Mendeley
TY  _  JOUR
ID  -  1401072739782
TI  -  Improving resource allocation in mobile edge computing using gray wolf and particle swarm optimization algorithms
JO  -  Journal of Information and Communication Technology
JA  -  ES
LA  -  fa
SN  -  2717-0411
AU  -  dashti seyed ebrahim
AU  -  shabooei saeid
AD  -  هیات علمی
AD  -  دانشگاه آزاد اسلامی
Y1  -  2024
PY  -  2024
VL  -  59
IS  -  
SP  -  108
EP  -  124
KW  -  Improving resource allocation 
KW  -   mobile edge computing 
KW  -   particle swarm optimization algorithm
KW  -   gray wolf algorithm.
DO  -  
N2  -  Mobile edge computing improves the experience of end users to achieve appropriate services and service quality. In this paper, the problem of improving resource allocation when offloading tasks based on mobile devices to edge servers in computing systems was investigated. Some tasks are processed locally and some are offloaded to edge servers. The main issue is that the offloaded tasks for virtual machines in computing networks are properly scheduled to minimize computing time, service cost, computing network waste, and the maximum connection of a task with the network. In this paper, it was introduced using the hybrid algorithm of particle swarm and gray wolf to manage resource allocation and task scheduling to achieve an optimal result in edge computing networks. The comparison results show the improvement of waiting time and cost in the proposed approach. The results show that, on average, the proposed model has performed better by reducing the work time by 10% and increasing the use of resources by 16%.
UR  - rimag.ir/en/Article/39782
L1  - rimag.ir/en/Article/Download/39782
ER  -  
