A Novel Hybrid Optimization-Based Approach for Efficient Development of Business-Applications in Cloud

Soumia Zertal, M. Batouche, Zakaria Laboudi
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引用次数: 1

Abstract

The requests of the companies for the development and deployment of their business-applications in Cloud become more complex so that, sometimes, a one single service cannot carry out the target task on its own. Hence, a user-request is provided as a composite service. On another note, the number of available services is significantly increasing. Therefore, the authors would need to find the optimal cloud service-compositions that satisfy the quality of service values as well as user requirements. The methods proposed in literature for composing cloud services do not consider the composition and deployment constraints of candidate cloud services. This paper presents a novel optimization-based approach for building business-application in Cloud. The proposed approach combines the particle swarm optimization algorithm with some principles of ant colony optimization algorithm to deal with multiple QoS parameters, but also to satisfy the composition and deployment constraints of cloud services. The experimental results show the efficiency of the method for all tests instances.
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基于混合优化的云业务应用高效开发新方法
公司在云中开发和部署业务应用程序的请求变得更加复杂,以至于有时单个服务无法单独执行目标任务。因此,用户请求作为组合服务提供。另一方面,可用服务的数量正在显著增加。因此,作者需要找到满足服务质量价值和用户需求的最佳云服务组合。文献中提出的组合云服务的方法没有考虑候选云服务的组合和部署约束。本文提出了一种新的基于优化的云计算业务应用构建方法。该方法将粒子群优化算法与蚁群优化算法的一些原理相结合,既能处理多个QoS参数,又能满足云服务的组成和部署约束。实验结果表明,该方法对所有测试实例都是有效的。
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