132343
Approaching optimal peer-to-peer overlays
In unstructured peer-to-peer (P2P) systems, there exists a serious topology mismatch problem between physical and logical network. We first analyze the relationship between the property of the overlay and the corresponding message duplications incurred by queries in a given overlay, and prove that computing an optimal overlay with global knowledge is an NP-hard problem. Motivated by the analysis results, we design a distributed overlay optimization algorithm, THANCS, to attack topology mismatch. We demonstrate its performance by comprehensive simulations in dynamic environments. The proposed THANCS has three major strengths. First, it does not need any global knowledge. Second, its optimization convergent speed is fast. Third, it is orthogonal with other types of advanced search approaches.
9356286
A design of overlay anonymous multicast protocol
Multicast services are demanded by a variety of applications. Many applications require anonymity during their communication. However, there has been very little work on anonymous multicasting and such services are not available yet. Since there are fundamental differences between multicast and unicast, the solutions proposed for anonymity in unicast communications cannot be directly applied to multicast applications. In this paper, we define the anonymous multicast system, and propose a mutual anonymous multicast (MAM) protocol including the design of a unicast mutual anonymity protocol and construction and optimization of an anonymous multicast tree. MAM is self organizing and completely distributed. We define the attack model in an anonymous multicast system and analyze the anonymity degree. We also evaluate the performance of MAM by simulations
13965365
Distributed caching and adaptive search in multilayer P2P networks
To improve the scalability of Gnutella-like unstructured peer-to-peer (P2P) networks, a uniform index caching (UIC) mechanism was suggested in some earlier work. In UIC, query results are cached in all peers along the inverse query path such that the same query of other peers can be replied from their nearby-cached results. However, our experiments show that the UIC method causes a large amount of duplicated and unnecessary caching of items among neighboring peers. Aiming at improving the search efficiency, we propose a distributed caching mechanism, which distributes the cache results among neighboring peers. Furthermore, based on the distributed caching mechanism, an adaptive search approach is built which selectively forwards the query to the peers with a high probability of providing the desired cache results. All the enhancements above are defined in a protocol called distributed caching and adaptive search (DiCAS). In the DiCAS enhanced Gnutella network, all the peers are logically divided into multiple layers, with the character that all the peers in the same layer have the same group ID. The query flooding is restricted in one layer with the matched group ID. Our simulation study shows that, with the help of the index caching and search space division, the DiCAS protocol can significantly reduce the network search traffic in unstructured P2P systems without degrading query success rate.
6911930
LANDMARC: Indoor Location Sensing Using Active RFID
Growing convergence among mobile computing devices and embedded technology sparks the development and deployment of “context-aware” applications, where location is the most essential context. In this paper we present LANDMARC, a location sensing prototype system that uses Radio Frequency Identification (RFID) technology for locating objects inside buildings. The major advantage of LANDMARC is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that active RFID is a viable and cost-effective candidate for indoor location sensing. Although RFID is not designed for indoor location sensing, we point out three major features that should be added to make RFID technologies competitive in this new and growing market.
866017
Contour map matching for event detection in sensor networks
Many sensor network applications, such as object tracking and disaster monitoring, require effective techniques for event detection. In this paper, we propose a novel event detection mechanism based on matching the contour maps of in-network sensory data distribution. Our key observation is that events in sensor networks can be abstracted into spatio-temporal patterns of sensory data and that pattern matching can be done efficiently through contour map matching. Therefore, we propose simple SQL extensions to allow users to specify common types of events as patterns in contour maps and study energy-efficient techniques of contour map construction and maintenance for our pattern-based event detection. Our experiments with synthetic workloads derived from a real-world coal mine surveillance application validate the effectiveness and efficiency of our approach.
16439747
Improving unstructured peer-to-peer systems by adaptive connection establishment
In unstructured peer-to-peer (P2P) systems, the mechanism of a peer randomly joining and leaving a P2P network causes a topology mismatch between the P2P logical overlay network and the physical underlying network, incurring a large volume of redundant traffic in the Internet. In order to alleviate the topology mismatch problem, we propose adaptive connection establishment (ACE), an algorithm for building an overlay multicast tree among each source node and the peers within a certain diameter from the source peer and further optimizing the neighbor connections that are not on the tree while retaining the search scope. Our simulation study shows that this approach can effectively solve the mismatch problem and significantly reduce P2P traffic. We further study the trade-offs between the topology optimization rate and the information exchange overhead by changing the diameter used to build the tree.
16328925
An empirical evaluation of architectural alternatives for J2EE and Web services
Component-based technologies such as J2EE and .NET have been widely adopted to develop Web-based applications. With the emerging use of Web services and service-based architectures, such component technologies provide the necessary back-end components to execute application business logic, supporting a variety of architectural alternatives. The combination of component technologies with Web services further extends the set of architecture choices, with each providing different levels of performance. It is therefore important for an architect to understand these performance implications in the early stages of the architecture design. In this paper, we measure and analyze the performance of four alternative architectures using J2EE and Web services. The purpose is to investigate the effects on performance, identify both hardware and software bottlenecks, and analyze the architectural design trade-offs.
5878659
An optimization algorithm for free-form surface partitioning based on weighted gaussian image
Partitioning free-form surfaces into sub-patches and finding optimal representative normal for each patch to maximize a global objective function is an important two-level operation in diverse industrial applications. In this paper, by solving a maximum hemispherical partitioning problem raised from a weighted Gaussian image, an optimization algorithm is proposed to partition a free-form surface into two sub-patches and simultaneously report the optimal representative normals. By discretizing the free-form surface with W sample points and clustering normals on the surface with m distinct sample normals, the proposed algorithm is designed, in general, with O(m2W2) time complexity and O(W2) space complexity, and in particular, if the surface is convex, in O(m2 logm) time complexity. Case studies with four representative examples are presented and a real world application is exploited to demonstrate the effectiveness and usefulness of the proposed algorithm.
39241507
Feature selection using a proximity-index optimization model
Abstract One of the recurring issues in pattern recognition problems has been feature extraction and selection. This paper addresses this issue from a different pespective. Without assuming any particular classificaiton algorithm, it first suggests that one extract as much information as conveniently possible in several pattern-information domains. This paper later suggests applying the proposed Proximity-Index method, to select a significantly smaller, yet optimal feature subset. This method is formally described and is successfully applied to a waveform classification problem. The features selected by the algorithm are used to classify ten signal classes and produce a very encouraging recognition performance of 87.00% on 200 samples. This method is computationally inexpensive and particularly useful for large data set problems.
15492987
Automatic Accurate Time-Bound Analysis for High-Level Languages
This paper describes a general approach for automatic and accurate time-bound analysis. The approach consists of transformations for building time-bound functions in the presence of partially known input structures, symbolic evaluation of the time-bound function based on input parameters, optimizations to make the overall analysis efficient as well as accurate, and measurements of primitive parameters, all at the source-language level. We have implemented this approach and performed a number of experiments for analyzing Scheme programs. The measured worst-case times are closely bounded by the calculated bounds.
912445
Efficient Symbolic Detection of Global Properties in Distributed Systems
A new approach is presented for detecting whether a computation of an asynchronous distributed system satisfies Poss Φ (read “possibly Φ”), meaning the system could have passed through a global state satisfying property Φ. Previous general-purpose algorithms for this problem explicitly enumerate the set of global states through which the system could have passed during the computation. The new approach is to represent this set symbolically, in particular, using ordered binary decision diagrams. We describe an implementation of this approach, suitable for off-line detection of properties, and compare its performance to the enumeration-based algorithm of Alagar & Venkatesan. In typical cases, the new algorithm is significantly faster. We have measured over 400-fold speedup in some cases.