Energy Efficient Resource Allocation in Heterogenous Software Defined Network : A Reverse Combinatorial Auction Approach
Zhang, D., Chang, Z., Zolotukhin, M., & Hämäläinen, T. (2015). Energy Efficient Resource Allocation in Heterogenous Software Defined Network : A Reverse Combinatorial Auction Approach. In Proceedings of the 4th IEEE/CIC International Conference on Communications in China (ICCC'2015). Symposium on Signal Processing for Communications (pp. 739-744). IEEE.
© 2015 IEEE. This is an author's post-print version of an article whose final and definitive form has been published in the conference proceeding by IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
In this paper, resource allocation for energy effi- ciency in heterogeneous Software Defined Network (SDN) with multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction game, which takes different quality of service (QoS) requirements into account. The heterogeneous network selection associated with power allocation problem is optimized by maximizing the energy efficiency of data transmission. By exploiting the properties of fractional programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent subtractive convex optimization problem. The proposed reverse combinatorial auction game is proved to be strategy-proof with low computing complexity. Simulation results illustrate that with SDN controller, the proposed iterative ascending price algorithm converges in a small number of iterations and demonstrates the trade-off between energy efficiency and heterogeneous QoS requirement, especially ensures high fairness among different network service providers. ...