An Analytical Study of Multiprocessor Scheduling Using Metaheuristic Approach

The process scheduling in the distributed and heterogeneous environment is the principal concern which can influence the execution performance of the application. The multiprocessor scheduling concept in grid environment incepts from 1980. After a decade in 1992 heuristic and evolutionary approaches started to solve these issues followed by nature inspired metaheuristic algorithms which started in the twentieth century. This paper provides a taxonomy of scheduling techniques which defines characteristics of each technique and gives some prominent algorithms as an example. Many research works have been done for minimizing execution cost and makespan as the influencing parameters for the scheduling of the dependent processes but few researchers have considered energy utilization, memory utilization and miss rate. This paper describes different types of algorithms starting from traditional algorithms from the year 1984 and consequently, metaheuristic algorithms including nature-inspired, bio-inspired, swarm intelligence-based techniques used for multiprocessor scheduling optimization purposes in different real-time applications up to 2019. It also defines available simulation tool for simulating scheduling algorithms. This paper will empower the beginners to select appropriate techniques according to their requirements and especially it will be a great help for getting a road map for different scheduling techniques and its applications. Graphical Abstract: [Figure not available: see fulltext.] © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.