1266771
Applying LVQ techniques to compress historical information in sensor networks
Summary form only given. In the emerging area of wireless sensor networks, a typical challenge is to retrieve historical information from the sensor nodes. We propose a new technique, called adaptive learning vector quantization (ALVQ), to compress this historical information. Our technique is based on the following two observations: (1) in sensor networks, the historical information exhibits similar patterns over time; and (2) different measurements are intrinsically correlated. Our algorithm works as follows: first, the codebook is obtained through a LVQ (learning vector quantization), which adjusts the codebook to be nearer to the optimal codebook. Second, ALVQ compresses the codebook update data pieces and transfers the compressed information to the base station. Using 2-level piece-wise regression, ALVQ can compress the updates with high precision while saving more bandwidth for data transmission in order to increase the quality of the approximation. In our experiments we used weather data to compare the performance of the ALVQ algorithm with the recently proposed SBR (self based regression) technique. Our experimental results demonstrate that the LVQ learning process significantly improves the quality of the codebook, thus increasing the regression precision. In addition the use of two-level regression for transmitting the codebook updates further minimizes the required bandwidth. Overall the ALVQ technique can achieve the same precision with SBR while using 75% of the bandwidth.
1538276
Distributed spatio-temporal similarity search
In this paper we introduce the distributed spatio-temporal similarity search problem: given a query trajectory Q, we want to find the trajectories that follow a motion similar to Q, when each of the target trajectories is segmented across a number of distributed nodes. We propose two novel algorithms, UB-K and UBLB-K, which combine local computations of lower and upper bounds on the matching between the distributed subsequences and Q. Such an operation generates the desired result without pulling together all the distributed subsequences over the fundamentally expensive communication medium. Our solutions find applications in a wide array of domains, such as cellular networks, wild life monitoring and video surveillance. Our experimental evaluation using realistic data demonstrates that our framework is both efficient and robust to a variety of conditions.
8641285
A data compression technique for sensor networks with dynamic bandwidth allocation
In this paper, we have presented a new data compression technique, designed for historical information compression in sensor networks. Our method employs the LVQ learning process to construct the codebook and the codebook's updates are compressed to save bandwidth for sensor data transmission. In addition, we have addressed the dynamic bandwidth allocation problem in sensor networks. Our DBA algorithm can dynamically adjust the communication bandwidth of different sensors in order to balance data compression qualities at different sensors.
16179
Efficient indexing data structures for flash-based sensor devices
Flash memory is the most prevalent storage medium found on modern wireless sensor devices (WSDs). In this article we present two external memory index structures for the efficient retrieval of records stored on the local flash memory of a WSD. Our index structures, MicroHash and MicroGF (micro grid files), exploit the asymmetric read/write and wear characteristics of flash memory in order to offer high-performance indexing and searching capabilities in the presence of a low-energy budget, which is typical for the devices under discussion. Both structures organize data and index pages on the flash media using a sorted by timestamp file organization. A key idea behind these index structures is that expensive random access deletions are completely eliminated. MicroHash enables equality searches by value in constant time and equality searches by timestamp in logarithmic time at a small cost of storing index pages on the flash media. Similarly, MicroGF enables spatial equality and proximity searches in constant time. We have implemented these index structures in nesC, the programming language of the TinyOS operating system. Our trace-driven experimentation with several real datasets reveals that our index structures offer excellent search performance at a small cost of constructing and maintaining the index.
31903182
The Fourier slice theorem for range data reconstruction
Abstract This paper proposes a new approach to resolve the ambiguity problem in multistriping laser triangulation systems [1] . The application of this new method to circularly symmetrical objects can achieve time and space complexity of order one. No optical shutter is required in this new method. The new solution is based on the Fourier slice theorem, which forms the basis of X-ray CT (computed tomography) reconstruction. This paper demonstrates how this theorem can also be used to resolve multistripe laser ambiguity effectively.
22001959
A Pinwheel Scheduler for Three Distinct Numbers with a Tight Schedulability Bound
Abstract. Given a multiset of positive integers 
 $A=\{a_1,a_2,\ldots,a_n\}$ , the pinwheel problem is to find an infinite sequence over 
 $\{1,2,\ldots,n\}$ such that there is at least one symbol i within any subsequence of length ai. The density of A is defined as 
 $\rho(A)=\sum^n_{i=1} (1/a_i)$ . In this paper we limit ourselves to instances composed of three distinct integers. The best scheduler [5] published previously can schedule all instances with a density of less than 0.77. A new and fast scheduling scheme based on spectrum partitioning is presented in this paper which improves the 0.77 result to a new 
 $\frac{5}{6}\approx 0.83$ density threshold. This scheduler has achieved the tight schedulability bound of this problem.
1475764
An Extendible Hash for Multi-Precision Similarity Querying of Image Databases
We propose multi-precision similarity matching where the image is divided into a number of subblocks, each with its associated color histogram. We present experimental results showing that the spatial distribution information recorded by multiprecision color histograms helps to make similarity matching more precise. We also show that sub-image queries are much better supported with multi-precision color histograms. To minimize the overhead, we employ a filtering scheme based on the 3-dimensional average color vectors. We provide a formal result proving that filtering with multi-precision color histograms is complete. Finally, we develop a novel extendible hashing structure for indexing the average color vectors. We give experimental results showing that the proposed structure significantly outperforms the SR-tree.
15193012
Unsupervised link discovery in multi-relational data via rarity analysis
A significant portion of knowledge discovery and data mining research focuses on finding patterns of interest in data. Once a pattern is found, it can be used to recognize satisfying instances. The new area of link discovery requires a complementary approach, since patterns of interest might not yet be known or might have too few examples to be learnable. We present an unsupervised link discovery method aimed at discovering unusual, interestingly linked entities in multi-relational datasets. Various notions of rarity are introduced to measure the "interestingness" of sets of paths and entities. These measurements have been implemented and applied to a real-world bibliographic dataset where they give very promising results.
746230
Designing the Market Game for a Trading Agent Competition
The authors discuss the design and operation of a trading agent competition, focusing on the game structure and some of the key technical issues in running and playing the game. They also describe the competition's genesis, its technical infrastructure, and its organization. The article by A. Greenwald and P. Stone (2001), describes the competition from a participant's perspective and describes the strategies of some of the top-placing agents. A visualization of the competition and a description of the preliminary and final rounds of the TAC are available in IC Online (http://computer.org/internet/tac.htm).