Title: Agent-based energy constrained channel allocation in mobile computing using GA

Authors: Lutfi Mohammed Omer Khanbary; Deo Prakash Vidyarthi

Addresses: Department of Computer Science, University of Aden, Aden, Yemen ' School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi-110067, India

Abstract: Energy is a significant limitation on mobile devices as battery power often drains very fast during execution. Little attention has been paid to the optimal power consumption by software execution on these mobile devices. Cellular systems are usually powered by battery, and therefore power conservation is a major concern in such networks. Energy-efficient algorithms serve better to save power in such environments. Optimal uses of the network resources may lead to power conservation in such systems. In this paper, an energy-efficient resources management algorithm to profile power consumption is proposed. Power consumption of the system is described with respect to certain workload. The proposed power management solution uses mobile agent technology for energy-efficient channel allocation in cellular networks. To handle this, a meta-heuristics technique, Genetic Algorithm, is used as the problem is combinatorial complex. Extensive simulation study, to evaluate the performance, exhibits the veracity of the proposed model.

Keywords: channel allocation; channel reuse; mobile agents; genetic algorithms; energy-constrained mobile devices; energy constraints; mobile computing; m-computing; agent-based systems; multi-agent systems; MAS; battery power; optimal power consumption; energy efficiency; resources management.

DOI: 10.1504/IJWMC.2014.063053

International Journal of Wireless and Mobile Computing, 2014 Vol.7 No.4, pp.388 - 399

Received: 27 Dec 2011
Accepted: 08 Jul 2012
Published online: 31 Oct 2014 *

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