Abstract
Cloud computing provides a number of resources over the internet to the users based on their request. These resources need to be scheduled in an efficient manner so that not only the provider gets benefited out of it, but the user also can take its advantage to the full extent. Therefore, resource scheduling is a critical and demanding requirement in a cloud environment. In this paper, we are proposing a bio-inspired approach, in which we have modified the existing particle swarm optimization (PSO) Algorithm and have combined it with genetic algorithm (GA) which in turn has the features and advantages of both the approaches. The proposed inventive particle swarm optimization with genetic algorithm (IPSO-GA) not only schedules resources efficiently, but also effectively manage the resources. The proposed approach is compared with traditional approaches on CloudSim simulator, where the proposed algorithm outperforms the traditional algorithms in terms of makespan time, execution time and resource utilization. Our proposed approach IPSO-GA has given better results than the existing approaches.
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Assudani, P.J., Balakrishnan, P. An efficient approach for load balancing of VMs in cloud environment. Appl Nanosci 13, 1313–1326 (2023). https://doi.org/10.1007/s13204-021-02014-z
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DOI: https://doi.org/10.1007/s13204-021-02014-z