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Cloud Computing Demand Elasticity Algorithm based on Ant Colony Algorithm

[ Vol. 14 , Issue. 1 ]

Author(s):

Chunyu Liu, Fengrui Mu* and Weilong Zhang   Pages 37 - 43 ( 7 )

Abstract:


Background: In the recent era of technology, the traditional Ant Colony Algorithm (ACO) is insufficient in solving the problem of network congestion and load balance, and network utilization.

Methods: This paper proposes an improved ant colony algorithm, which considers the price factor based on the theory of elasticity of demand. The price factor is denominated in the impact on the network load which means indirect control of network load, congestion or auxiliary solution to calculate the idle resources caused by the low network utilization and reduced profits.

Results: Experimental results show that the improved algorithm can balance the overall network load, extend the life of path by nearly 3 hours, greatly reduce the risk of network paralysis, and increase the profit of the manufacturer by 300 million Yuan.

Conclusion: Furthermore, the results show that the improved method has great application value in improving network efficiency, balancing network load, prolonging network life and increasing network operating profit.

Keywords:

Cloud computing, ant colony algorithm, elasticity of demand theory, amazon Elastic Compute Cloud (Amazon EC2), Platform as a Service (PaaS), Ant Colony Algorithm (ACO).

Affiliation:

College of Computer Science and Engineering, Cangzhou, Normal University, Hebei, Cangzhou 061000, College of Computer Science and Engineering, Cangzhou, Normal University, Hebei, Cangzhou 061000, Quality Management Center, Hebei Jiaotong Vocational and Technical, Shijiazhuang, Hebei 050035

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