A bacterial foraging-based batch scheduling model for distributed systems

The problem of scheduling in the parallel and distributed environment is proven to be NP-complete and has been addressed by various heuristics. It is always desired from a scheduling scheme to distribute the load evenly on the available resources so as to have maximum resource utilisation while meeting the scheduling objective(s). Bio-inspired metaheuristics for job scheduling have gained immense popularity due to their effectiveness in providing near optimal solution in a reasonable time and computational complexity. This work proposes an evolutionary static scheduling technique based on bacterial foraging for a batch of independent jobs. This model generates the schedule minimising the node idle time and the makespan while exhibiting a balanced load distribution with minimum run time overhead. Simulation study proves the effectiveness of the proposed model in comparison with its peers.