2951727
Adaptively Routing P2P Queries Using Association Analysis
Unstructured peer-to-peer networks have become a very popular method for content distribution in the past few years. By not enforcing strict rules on the network's topology or content location, such networks can be created quickly and easily. Unfortunately, because of the unstructured nature of these networks, in order to find content, query messages are flooded to nodes in the network, which results in a large amount of traffic. This work borrows the technique of association analysis from the data mining community and extends it to intelligently forward queries through the network. Because only a small subset of a node's neighbors are forwarded queries, the number of times those queries are propagated is also reduced, which results in considerably less network traffic. These savings enable the networks to scale to much larger sizes, which allows for more content to be shared and more redundancy to be added to the system, as well as allowing more users to take advantage of such networks
1003958
An Effective P2P Search Scheme to Exploit File Sharing Heterogeneity
Although the original intent of the peer-to-peer (P2P) concept is to treat each participant equally, heterogeneity widely exists in deployed P2P networks. Peers are different from each other in many aspects, such as bandwidth, CPU power, and storage capacity. Some approaches have been proposed to take advantage of the query forwarding heterogeneity such that the high bandwidth of powerful nodes can be fully utilized to maximize the system capacity. In this paper, we suggest using the query answering heterogeneity to directly improve the search efficiency of P2P networks. In our proposed differentiated search (DiffSearch) algorithm, the peers with high query answering capabilities will have higher priority to be queried. Because the query answering capabilities are extremely unbalanced among peers, a high query success rate can be achieved by querying only a small portion of a network. The search traffic is significantly reduced due to the shrunken search space. Our trace analysis and simulation show that the DiffSearch algorithm can save up to 60 percent of search traffic
28624321
Improving Event-to-Sink Throughput in Wireless Sensor Networks
Disaster relief is an important application of sensor networks, in which bursting data needs to be collected in a short period to the sink through a multi-hop wireless network. In general, packets containing the reported data have few correlations among each other, such that meaningful information can be inferred from partially received packets. For better understanding of monitored events, it is more important to capture the total number of unique reports rather than to reliably deliver each individual packet. Therefore, in the case of monitoring disaster filed with bursting data, communication channel throughput has higher priority than the channel reliability. Under this circumstance, we revisit the sensor network transport protocols, which use hop-by-hop recovery to provide reliable data transmission over unreliable links. We found that the complex recovery mechanism, while assuring high reliable individual packet delivery, reduces channel throughput when measured data is reported at high rate. To provide optimal data transport in a sensor network with bursting data generation, we propose a light weight sink centric transport protocol, which maximizes the channel throughput by minimizing the interference of packet recovery process. We implement the sink centric transport protocol in TinyOS and evaluate its performance in the TOSSIM simulator. The comparison shows that our proposed approach outperforms the hop-by-hop recovery approach in terms of event reporting throughput and transmission costs.
425294
A Decomposition-Based Probabilistic Framework for Estimating the Selectivity of XML Twig Queries
In this paper we present a novel approach for estimating the selectivity of XML twig queries. Such a technique is useful for answering approximate queries as well as for determining an optimal query plan for complex queries based on said estimates. Our approach relies on a summary structure that contains the occurrence statistics of small twigs. We rely on a novel probabilistic approach for decomposing larger twig queries into smaller ones. We then show how it can be used to estimate the selectivity of the larger query in conjunction with the summary information. We present and evaluate different strategies for decomposition and compare this work against a state-of-the-art selectivity estimation approach on synthetic and real datasets. The experimental results show that our proposed approach is very effective in estimating the selectivity of XML twig queries.
15593196
Real Time Sobel Square Edge Detector for Night Vision Analysis
Vision analysis with low or no illumination is gaining more and more attention recently, especially in the fields of security surveillance and medical diagnosis. In this paper, a real time sobel square edge detector is developed as a vision enhancer in order to render clear shapes of object in targeting scenes, allowing further analysis such as object or human detection, object or human tracking, human behavior recognition, and identification on abnormal scenes or activities. The method is optimized for real time applications and compared with existing edge detectors. Program codes are illustrated in the content and the results show that the proposed algorithm is promising to generate clear vision data with low noise.
33976422
Concurrent product/process design with multiple representations of parts
The need for concurrency in design and manufacturing is supported in a sheet metal design system by doing preliminary process design at the detail product design stage. This design with features approach represents the evolving part form to the designer in multiple process domains and at multiple stages of a sequential process. Each part of part form representations defines the conceptualized process which transforms it from one to the other. At this modeling level, processes are reversible so that design activity can take place in any of the domains and be transferred to the others. This concept is fully implemented in a sheet metal design/manufacturing system in which preliminary process design occurs concurrently with product design and the normal representation ambiguities of wireframe and flat panel models are eliminated.<<ETX>>
38065257
Tetrahedralization of Two Nested Convex Polyhedra
In this paper, we present an algorithm to tetrahedralize the region between two nested convex polyhedra without introducing Steiner points. The resulting tetrahedralization consists of linear number of tetrahedra. Thus, we answer the open problem raised by Chazelle and Shouraboura: "whether or not one can tetrahedralize the region between two nested convex polyhedra into linear number of tetrahedra, avoiding Steiner points?". Our algorithm runs in O((n+m)3 log(n+m)) time and produces 2(m+n-3) tetrahedra, where n and m are the numbers of the vertices in the two given polyhedra, respectively.
600527
Learning from BDDs in SAT-based bounded model checking
Bounded Model Checking (BMC) based on Boolean Satisfiability (SAT) procedures has recently gained popularity as an alternative to BDD-based model checking techniques for finding bugs in large designs. In this paper, we explore the use of learning from BDDs, where learned clauses generated by BDD-based analysis are added to the SAT solver, to supplement its other learning mechanisms. We propose several heuristics for guiding this process, aimed at increasing the usefulness of the learned clauses, while reducing the overheads. We demonstrate the effectiveness of our approach on several industrial designs, where BMC performance is improved and the design can be searched up to a greater depth by use of BDD-based learning.