شماره ركورد كنفرانس :
4753
عنوان مقاله :
Resources allocation with dragonfly algorithm in cloud datacenters
عنوان به زبان ديگر :
Resources allocation with dragonfly algorithm in cloud datacenters
پديدآورندگان :
Miri Seyed Saleh benjamin.miri@hotmail.com Department of computer engineering, Faculty of engineering, Ashtian Branch , Zarafshan Faraneh Department of computer engineering, Faculty of engineering, Ashtian Branch , Nadi Senejani Mahdieh Department of computer engineering, Faculty of engineering, Ashtian Branch
كليدواژه :
load balancing , dragonfly optimization algorithm , resources allocation , cloud computing.
عنوان كنفرانس :
اولين كنفرانس بين المللي محاسبات و سامانه هاي توزيع شده
چكيده فارسي :
Load balancing, resource allocation management, and scheduling tasks are the most important challenges in cloud computing. Load balancing is performed at virtual machine level in data centers, while scheduling and allocation of resources are applied on the hosts and virtual machines, respectively. Therefore, the process of allocation of resources to virtual machines in cloud computing and maintaining the load balanced are performed using dragonfly optimization algorithm in this research. The proposed method consists of initializing the algorithm, determining the number of virtual machines and the number of tasks, implementing the dragonfly optimization algorithm, allocating resources, and scheduling the tasks by maintaining the load balanced on virtual machines. Compared to other methods, improvement of the dragonfly algorithm is approximately 1.34 times more at execution time, 20 milliseconds faster at response time to requests and 6% improvement in term of number of migrations.
چكيده لاتين :
Load balancing, resource allocation management, and scheduling tasks are the most important challenges in cloud computing. Load balancing is performed at virtual machine level in data centers, while scheduling and allocation of resources are applied on the hosts and virtual machines, respectively. Therefore, the process of allocation of resources to virtual machines in cloud computing and maintaining the load balanced are performed using dragonfly optimization algorithm in this research. The proposed method consists of initializing the algorithm, determining the number of virtual machines and the number of tasks, implementing the dragonfly optimization algorithm, allocating resources, and scheduling the tasks by maintaining the load balanced on virtual machines. Compared to other methods, improvement of the dragonfly algorithm is approximately 1.34 times more at execution time, 20 milliseconds faster at response time to requests and 6% improvement in term of number of migrations.
