On the use of meta-heuristics to increase the efficiency of online grid workflow scheduling algorithms
The competitiveness of online algorithms is measured based on the correctness of the results produced and processing time efficiency. Traditionally evolutionary algorithms are not favored in online paradigms because of the large number of iterations involved in the algorithm which translates directly into processing time overhead. In this paper we describe MARS (Management Architecture for Resource Services) online scheduling algorithm which uses Simulated Annealing and concepts from Tabu Search to drastically decrease the processing time of the algorithm. The paper outlines the concepts behind MARS, the components involved and scheduling methodology used. In addition we also identify the time consuming bottlenecks in the performance of the system and how evolutionary algorithms help us soar past them.
workflow scheduling simulated annealing grid management architectures scheduling heuristics grid middleware collaborative computing resource selection