Resource allocation method in cloud computing environments with multiple data centers over a wide area

2015 ◽  
Author(s):  
Masatoshi Uriu ◽  
Shin-ichi Kuribayashi
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Data Centers ◽  
Wide Area ◽  
Allocation Method ◽  
Multiple Data ◽  
Computing Environments

Heuristic Task Consolidation Techniques for Energy Efficient Cloud Computing

2015 ◽  
pp. 238-260 ◽  
Author(s):  
Dilip Kumar ◽  
Bibhudatta Sahoo ◽  
Tarni Mandal
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Data Centers ◽  
Optimal Solution ◽  
Solution Space ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Cloud Infrastructure ◽  
Two Phase ◽  
Phase Selection

The energy consumption in the cloud is proportional to the resource utilization and data centers are almost the world's highest consumers of electricity. The complexity of the resource allocation problem increases with the size of cloud infrastructure and becomes difficult to solve effectively. The exponential solution space for the resource allocation problem can be searched using heuristic techniques to obtain a sub-optimal solution at the acceptable time. This chapter presents the resource allocation problem in cloud computing as a linear programming problem, with the objective to minimize energy consumed in computation. This resource allocation problem has been treated using heuristic approaches. In particular, we have used two phase selection algorithm ‘FcfsRand', ‘FcfsRr', ‘FcfsMin', ‘FcfsMax', ‘MinMin', ‘MedianMin', ‘MaxMin', ‘MinMax', ‘MedianMax', and ‘MaxMax'. The simulation results indicate in the favor of MaxMax.

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