PSO-COGENT: Cost and energy efficient scheduling in cloud environment with deadline constraint
PSO-COGENT: Cost and energy efficient scheduling in cloud environment with deadline constraint
复制标题
DOI：
10.1016/j.suscom.2018.06.002
复制
发表时间：
2018-09-01
影响因子：
4.5
通讯作者：
Sharma, S. C.
中科院分区：
文献类型：
--
作者：
Kumar, Mohit;Sharma, S. C.
云服务提供商的主要目标是最大化云基础设施的利润，而云用户则希望以最小的执行成本和时间来执行他们的应用程序。计算能力需求的快速增长引发了云数据中心的大量增长，云数据中心需要大量的能源消耗，对环境构成严重威胁。由于工作站（物理机）之间的不兼容和不可预测的用户需求，在云环境中降低能耗并获得最大利润是一个具有挑战性的问题。在本文中，我们提出了一种用于高效处理应用程序的资源分配模型和基于粒子群优化的调度（PSO）算法（称为PSO-COGENT算法），该算法不仅优化执行成本和时间，而且以期限为约束，还降低了云数据中心的能耗。所开发的PSO-COGENT算法已在cloudsim上进行了模拟，观察到与PSO、蜜蜂和min-min算法相比，它减少了执行时间、执行成本、任务拒绝率、能耗并增加了吞吐量。
The main goal of cloud service provider is to maximize the profit from cloud infrastructure, while cloud users want to execute their applications in minimum execution cost and time. The rapid growth in demand of computational power invites the massive growth in cloud data centers and requirement of large amount of energy consumption in cloud data centers, becomes a serious threat to the environment. To reduce the energy consumption and gain the maximum profit in cloud environment is a challenging problem due to incompatibility between workstation (physical machine) and unpredictable user demand. In this paper, we have proposed a resource allocation model for processing the applications efficiently and Particle Swarm Optimization based scheduling (PSO) algorithm named as PSO-COGENT algorithm that not only optimize execution cost and time but also reduces the energy consumption of cloud data centers, considering deadline as constraint. The developed PSO-COGENT algorithm has been simulated at cloudsim and observed that it reduces the execution time, execution cost, task rejection ratio, energy consumption and increase the throughput in comparison to PSO, honey bee and min-min algorithm.