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Construction and Resource Allocation of Cost-Efficient Clustered Virtual Network in Software Defined Networks

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Abstract

As cloud computing becomes more and more massive and dynamic, software defined networks (SDNs), as a global sight of the network, make resource allocation more serviceable and effective. However, it is a great challenge to effectively allocate resource for different tenants’ computing requests while considering the performance of the whole network. To address this problem, in this paper, we propose a clustered virtual network (CVN) abstraction strategy and a dynamical heapsort algorithm to find the pod with the most appropriate number of virtual machines. In the cloud, when the SDN controller receives a tenant’s computing task request, it will search for the resources in the whole data center resource pool by the tenant’s request. If there are enough virtual machine resources in one single pod to meet the computing task, the controller will construct a CVN time-efficiently. If not, the controller will provide resources from several pods to construct a crossing pod CVN. Furthermore, we formulate the resource allocation problem as a Linear Programming problem aiming to maximize network throughput. To achieve computation feasibility in massive data center networks, we propose an approximation primal dual algorithm for solving this Linear Programming problem. Theoretical analysis shows that the proposed primal-dual algorithm is feasible and suitable for solving massive computation problem in SDNs. Finally, we evaluate the performance of our proposed algorithms and verify the correctness of our theoretical analysis.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61373179, 6137 3178, 61402381, 61503309), Natural Science Key Foundation of Chongqing (cstc2015jcyjBX0094), the Fundamental Research Funds for the Central Universities (XDJK2015C010, XDJK 2015D023, XDJK2016A011, XDJK2016D047), Natural Science Foundation of Chongqing (CSTC2016JCYJA0449), China Postdoctoral Science Foundation (2016M592619), Chongqing Postdoctoral Science Foundation (XM2016002).

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Authors and Affiliations

  1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Bo Li, Songtao Guo & Yan Wu

  2. School of Chemistry and Chemical Engineering, Southwest University, Chongqing, 400715, China

    Defang Liu

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  1. Bo Li
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  2. Songtao Guo
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  3. Yan Wu
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  4. Defang Liu
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Correspondence to Songtao Guo.

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Li, B., Guo, S., Wu, Y. et al. Construction and Resource Allocation of Cost-Efficient Clustered Virtual Network in Software Defined Networks. J Grid Computing 15, 457–473 (2017). https://doi.org/10.1007/s10723-017-9402-6

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