42167729
Computation of chain queries in distributed database systems
215965918
A Parallel Scheme Using the Divide-and-Conquer Method
A parallel scheme using the divide-and-conquer method is developed. This partitions the input set of a problem into subsets, computes a partial result from each subset, and finally employs a mergin...
2850409
A Framework for Automatic Problem Decomposition in Planning
An intelligent problem solver must be able to decompose a complex problem into simpler parts. A decomposition algorithm would not only be beneficial for traditional subgoal-oriented planning systems but also support distributed, multi-agent planners. In this paper, we present an algorithm for automatic problem decomposition. Given a domain description with a number of objects to be manipulated, our method constructs subspaces complete with subproblem descriptions and operators, and solves the subproblems concurrently. The solutions in individual subspaces are combined using a constraint satisfaction algorithm. The effectiveness of the approach is guaranteed by our careful analysis of the interactions among different subspaces. The results presented in this paper support parallel, distributed and multi-agent planning systems.
40082925
Analysis of Packet-Switched Multiple-Bus Multiprocessor Systems
Performance analyses of packet-switched multiple-bus multiprocessor systems are presented. Approximate queuing network models are developed for both synchronous and asynchronous control schemes, and the results are shown to be in good agreement with simulation results. The analysis of the synchronous system is based on a decomposition technique, with each of the shared resources in the system being represented as a single-server queue. For asynchronous systems, the analysis is based on the flow equivalence technique. Numerical results obtained from the analyses indicate that packet-switched multiple-bus multiprocessors with only a few buses perform almost as well as crossbar-based multiprocessors. >
5241796
Finding Biclusters by Random Projections
Given a matrix X composed of symbols, a bicluster is a submatrix of X obtained by removing some of the rows and some of the columns of X in such a way that each row of what is left reads the same string. In this paper, we are concerned with the problem of finding the bicluster with the largest area in a large matrix X. The problem is first proved to be NP-complete. We present a fast and efficient randomized algorithm that discovers the largest bicluster by random projections. A detailed probabilistic analysis of the algorithm and an asymptotic study of the statistical significance of the solutions are given. We report results of extensive simulations on synthetic data.
13076928
Coverage Algorithm and Protocol in Heterogeneous Sensor Networks
One fundamental issue in wireless sensor networks is the coverage problem. In heterogeneous sensor networks composed of different types of sensors, the difference of the sensing radius of nodes augments the computation difficulty of coverage degree. In this paper, we analyze the features of heterogeneous sensor networks and discuss the approaches to guarantee and calculate the coverage degree of the region deployed by heterogeneous sensor networks. Based on our analysis, a Distributed Coverage Optimization Algorithm by which each node in the network can determine whether it should be turn active/inactive is proposed. Simulation shows that our algorithm can make the extraneous nodes inactive and minimize the number of nodes need to remain active.
219267
Planning with Primary Effects: Experiments and Analysis
The use of primary effects in planning is an effective approach to reducing search. The underlying idea of this approach is to select certain "important" effects among the effects of each operator and to use an operator only for achieving its important effects. In the past, there has been little analysis of planning with primary effects and few experimental results We provide empirical and analytical results on the use of primary effects First, we experimentally demonstrate that the use of primary effects may lead to an exponential reduction of the planning time. Second, we analytically ex plain the experimental results and identify the factors that influence the efficiency of planning with primary effects. Third we describe an application of our analysis to predicting the performance of a planner for a given selection of primary effects.