Fen He, Kimia Rezaei Kalantrai, A. Ebrahimnejad, H. Motameni
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引用次数: 2
Abstract
Software rejuvenation is an effective technique to counteract software aging in continuously-running application such as web service based systems. In client-server applications, where the server is intended to run perpetually, rejuvenation of the server process periodically during the server idle times increases the availability of that service. In these systems, web services are allocated based on the user’s requirements and server’s facilities. Since the selection of a service among candidates while maintaining the optimal quality of service is an Non-Deterministic Polynomial (NP)-hard problem, Meta-heuristics seems to be suitable. In this paper, we proposed dynamic software rejuvenation as a proactive fault-tolerance technique based on a combination of Cuckoo Search (CS) and Particle Swarm Optimization (PSO) algorithms called Computer Program Deviation Request (CPDR). Simulation results on Web Site Dream (WS-DREAM) dataset revealed that our strategy can decrease the failure rate of web services on average 38.6 percent in comparison with Genetic Algorithm (GA), Decision-Tree (DT) and Whale Optimization Algorithm (WOA) strategies.
软件再生是一种有效的技术,以防止软件老化的持续运行的应用程序,如基于web服务的系统。在客户机-服务器应用程序中,服务器打算永久运行,在服务器空闲期间定期恢复服务器进程可以提高该服务的可用性。在这些系统中,web服务是根据用户的需求和服务器的设施来分配的。由于在候选服务中选择服务同时保持最佳服务质量是一个非确定性多项式(NP)难题,因此元启发式似乎是合适的。本文提出了一种基于布谷鸟搜索(CS)和粒子群优化(PSO)算法的主动容错技术,即计算机程序偏差请求(CPDR)。在Web Site Dream (WS-DREAM)数据集上的仿真结果表明,与遗传算法(GA)、决策树(DT)和鲸鱼优化算法(WOA)策略相比,我们的策略可以将Web服务的故障率平均降低38.6%。