• Agent-based energy constrained...

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

Title:
Agent-based energy constrained channel allocation in mobile computing using GA
Authors:
LUTFI MOHAMMED OMER KHANBARY, DEO PRAKASH VIDYARTHI
Source:
ADVANCES IN MULTIMEDIA, COMPUTER GRAPHICS AND BROADCASTINGInternational journal of wireless and mobile computing (Print). 7(4):388-399
Publisher Information:
Genève: Inderscience Publishers, 2014.
Publication Year:
2014
Physical Description:
print, 1 p.1/4
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Télécommunications, Telecommunications, Systèmes, réseaux et services de télécommunications, Systems, networks and services of telecommunications, Transmission et modulation (techniques et équipements), Transmission and modulation (techniques and equipments), Réseaux téléinformatiques. Rnis, Teleprocessing networks. Isdn, Divers, Miscellaneous, Radiocommunications, Equipements et installations, Equipments and installations, Radiocommunications du service mobile, Mobile radiocommunication systems, Accumulateur électrochimique, Secondary cell, Acumulador electroquímico, Agent mobile, Mobile agent, Agente movil, Algorithme génétique, Genetic algorithm, Algoritmo genético, Allocation canal, Channel allocation, Asignación canal, Communication service mobile, Mobile communication, Consommation électricité, Electric power consumption, Consumo electricidad, Electronique faible puissance, Low-power electronics, Energie minimale, Minimum energy, Energía mínima, Evaluation performance, Performance evaluation, Evaluación prestación, Gestion ressources, Resource management, Gestión recursos, Gestion énergie, Energy management, Gestión energía, Informatique mobile, Mobile computing, Logiciel, Software, Logicial, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode heuristique, Heuristic method, Método heurístico, Performance algorithme, Algorithm performance, Resultado algoritmo, Radiocommunication service mobile, Mobile radiocommunication, Radiocomunicación servicio móvil, Réseau cellulaire, Cell network, Red celular, Réseau télécommunication, Telecommunication network, Red telecomunicación, Simulation, Simulación, Système multiagent, Multiagent system, Sistema multiagente, Télécommunication sans fil, Wireless telecommunication, Telecomunicación sin hilo, channel allocation, channel reuse, energy- constrained mobile devices, genetic algorithm, mobile agent
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, University of Aden, Aden, Yemen
School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi-110067, India
ISSN:
1741-1084
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=29109468
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.29109468
Database:
PASCAL Archive

Further Information

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.