Optimal task allocation in hypercube multiprocessor ensembles

Criteria are established to determine the optimal policy for allocating a set of uniform tasks onto a multiprocessor hypercube ensemble. It is shown that the optimal policy depends on the ratio of computation to intertask communication required by the distributed program, and that based on this ratio, tasks should be placed either all on one processor or uniformly distributed over the largest possible hypercube.     

Model checker aided design of a controller for a wafer scanner

For a case-study of a wafer scanner from the semiconductor industry it is shown how model checking techniques can be used to compute (1) a simple yet optimal deadlock avoidance policy, and (2) an infinite schedule that optimizes throughput. in the absence of errors. Deadlock avoidance is studied based on a simple finite state model using Smv, and for throughput analysis a more detailed timed automaton model has been constructed and analyzed using the Uppaal tool. The Smv and Uppaal models are formally related through the notion of a stuttering bisimulation. The results were obtained within 2 weeks, which confirms once more that model checking techniques may help to improve the design process of realistic, industrial systems. Methodologically, the case study is interesting since two models were used to obtain results that could not have been obtained using only a single model. Supported by the European Community Project IST-2001-35304 (Ametist), http://ametist.cs.utwente.nl/.     

IC—V100电台锁相环频率合成器

本文从频率合成器的结构、功能入手,详细阐述了频率编程的原理及方法。     

On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.     

Assessing the relative priority of projects

Where there are a large number of projects competing for a limited pool of resources, projects have to be assigned priorities to determine which should proceed and which should be curtailed. The traditional economic procedures for assessing the relative priority of projects are reviewed, and alternative methods of ranking projects are suggested, with particular emphasis on methods that are inexpensive and easy to use.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

A branch-and-price algorithm to solve the molten iron allocation problem in iron and steel industry

The molten iron allocation problem (MIAP) is to allocate molten iron from blast furnaces to steel-making furnaces. The allocation needs to observe the release times of the molten iron defined by the draining plan of the blast furnaces and the transport time between the iron-making and steel-making stages. Time window constraints for processing the molten iron must be satisfied to avoid freezing. The objective is to find a schedule with minimum total weighted completion time. This objective reflects the practical consideration of improving steel-making efficiency and reducing operation cost caused by the need for reheating. Such a problem can be viewed as a parallel machine scheduling problem with time windows which is known to be NP-hard. In this paper, we first formulate the molten iron allocation problem as an integer programming model and then reformulate it as a set partitioning model by applying the Dantzig–Wolfe decomposition. We solve the problem using a column generation-based branch-and-price algorithm. Since the subproblem of column generation is still NP-hard, we propose a state-space relaxation-based dynamic programming algorithm for the subproblem. Computational experiments demonstrate that the proposed algorithm is capable of solving problems with up to 100 jobs to optimality within a reasonable computation time.     

Stability analysis of network-based cooperative resource allocation strategies

Resource allocation involves deciding how to divide a resource of limited availability among multiple demands in a way that optimizes current objectives. In this brief paper we focus on one type of distributed resource allocation problem where via an imperfect communication network multiple processors can share the load presented by multiple task types. We introduce asynchronous “cooperative” resource allocation strategies, and show that they lead to a bounded cumulative demand.     

利用计算机进行油气资源评价和勘探决策

本文着重介绍了构成《现代勘探决策理论系统》的5个主要计算机模块,即:生油岩热演化处理、求任意曲边形面积、数学模拟预测资源量、勘探经济评价分析及决策、辅助处理等模块。该系统曾在塔里木盆地和准噶尔盆地的油气资源评价和勘探决策中发挥了作用,受到了专家和用户的好评。