Extended Max-Min Scheduling using Petri Net and Load Balancing
El-Sayed T. El-kenawy1, Ali Ibraheem El-Desoky2, Mohamed F. Al-rahamawy3

1El-Sayed T. El-kenawy Dep. of Comp. and Sys. Eng., Faculty of Engineering, Mansoura University, Egypt.
2Ali Ibraheem El-DesokyDep. of Comp. and Sys. Eng., Faculty of Engineering, Mansoura University, Egypt
3Mohamed F. Al-rahamawy Dep. of Computer scienecs, Faculty of Computer and Info., Mansoura University, Egypt.
Manuscript received on September 01, 2012. | Revised Manuscript received on September 02, 2012. | Manuscript published on September 05, 2012. | PP: 189-203 | Volume-2 Issue-4, September 2012. | Retrieval Number: D0940082412/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Max-min algorithm is based on comprehensive study of the impact of RASA algorithm in scheduling tasks and the atom concept of Max-min strategy. An Improved unique version of Max-min algorithm is proposed to outperform scheduling map at least similar to RASA map in total complete time for submitted jobs. Improved Max-min is based on the expected execution time instead of complete time as a selection basis. We employ Petri nets which are well suited for modeling the concurrent behavior of distributed systems. Experimental results show availability of load balance in small cloud computing environment and total small makespan in large-scale distributed system; cloud computing. In turn scheduling tasks within cloud computing using Improved Max-min demonstrates achieving schedules with comparable lower makespan rather than RASA and original Max-min.
Keywords: Distributed System, Job Dispatching Algorithms and Cloud Computing. Petri net, Load Balance, Quality of Service, Meta Task Scheduling, Max-min Algorithm, Min-min Algorithm