A robust voting machine allocation model to reduce extreme waiting

Omega ◽  
2015 ◽  
Vol 57 ◽  
pp. 230-237 ◽  
Author(s):  
Muer Yang ◽  
Xinfang (Jocelyn) Wang ◽  
Nuo Xu
2015 ◽  
Vol 66 (8) ◽  
pp. 1363-1369 ◽  
Author(s):  
Xinfang (Jocelyn) Wang ◽  
Muer Yang ◽  
Michael J Fry

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
An-ping Xiong ◽  
Chun-xiang Xu

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.


2021 ◽  
Vol 122 ◽  
pp. 102888
Author(s):  
Han Zou ◽  
Maged M. Dessouky ◽  
Shichun Hu

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