Task allocation in distributed computing systems using adaptive particle swarm optimisation Online publication date: Mon, 29-Oct-2012
by G. Subashini; M.C. Bhuvaneswari
International Journal of Computer Applications in Technology (IJCAT), Vol. 44, No. 4, 2012
Abstract: Both parallel and distributed systems play a vital role in the improvement of high performance computing. A primary issue concerned with the performance of a parallel application executing on a distributed system is allocating the tasks of the application among the various processors in the system. As several conflicting factors influence the allocation strategy, it is necessary to account for multiple objectives. To handle the multi-objective task allocation problem, a Multi-objective Adaptive Particle Swarm Optimisation (MO-ANPSO) with non-dominated sorting is proposed in this paper. The algorithm is implemented and tested on a data set comprising several instances of task interaction graph that models the application. The results show that the proposed method obtains a set of optimal allocations with increased level of performance over the other PSO methods.
Online publication date: Mon, 29-Oct-2012
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com