NDLI: Improved simulated annealing algorithm for task allocation in real-time distributed systems

Content Provider	IEEE Xplore Digital Library
Author	Wenbo Wu Lin Li Xinyu Yao
Copyright Year	2014
Description	Author affiliation: State Key Lab. of Complex Electromagn. Environ. Effects on Electron. & Inf. Syst., Luoyang, China (Wenbo Wu; Lin Li) \|\| Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China (Xinyu Yao)
Abstract	This paper addresses the problem of task allocation in real-time distributed systems with the goal of maximizing the system reliability, it has been shown to be NP-hard. Many studies have been made to solve this problem without considering the real-time constraint. We first take account of the deadline constraint in order to formulate this problem, and then propose an improved simulated annealing algorithm call adaptive memory-based simulated annealing (AMSA) to solve the problem. The AMSA introduces adaptive factors to reduce the total computation time, and adds memory function to save the recently visited solutions and best solution by now. The effectiveness of AMSA is evaluated by comparing with traditional simulated annealing algorithm. The results show that AMSA can produce “good enough” solution in much less time.
Starting Page	50
Ending Page	54
File Size	528079
Page Count	5
File Format	PDF
ISBN	9781479952724
e-ISBN	9781479952748
DOI	10.1109/ICSPCC.2014.6986150
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Memory management Real-time Simulated annealing Task allocation Real-time systems Software reliability Distributed system Resource management Reliability Distributed computing
Content Type	Text
Resource Type	Article

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