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Title:
bi-objective task assignment in heterogeneous distributed systems using honeybee mating optimization
Author: Kang Qinma ; He Hong ; Deng Rong
Source: Applied Mathematics and Computation
Issued Date: 2012
Pages: -
Indexed Type: ei
Department: (1) School of Information Engineering, Shandong University at Weihai, Weihai 264209, China; (2) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (3) School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
English Abstract: Effective task assignment is critical for achieving high performance in heterogeneous distributed computing systems. However, there is a possibility of processor and network failures and this can have an adverse impact on applications running on such systems. This paper proposes a new technique based on the honeybee mating optimization (HBMO) algorithm for static task assignment in the systems, which takes into account both minimizing the total execution and communication times and maximizing the system reliability simultaneously. The HBMO based approach combines the powers of simulated annealing, genetic algorithms, and an effective local search heuristic to search for the best possible solution to the problem under investigation within a reasonable computing time. We study the performance of the algorithm over a wide range of parameters such as the number of tasks, the number of processors, the ratio of average communication time to average computation time, and task interaction density of applications. The effectiveness and efficiency of our algorithm are manifested by comparing it with recently proposed algorithms from the literature. © 2012 Elsevier Inc. All rights reserved.
Language: 英语
WOS ID: WOS:000310504500021
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14737
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Kang Qinma,He Hong,Deng Rong. bi-objective task assignment in heterogeneous distributed systems using honeybee mating optimization[J]. Applied Mathematics and Computation,2012-01-01:-.
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