P2P网络中构建支持语义搜索的覆盖网络DOverlay

P2P网络上构建支持复杂语义请求的覆盖网络是一个新的挑战.支持复杂语义的覆盖网络不仅要满足P2P网络的完全分布性、动态性、可扩展性等相关特性,还要尽量提高P2P网络的可靠性和低成本维护性.提出的非结构化领域覆盖网络DOverlay由于其资源特征是直接由其对应领域本体的概念树转换而来,因此资源可自动形成相关聚类.而基于DOverlay的资源搜索策略D_Search不仅在减少了网络开销的前提下增大了搜索成功率,而且在Dl_Search中设计的资源评级策略还大大增加了搜索的有效性.     

Query-driven indexing for scalable peer-to-peer text retrieval

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within a structured P2P network. Our indexing strategy is based on two important properties: (1) the generated distributed index stores posting lists for carefully chosen indexing term combinations that are frequently present in user queries, and (2) the posting lists containing too many document references are truncated to a bounded number of their top-ranked elements. These two properties guarantee acceptable latency and bandwidth requirements, essentially because the number of indexing term combinations remains scalable and the posting lists transmitted during retrieval never exceed a constant size. A novel index update mechanism efficiently handles adding of new documents to the document collection. Thus, the generated distributed index corresponds to a constantly evolving query-driven indexing structure that efficiently follows current information needs of the users and changes in the document collection.We show that the size of the index and the generated indexing/retrieval traffic remains manageable even for Web-size document collections at the price of a marginal loss in precision for rare queries. Our theoretical analysis and experimental results provide convincing evidence about the feasibility of the query-driven indexing strategy for large scale P2P text retrieval.     

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.     

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.     

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。     

Distributed processing of continuous sliding-window k-NN queries for data stream filtering

A sliding-window k-NN query (k-NN/w query) continuously monitors incoming data stream objects within a sliding window to identify k closest objects to a query. It enables effective filtering of data objects streaming in at high rates from potentially distributed sources, and offers means to control the rate of object insertions into result streams. Therefore k-NN/w processing systems may be regarded as one of the prospective solutions for the information overload problem in applications that require processing of structured data in real-time, such as the Sensor Web. Existing k-NN/w processing systems are mainly centralized and cannot cope with multiple data streams, where data sources are scattered over the Internet. In this paper, we propose a solution for distributed continuous k-NN/w processing of structured data from distributed streams. We define a k-NN/w processing model for such setting, and design a distributed k-NN/w processing system on top of the Content-Addressable Network (CAN) overlay. An extensive evaluation using both real and synthetic data sets demonstrates the feasibility of the proposed solution because it balances the load among the peers, while the messaging overhead within the P2P network remains reasonable. Moreover, our results clearly show the solution is scalable for an increasing number of queries and peers.     

Processing moving queries over moving objects using motion-adaptive indexes

This paper describes a motion-adaptive indexing scheme for efficient evaluation of moving continual queries (MCQs) over moving objects. It uses the concept of motion-sensitive bounding boxes (MSBs) to model moving objects and moving queries. These bounding boxes automatically adapt their sizes to the dynamic motion behaviors of individual objects. Instead of indexing frequently changing object positions, we index less frequently changing object and query MSBs, where updates to the bounding boxes are needed only when objects and queries move across the boundaries of their boxes. This helps decrease the number of updates to the indexes. More importantly, we use predictive query results to optimistically precalculate query results, decreasing the number of searches on the indexes. Motion-sensitive bounding boxes are used to incrementally update the predictive query results. Furthermore, we introduce the concepts of guaranteed safe radius and optimistic safe radius to extend our motion-adaptive indexing scheme to evaluating moving continual k-nearest neighbor (kNN) queries. Our experiments show that the proposed motion-adaptive indexing scheme is efficient for the evaluation of both moving continual range queries and moving continual kNN queries.