17947344
Enhancing Search Performance in Unstructured P2P Networks Based on Users' Common Interest
Peer-to-peer (P2P) networks establish loosely coupled application-level overlays on top of the Internet to facilitate efficient sharing of resources. They can be roughly classified as either structured or unstructured networks. Without stringent constraints over the network topology, unstructured P2P networks can be constructed very efficiently and are therefore considered suitable to the Internet environment. However, the random search strategies adopted by these networks usually perform poorly with a large network size. In this paper, we seek to enhance the search performance in unstructured P2P networks through exploiting users' common interest patterns captured within a probability-theoretic framework termed the user interest model (UIM). A search protocol and a routing table updating protocol are further proposed in order to expedite the search process through self organizing the P2P network into a small world. Both theoretical and experimental analyses are conducted and demonstrated the effectiveness and efficiency of our approach.
2378122
Self-organized manufacturing resource management: An ant-colony inspired approach
In a typical manufacturing system, jobs are released from a production planning stage to a shop floor, where they are allocated to resources like machines. An optimal or near optimal schedule is generally found for those jobs. In reality, the execution of this schedule is often interrupted by dynamic events like unexpected incoming new jobs, machine breakdowns, etc. A rapid recovery or a self-organized feature of the interrupted schedule is desirable for manufacturing resource management. This paper proposes an ant-colony inspired approach to recover the interrupted schedule through a self-organization mechanism. The experiments show that this mechanism significantly improves the quality of the recovered schedules.
14272859
Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown
The ant colony optimization (ACO) algorithm is a metaheuristic inspired from the behavior of foraging ants. Instead of exploring its ability in finding optimal solutions, the current study investigates another unique property - self-healing mechanism for resource allocation in a service-oriented environment where unexpected resource breakdown can occur. A system architecture is first proposed to detect, diagnose and react to disturbances. Then the performance of the ACO self-healing mechanism is tested and compared based on a modified benchmark problem. The experimental results show that the self-healing mechanism can promptly recover an obsolete schedule with high quality solutions.
8202363
Coordinated Services Provision in Peer-to-Peer Environments
In recent years, inspired by the emerging Web services standard and peer-to-peer technology, a new federated service providing (FSP) system paradigm has attracted increasing research interests. Many existing systems have either explicitly or implicitly followed this paradigm. Instead of exchanging files, peers in FSP systems share their computation resources in order to offer domain-specific services. In this paper, we focused on the coordination problem of how to self-organize the service group structures in response to the varying service demand. We presented our solution in the form of a coordination mechanism, which includes a labor-market model, a recruiting protocol, and a policy-driven decision architecture. Peers make their service providing decisions based on their local policies, which can be added, removed, or modified by users. A general methodology is introduced in this paper to facilitate policy design. Specifically, a heuristic inspired by the extremal optimization technique is utilized to handle potential inconsistencies among policies. A stimulus-response mechanism was further applied to make the decision process adjustable. Experiments under five application scenarios verified our ideas and demonstrated the effectiveness of our coordination mechanism.
3870686
An improved dead reckoning method for mobile robot with redundant odometry information
Dead reckoning is an important method for mobile robot. If its accuracy can be improved, navigation tasks will be simplified. The mobile robot concerned in this paper is with five wheels, in which there are dual driving wheels and a castor. A measurement wheel with encoder is fixed beside each driving wheel. There are two encoders fixed on the castor. One measures the castor's movement, and another indicates the angle of yawing. A new kind of kinematics equations derived from the robot's turning radius and angle of movement trajectory is presented. We can get a group of turning radius and angle from the data of four encoders, in which there are four different values for radius and six different values for angle. The estimated values of radius and angle can be gotten by fusion using fuzzy algorithm. The improved dead reckoning method has the advantages of simplicity, less computation cost, cheapness and good performance in uneven road. The simulation shows its effectiveness.
17872919
Extremal search of decision policies for scalable distributed applications
The ongoing trend of constructing open, scalable distributed systems such as peer-to-peer (P2P) systems demands for effective tools to manage the interactions between constituent entities (or nodes). One such tool is through imposing decision policies at the network level. However very few techniques are available to allow computers autonomously identify good policies with limited human intervention. In this paper, we propose an Extremal Programming (EP) algorithm to achieve automatic policy identification. The algorithm is inspired by recent advances in understanding far from equilibrium phenomena in terms of self-organized criticality (SOC). The effectiveness of EP is evaluated through a P2P application called location-aware video streaming (LAVS). The simulation studies in LAVS demonstrate that with EP, the fast and effective sharing of video streams is achieved.
12333144
Query Triggered Crawling Strategy: Build a Time Sensitive Vertical Search Engine
In today's information society, it is important to retrieve fresh information. Many of the vertical search results are valid to users in only a short period of time. But due to resource constraints, it is not possible to keep the entire local storage synchronized with the Web. We implemented a TSVS (time sensitive vertical search engine) prototype named Velocisaurus focused on time-critical airfare discount information search to investigate the time critical requirements of vertical search and proposed a QTC (query triggered crawling) strategy to coordinate the crawling systems by real-time user queries and solve this problem. Experiment shows that QTC driven crawlers significantly improves the freshness of the search results and utilizes the resources more efficiently compared to regular search engine crawlers..
5919440
MIME: A Dynamic Index Scheme for Multi-dimensional Query in Mobile P2P Networks
Nowadays, as the mobile services become widely used, there is a strong demand for mobile support in P2P search techniques. In this paper, we introduce a new cost model for searching multi-dimensional data in mobile P2P environment and propose a novel multi-dimensional MP2P search scheme MIME. MIME models the physical node layout in a two-dimensional plane and keeps records of the locations of the nodes to construct a proximity-aware P2P overlay. MIME also incorporates two adaptive features: an update algorithm that makes dynamic updates to the overlay, and a cache mechanism that reduces the load of data migration during the updates. Experiment results show that MIME achieves significant performance improvements in point/range queries compared to the conventional system.
5747087
Efficient Processing of Warping Time Series Join of Motion Capture Data
Discovering non-trivial matching subsequences from two time series is very useful in synthesizing novel time series. This can be applied to applications such as motion synthesis where smooth and natural motion sequences are often required to be generated from existing motion sequences. We first address this problem by defining it as a problem of l-e-join over two time series. Given two time series, the goal of l-e-join is to find those non-trivial matching subsequences by detecting maximal l-connections from the e-matching matrix of the two time series. Given a querying motion sequence, the l-e-join can be applied to retrieve all connectable motion sequences from a database of motion sequences. To support efficient l-e-join of time series, we propose a two-step filter-and-refine algorithm, called Warping Time Series Join (WTSJ) algorithm. The filtering step serves to prune those sparse regions of the e-matching matrix where there are no maximal l-connections without incurring costly computation. The refinement step serves to detect closed l-connections within regions that cannot be pruned by the filtering step. To speed up the computation of e-matching matrix, we propose a block-based time series summarization method, based on which the block-wise e-matching matrix is first computed. Lots of pairwise distance computation of elements can then be avoided by applying the filtering algorithm on the block-wise e-matching matrix.Extensive experiments on l-e-join of motion capture sequences are conducted. The results confirm the efficiency and effectiveness of our proposed algorithm in processing l-e-join of motion capture time series.
33357953
PISA: Federated Search in P2P Networks with Uncooperative Peers
Recently, federated search in P2P networks has received much attention. Most of the previous work assumed a cooperative environment where each peer can actively participate in information publishing and distributed document indexing. However, little work has addressed the problem of incorporating uncooperative peers, which do not publish their own corpus statistics, into a network. This paper presents a P2P-based federated search framework called PISA which incorporates uncooperative peers as well as the normal ones. In order to address the indexing needs for uncooperative peers, we propose a novel heuristic query-based sampling approach which can obtain high-quality resource descriptions from uncooperative peers at relatively low communication cost. We also propose an effective method called RISE to merge the results returned by uncooperative peers. Our experimental results indicate that PISA can provide quality search results, while utilizing the uncooperative peers at a low cost.
18254131
Bitmap Filtering: An Efficient Speedup Method for XML Structural Matching
With the proliferation of XML data on the internet, there is a large demand for efficient techniques in XML structural matching. We propose a novel filtering method, which is based on two auxiliary bitmaps named suffix bitmap and prefix bitmap, to accelerate XML structural matching. For each node in the XML document, the suffix bitmap captures in a compact format the tag name list of suffix subtree, and the prefix bitmap captures the tag name list of prefix path respectively. During the structural matching, most of unmatched node candidates can be filtered efficiently by comparing the respective bitmaps. We integrate the bitmap filtering into two categories of structural matching algorithms which are navigation-based algorithms and join-based algorithms. The experimental results demonstrate that the bitmap filtering can improve significantly the performance of XML structural matching.