Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center

2019 ◽  
pp. 77-97 ◽  
Author(s):  
Mohammed Abdullahi ◽  
Shafi’i Muhammad Abdulhamid ◽  
Salihu Idi Dishing ◽  
Mohammed Joda Usman
Keyword(s):  
Virtual Machine ◽  
Data Center ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Cloud Data Center ◽  
Symbiotic Organisms Search ◽  
Cloud Data ◽  
Symbiotic Organisms ◽  
Energy Efficient Scheduling

scholarly journals Energy Efficient Multiresource Allocation of Virtual Machine Based on PSO in Cloud Data Center

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
An-ping Xiong ◽  
Chun-xiang Xu
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Data Center ◽  
Energy Efficient ◽  
Heuristic Algorithms ◽  
Fitness Function ◽  
Cloud Data Center ◽  
Allocation Model ◽  
Cloud Data ◽  
Machine Allocation

Presently, massive energy consumption in cloud data center tends to be an escalating threat to the environment. To reduce energy consumption in cloud data center, an energy efficient virtual machine allocation algorithm is proposed in this paper based on a proposed energy efficient multiresource allocation model and the particle swarm optimization (PSO) method. In this algorithm, the fitness function of PSO is defined as the total Euclidean distance to determine the optimal point between resource utilization and energy consumption. This algorithm can avoid falling into local optima which is common in traditional heuristic algorithms. Compared to traditional heuristic algorithms MBFD and MBFH, our algorithm shows significantly energy savings in cloud data center and also makes the utilization of system resources reasonable at the same time.

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