Enhanced Honey Badger Algorithm for Resource Allocation and Task Scheduling in Cloud Environment

Abstract

Cloud computing is a technology that offers dynamic resources to the users with enhanced scalability and flexibility. The major concerns in cloud environment that has direct impact on the throughput of cloud system and contentment of cloud users is the problem of task scheduling and resource allocation. The time taken to execute the tasks and cost incurred for the computation are the significant objectives that affect the performance of the cloud system. This work proposes a multiobjective task scheduling and resource allocation technique using metaheuristic optimization algorithm. Enhanced Honey Badger algorithm (EHBA) is employed to schedule the tasks and allocate computing resources effectively while minimizing the time and cost objectives. The performance of the proposed technique is assessed in a simulation environment, CloudSim, which mimics the settings of real cloud computing system. Various measures such as TimetoExecute, CosttoCompute, TasktoResource utilization and TimetoRespond are used to assess the performance of the suggested EHBA method for efficient task scheduling and resource allocation. The experimental results produced by the proposed method is also compared against the stateoftheart studies that employ metaheuristic optimization algorithms. The outcomes revealed that EHBA outperformed other methods by executing the tasks in a minimum time with reduced cost and maximum utilization of the computing resources. © 2023 IEEE.