Optimising data access latencies of virtual machine placement based on greedy algorithm in datacentre
by Xinyan Zhang; Keqiu Li; Yong Zhang
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 2, 2019

Abstract: The total completion time of a task is also the major bottleneck in the big data processing applications based on parallel computation, since the computation and data are distributed on more and more nodes. Therefore, the total completion time of task is an important index to evaluate the cloud performance. The access latency between the nodes is one of the key factors affecting task completion time for cloud applications. Additionally, minimising total access time can reduce the overall bandwidth cost of running the job. This paper proposes an optimisation model focused on optimising VMs placement so as to minimise the total data access latency where the datasets have been located. According to the proposed model, our optimising VMs problem is linear programming. Therefore, we obtain the optimum solution of our model by the branch-and-bound algorithm with time complexity O(2^NM). Simultaneously, we also present a greedy algorithm, which has O(NM) of time complexity, to solve our model. Finally, the simulation results show that all of the solutions of our model are superior to existing models and close to the optimal value.

Online publication date: Mon, 25-Feb-2019

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