Resource management is an important issue in the cloud computing paradigm. The maximum Utilization of resources leads the service providers to get maximum profit. The suitable resources in the cloud data centre are needed to satisfy the user needs. The selection of the right resource is very essential in the data centre. Metaheuristic algorithms are used to perform the task allocation in the cloud computing environment. In this paper, a novel task allocation algorithm is proposed using Cat Swarm Optimization and BAT algorithm. BAT algorithm helps CSO algorithm to escape from a pre convergence issue. The proposed HGCSBAT algorithm results are evaluated and compared with the popular algorithms CSO and BAT algorithms. The HGCSBAT results are better than Genetic algorithm, Cat Swarm Optimization, and BAT algorithms in terms of availability and throughput.

资源管理是云计算范例中的重要问题。最大限度地利用资源可以使服务提供商获得最大的利润。需要云数据中心中的合适资源来满足用户需求。在数据中心中，选择正确的资源非常重要。元启发式算法用于在云计算环境中执行任务分配。本文提出了一种新的基于Cat Swarm Optimization和BAT算法的任务分配算法。BAT算法可帮助CSO算法摆脱预收敛问题。评估了所提出的HGCSBAT算法的结果，并将其与流行的算法CSO和BAT算法进行了比较。HGCSBAT结果优于遗传算法，Cat Swarm优化，