01596nas a2200253   4500000000100000000000100001008004100002260001200043653002800055653002700083653001900110653001900129653001300148100002000161700002200181700001800203700001900221245006000240856009700300300001000397490000600407520091500413022001401328       2013                            d  c03/201310aArtificial Intelligence10aDistributed  Computing10aGrid computing10aJob Scheduling10aMakespan1 aZahra Pooranian1 aMohammad Shojafar1 aJemal Abawajy1 aMukesh Singhal00aGLOA: A New Job Scheduling Algorithm for Grid Computing  uhttp://www.ijimai.org/journal/sites/default/files/files/2013/03/ijimai20132_18_pdf_62825.pdf  a59-640 v23 aThe purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed) algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA), to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.  a1989-1660