Geographical Scheduling of Multi-application Tasks for Cost Minimization in Distributed Green Data Centers

Document Type

Conference Proceeding

Publication Date

7-2-2018

Abstract

The infrastructure resources in distributed green data centers (DGDCs) are shared by multiple heterogeneous applications to provide flexible services to global users in a high-performance and low-cost way. It is highly challenging to minimize the total cost of a DGDC provider in a market where bandwidth price of Internet service providers (ISPs), electricity price and the availability of renewable green energy all vary with geographic locations. Unlike existing studies, a Geographical Scheduling method of Multi-Application Tasks (GSMAT) that exploits spatial diversity in DGDCs is proposed to minimize the total cost of their provider by cost-effectively scheduling all arriving tasks of heterogeneous applications to meet tasks' delay bound constraints. In each time slot, the cost minimization problem for DGDCs is formulated as a constrained optimization one and solved by the proposed Simulated-annealing-based Bat Algorithm (SBA). Trace-driven experiments demonstrate that GSMAT achieves lower cost and higher throughput than two typical scheduling methods.

Identifier

85062239183 (Scopus)

ISBN

[9781538666500]

Publication Title

Proceedings 2018 IEEE International Conference on Systems Man and Cybernetics Smc 2018

External Full Text Location

https://doi.org/10.1109/SMC.2018.00537

First Page

3171

Last Page

3176

Grant

61703011

Fund Ref

National Natural Science Foundation of China

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