Bi-Objective Task Scheduling Based on Heuristic Initialization of the Jellyfish Search Algorithm in Cloud Computing

In the computing cloud environment, task scheduling is the most important feature affecting system performance, and its improvement can contribute to achieving user satisfaction. There are many strategies for handling task scheduling; the available algorithms focus on reducing execution time while ignoring other quality of service (QoS). This paper presents a bi-objective hybrid optimisation model based on integrating the Min-Min task scheduling algorithm and the Jellyfish Search Algorithm (JSA) for independent task scheduling. First, the Min-Min task scheduling algorithm is used to initiate the initial solutions, and then JSA is used to schedule cloudlets to the appropriate virtual resources. The CloudSim toolkit is used for analysing the results of the presented algorithm. A comparison with previously presented methods is performed, namely MCT-PSO, CETSA, and ACOBF. Performance is evaluated based on time, energy consumption, and throughput metrics. The results reveal that the proposed method performs better than the existing methods.