In this paper, we propose a novel HYBRID Bio-Inspired algorithm for task scheduling and resource management, since it plays an important role in the cloud computing environment. Conventional scheduling algorithms such as Round Robin, First Come First Serve, Ant Colony Optimization etc. have been widely used in many cloud computing systems. Cloud receives clients tasks in a rapid rate and allocation of resources to these tasks should be handled in an intelligent manner. In this proposed work, we allocate the tasks to the virtual machines in an efficient manner using Modified Particle Swarm Optimization algorithm and then allocation / management of resources (CPU and Memory), as demanded by the tasks, is handled by proposed HYBRID Bio-Inspired algorithm (Modified PSO + Modified CSO). Experimental results demonstrate that our proposed HYBRID algorithm outperforms peer research and benchmark algorithms (ACO, MPSO, CSO, RR and Exact algorithm based on branch-and-bound technique) in terms of efficient utilization of the cloud resources, improved reliability and reduced average response time.

中文翻译：

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一种用于云环境中调度和资源管理的混合仿生算法

在本文中，我们提出了一种新颖的 HYBRID Bio-Inspired 算法，用于任务调度和资源管理，因为它在云计算环境中发挥着重要作用。循环调度、先来先服务、蚁群优化等传统调度算法已广泛应用于许多云计算系统中。云以快速的速度接收客户任务，并应以智能方式处理这些任务的资源分配。在这项提议的工作中，我们使用改进的粒子群优化算法以有效的方式将任务分配给虚拟机，然后根据任务的要求分配/管理资源（CPU 和内存），由提议的 HYBRID Bio-Inspired 处理算法（修改的 PSO + 修改的 CSO）。