Job Scheduling Algorithms on Grid Computing: State-of- the Art

Abstract

Scheduling jobs on computational grids is identified as NP-complete problem due to the heterogeneity of resources; the resources belong to different administrative domains and apply different management policies. This paper conducted an extensive and wide literature review to study the state of the art of grid scheduling algorithms. This review starts with an overview of the grid technologies and a description of the grid resource management systems. The evolution of the grid scheduling mechanisms is illustrated in this paper started from basic scheduling mechanisms such as Min-Min and Max-Min approaches ending with the swarm intelligence optimization methods. The swarm intelligence and evolutionary mechanisms are also presented and critically analyzed.