Intelligent neighbor selection for efficient query routing in unstructured P2P networks using Q-learning

Applied Intelligence - Over the last two decades, peer-to-peer systems have proven their vital role in sharing various resources and services to diverse user communities over the internet. The...     

HD Tree: A novel data structure to support multi-dimensional range query for P2P networks

There are two basic concerns for supporting multi-dimensional range query in P2P overlay networks. The first is to preserve data locality in the process of data space partitioning, and the second is the maintenance of data locality among data ranges with an exponentially expanding and extending rate. The first problem has been well addressed by using recursive decomposition schemes, such as Quad-tree, K-d tree, Z-order, and Hilbert curve. On the other hand, the second problem has been recently identified by our novel data structure: HD Tree. In this paper, we explore how data locality can be easily maintained, and how range query can be efficiently supported in HD Tree. This is done by introducing two basic routing strategies: hierarchical routing and distributed routing. Although hierarchical routing can be applied to any two nodes in the P2P system, it generates high volume traffic toward nodes near the root, and has very limited options to cope with node failure. On the other hand, distributed routing concerns source and destination pairs only at the same depth, but traffic load is bound to some nodes at two neighboring depths, and multiple options can be found to redirect a routing request. Because HD Tree supports multiple routes between any two nodes in the P2P system, routing in HD Tree is very flexible; it can be designed for many purposes, like fault tolerance, or dynamic load balancing. Distributed routing oriented combined routing (DROCR) algorithm is one such routing strategy implemented so far. It is a hybrid algorithm combining advantages from both hierarchical routing and distributed routing. The experimental results show that DROCR algorithm achieves considerable performance gain over the equivalent tree routing at the highest depth examined. For supporting multi-dimensional range query, the experimental results indicate that the exponentially expanding and extending rate have been effectively controlled and minimized by HD Tree overlay structure and DROCR routing.     

基于结构化P2P网络的动态负载均衡算法研究

针对结构化P2P网络中可能出现的查找"热点"问题,结合基于DHT的P2P系统路由机制提出了ADLB(adaptive dy namic load balancing)算法,该算法充分利用原有Chord[4]协议的路由机制和P2P网络中各节点的异质性,通过动态控制节点加入来减轻重载节点的负载.此外还提出了一套动态监测控制节点负载的方法,最后通过性能仿真验证了算法的有效性.     

Voronoi-based reverse nearest neighbor query processing on spatial networks

The use of Voronoi diagram has traditionally been applied to computational geometry and multimedia problems. In this paper, we will show how Voronoi diagram can be applied to spatial query processing, and in particular to Reverse Nearest Neighbor (RNN) queries. Spatial and geographical query processing, in general, and RNN in particular, are becoming more important, as online maps are now widely available. In this paper, using the concept of Voronoi diagram, we classify RNN into four types depending on whether the query point and the interest objects are the generator points of the Voronoi Polygon or not. Our approach is based on manipulating Network Voronoi Diagram properties and applying a progressive incremental network expansion for finding the polygon inner network distances required to solve RNN queries. Our experimentation results show that our approaches have good response times in answering RNN queries.     

The biometric signature delegation scheme to balance the load of digital signing in hybrid P2P networks

Peer-to-Peer Networking and Applications - With the wide spread use of smart phones and high-speed networks, the demands for video contents are growing rapidly, for which broad bandwidth is needed....     

A popularity-based query scheme in P2P networks using adaptive gossip sampling

As P2P networks, such as many forms of social networking have been rapidly growing, numerous efforts have been made to improve the efficiency of the search operation especially in terms of response time and hit ratio. To this end, popularity-based schemes have recently attracted attention aimed at increasing search efficiency using content popularity ranking; however, these methods suffer from high cost and overhead, or inappropriate level of accuracy in specifying the popularity. In this paper, we propose an adaptive sampling scheme to make a tradeoff between cost and accuracy. This scheme relies on exchanging File Index Table (FIT) between peers in a local neighborhood using a Gossip Exchange Method (GEM). The proposed Hybrid Adaptive Search According to Gossip Exchange Method (HAS-A-GEM) is based on smart unstructured peer to peer overlays. We apply a hybrid overlay that efficiently combines topology-aware and interest-based links instead of random or DHT invoked connections. An analytical model as well as a simulation framework is developed to illustrate the performance of this scheme. The effectiveness of the proposed scheme is demonstrated under various conditions. Simulation results reveal that HAS-A-GEM performs well for large-scale networks, exploiting local content popularity when each local area contains enough number of peers.     

Hash-based proximity clustering for efficient load balancing in heterogeneous DHT networks

Distributed hash table (DHT) networks based on consistent hashing functions have an inherent load uneven distribution problem. The objective of DHT load balancing is to balance the workload of the network nodes in proportion to their capacity so as to eliminate traffic bottleneck. It is challenging because of the dynamism, proximity and heterogeneity natures of DHT networks and time-varying load characteristics.     

Implementing and evaluating phrasal query suggestions for proximity search

This paper describes and evaluates a unified approach to phrasal query suggestions in the context of a high-precision search engine. The search engine performs ranked extended-Boolean searches with the proximity operator near being the default operation. Suggestions are offered to the searcher when the length of the result list falls outside predefined bounds. If the list is too long, the engine specializes the query through the use of super phrases; if the list is too short, the engine generalizes the query through the use of proximal subphrases.We describe methods for generating both types of suggestions and present algorithms for ranking the suggestions. Specifically, we present the problem of counting proximal subphrases for specialization and the problem of counting unordered super phrases for generalization.The uptake of our approach was evaluated by analyzing search log data from before and after the suggestion feature was added to a commercial version of the search engine. We looked at approximately 1.5 million queries and found that, after they were added, suggestions represented nearly 30% of the total queries. Efficacy was evaluated through a controlled study of 24 participants performing nine searches using three different search engines. We found that the engine with phrasal query suggestions had better high-precision recall than both the same search engine without suggestions and a search engine with a similar interface but using an Okapi BM25 ranking algorithm.     

Dynamic storage and access load balancing for answering range queries in peer-to-peer networks

Recently, many applications have used Peer-to-Peer (P2P) systems to overcome the current problems with client/server systems such as non-scalability, high bandwidth requirement and single point of failure. In this paper, we propose an efficient scheme to support efficient range query processing over structured P2P systems, while balancing both the storage load and access load. The paper proposes a rotating token scheme to balance the storage load by placing joining nodes in appropriate locations in the identifier space to share loads with already overloaded nodes. Then, to support range queries, we utilize an order-preserving mapping function to map keys to nodes in order preserving way and without hashing. This may result in an access load imbalance due to non-uniform distribution of keys in the identifier space. Thus, we propose an adaptive replication scheme to relieve overloaded nodes by shedding some load on other nodes to balance the access load. We derive a formula for estimating the overhead of the proposed adaptive replication scheme. In this study, we carry simulation experiments with synthetic data to measure the performance of the proposed schemes. Our simulation experiments show significant gains in both storage load balancing and access load balancing.     

A dynamic load balancing scheme with incentive mechanism in heterogeneous structured P2P networks

Dynamic load imbalance is a basic and inherent problem in structured P2P networks. Most existing research suffers from the problems of inefficiency in globally managing the nodes’ load information and consumption of network bandwidth. This paper describes the mechanisms for collecting and globally managing the dynamic load of each node, and based on which to present a load balancing strategy which transfers the load from overloaded to under loaded nodes so as to improve load balancing efficiency. In order to encourage the rational and selfish nodes to actively participate in the load balancing process, we also propose an incentive mechanism in dynamic load balancing, by which the differentiated services could be provided for the nodes according to their load balancing abilities. The simulation results indicate that our approach could tackle the load imbalance problem in structured P2P networks effectively and efficiently in terms of the load distribution and the transferred load volume.     

一种基于位置信息的P2P路由算法

传统的Peeer-to-Peer（P2P）网络的研究已经基本上解决了分布式网络路由问题,为提高路由的效率,如何有效地缩短路由距离成为当前急需解决的热点.针对这一问题,在分析现有的路由算法的基础上,提出一种基于位置信息的P2P路由算法.算法中结合传统算法和节点所在区域位置的信息,使得网络节点在决定下一步跳转时,优先选择距离较近的节点,从而提高路由效率,减少路由延时.     

Continuous visible nearest neighbor query processing in spatial databases

In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of \({\langle p, R\rangle}\) tuples such that \({p \in P}\) is the nearest neighbor to every point r along the interval \({R \subseteq q}\) as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R due to the obstruction of some obstacles in O. In contrast to existing continuous nearest neighbor query, CVNN retrieval considers the impact of obstacles on visibility between objects, which is ignored by most of spatial queries. We formulate the problem, analyze its unique characteristics, and develop efficient algorithms for exact CVNN query processing. Our methods (1) utilize conventional data-partitioning indices (e.g., R-trees) on both P and O, (2) tackle the CVNN search by performing a single query for the entire query line segment, and (3) only access the data points and obstacles relevant to the final query result by employing a suite of effective pruning heuristics. In addition, several interesting variations of CVNN queries have been introduced, and they can be supported by our techniques, which further demonstrates the flexibility of the proposed algorithms. A comprehensive experimental evaluation using both real and synthetic data sets has been conducted to verify the effectiveness of our proposed pruning heuristics and the performance of our proposed algorithms.     

Efficient mutual nearest neighbor query processing for moving object trajectories

Given a set D of trajectories, a query object q, and a query time extent Γ, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D, the set of trajectories that are among the k₁ nearest neighbors (NNs) of q within Γ, and meanwhile, have q as one of their k₂ NNs. This type of queries is useful in many applications such as decision making, data mining, and pattern recognition, as it considers both the proximity of the trajectories to q and the proximity of q to the trajectories. In this paper, we first formalize MNN search and identify its characteristics, and then develop several algorithms for processing MNN queries efficiently. In particular, we investigate two classes of MNN queries, i.e., MNN_P and MNN_T queries, which are defined with respect to stationary query points and moving query trajectories, respectively. Our methods utilize the batch processing and reusing technology to reduce the I/O cost (i.e., number of node/page accesses) and CPU time significantly. In addition, we extend our techniques to tackle historical continuous MNN (HCMNN) search for moving object trajectories, which returns the mutual nearest neighbors of q (for a specified k₁ and k₂) at any time instance of Γ. Extensive experiments with real and synthetic datasets demonstrate the performance of our proposed algorithms in terms of efficiency and scalability.     

基于负载平衡因子的传感器网络路由算法研究

利用成簇算法延长无线传感器网络的生命周期是一个研究热点,而现有的分层路由成簇算法大多存在负载不均衡的问题.通过研究sLEACH(solar-awareLEACH)协议,分析负载不均衡的原因.提出了基于平衡负载因子优化算法(LBF),使用OMNET++进行仿真实验.结果表明,优化算法使簇头分布更合理,提高了负载均衡度,延长整个网络的工作寿命.     

Group formation with neighbor similarity trust in P2P E-commerce

The simplicity with which products and prices are compared in e-commerce has introduced an attractive option for many online merchants. The completion of online business transactions with personal information provisioning has always been an act that beckons hesitation. Most online traders are highly conscious of various threats and attacks such as credit card fraud, identity theft, spoofing, hacking, phishing, and other abuses, leading to low trust in online business transactions. Online transactions take place among Peer-to-Peer (P2P) systems at the edge of the Internet. Peer communities are often established dynamically with peers that are unrelated and unknown to each other. In our proposed mechanism, peers form groups in order to ensure trust and security. Each group is established based on interest among peers. In this paper, we show how peers form groups, and select group leaders. A peer can belong to more than one group. Comparing with some existing work, our work reveals that peers can have common neighbors which have a similarity based on their interest. Our simulation results show that the model can deal with the malicious attacks efficiently by comparison with existing models.     

Voronoi-based range and continuous range query processing in mobile databases

With the wide availability of mobile devices (smart phones, iPhones, etc.), mobile location-based queries are increasingly in demand. One of the most frequent queries is range search which returns objects of interest within a pre-defined area. Most of the existing methods are based on the road network expansion method – expanding all nodes (intersections and objects) and computing the distance of each node to the query point. Since road networks are extremely complex, node expansion approaches are inefficient. In this paper, we propose a method, Voronoi Range Search (VRS) based on the Voronoi diagram, to process range search queries efficiently and accurately by partitioning the road networks to some special polygons. Then we further propose Voronoi Continuous Range (VCR) to satisfy the requirement for continuous range search queries (moving queries) based on VRS. Our empirical experiments show that VRS and VCR surpass all their rivals for both static and moving queries.     

Fault-tolerant query processing in structured P2P-systems

Recently, a number of query processors has been proposed for the evaluation of relational queries in structured P2P systems. However, as these approaches do not consider peer or link failures, they cannot be deployed without extensions for real-world applications. We show that typical failures in structured P2P systems can have an unpredictable impact on the correctness of the result. In particular stateful operators that store intermediate results on peers, e.g., the distributed hash join, must protect such results against failures. Although many replication schemes for P2P systems exist, they cannot replicate operator states while the query is processed. In this paper we propose an in-query replication scheme which replicates the state of an operator among the neighbors of the processing peer. Our analytical evaluation shows that the network overhead of the in-query replication is in O(1) regarding network size, i.e., our scheme is scalable. We have carried out an extensive experimental evaluation using simulations as well as a PlanetLab deployment. It confirms the effectiveness and the efficiency of the in-query replication scheme and shows the effectiveness of the routing extension in networks of varying reliability.     

Correlation-aware partitioning for skewed range query optimization

World Wide Web - Data partitioning is an effective way to reduce cost and improve query performance in large-scale Web data analytical applications. State-of-the-art partitioning approaches on...     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.