Multiple tasks allocation in arbitrarily connected distributed computing systems using a* algorithm and genetic algorithm

Authors:
Biplab Kumer Sarker;Anil Kumar Tripathi;Deo Prakash Vidyarthi;Laurence Tianruo Yang;Kuniaki Uehara
Affiliations:
Faculty of Computer Science, University of New Brunswick, Fredericton, Canada;Institute of Technology, Banaras Hindu University, Varanasi, India;Jawaharal Nehru University, New Delhi, India;Department of Computer Science, St. Francis Xavier University, Canada;Graduate School of Science and Technology, Kobe University, Japan
Venue:
ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking
Year:
2006

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Abstract

A number of algorithms is proposed for allocation of tasks in a DCS. Most of them did not consider allocation of various unrelated tasks partitioned into modules by taking into account the architectural capability of the processing nodes and the connectivity among them. This work considers allocation of disjoint multiple tasks with corresponding modules wherein multiple disjoint tasks with their modules compete for execution on an arbitrarily networked DCS. Two algorithms have been presented based on well-known A* algorithm and Genetic Algorithm techniques. The proposed algorithms consider a load balanced allocation for the purpose. The paper justifies the effectiveness of the proposed algorithms using several case studies.