Network operators run various applications on the control platform to perform different management tasks, like routing, monitoring, load balancing and firewall. These applications have complex interactions with each other, making it difficult to deploy and reason about their behaviours. To solve these kinds of problem, this paper presents a Distributed efficient joint resource allocation using conjugate gradient method (DEJRA-CG) is to accurately calculate the average energy consumption for all case in the dynamic network. The proposed method follows a SDN model for finding the Shortest Distances in gradient search estimation was formulated using three algorithms, namely Resource Allocation, Searching algorithm and Distributed Power Efficient Scheduling algorithm based on the identified network path in SDN. According to the experimental results the proposed algorithm mainly focused on SDN based caching and computing time using MATLAB R2013a platform. The achieved DEJRA-CG has less distance variation with less computation time when comparing to Building the Dependency Graph and software-defined networking, caching, and computing (SD-NCC) algorithms.

Networking, caching, computing, resource allocation, energy efficient

[1] J. Baliga, R. W. A. Ayre, K. Hinton, and R. S. Tucker, “Green cloud computing: Balancing energy in processing, storage, and transport,” Proc. IEEE, vol. 99, no. 1, pp. 149–167, Jan. 2011.
[2] N. Choi, K. Guan, D. C. Kilper, and G. Atkinson, “In-network caching effect on optimal energy consumption in content-centric networking,” in Proc. IEEE ICC, Jun. 2012, pp. 2889–2894.
[3] S. Salsano, N. Blefari-Melazzi, A. Detti, G. Morabito, and L. Veltri, “Information centric networking over SDN and OpenFlow: Architectural aspects and experiments on the OFELIA testbed,” Comput. Netw., vol. 57, no. 16, pp. 3207–3221, Nov. 2013.
[4] A. Chanda and C. Westphal, “ContentFlow: Adding content primitives to software defined networks,” in Proc. IEEE GLOBCOM, Dec. 2013, pp. 2132–2138.
[5] B. Wang, Y. Zheng, W. Lou, and Y. T. Hou, “DDoS attack protection in the era of cloud computing and software-defined networking,” in Proc. IEEE 22nd Int. Conf. Netw. Protocols, Oct. 2014, pp. 624–629.
[6] D. Kreutz, F. Ramos, P. E. Veríssimo, C. E. Rothenberg, S. Azodolmolky, and S. Uhlig, “Software-defined networking: A comprehensive survey,” Proc. IEEE, vol. 103, no. 1, pp. 14–76, Jan. 2015.
[7] G. Liu, F. R. Yu, H. Ji, and V. C. M. Leung, “Virtual resource management in green cellular networks with shared full-duplex relaying and wireless virtualization: A game-based approach,” IEEE Trans. Veh. Technol., vol. 65, no. 9, pp. 7529–7542, Sep. 2016.
[8] B. Wang, W. Song, W. Lou, and Y. T. Hou, “Privacy-preserving pattern matching over encrypted genetic data in cloud computing,” in Proc. IEEE INFOCOM, May 2017, pp. 1–9.
[9] Q. Chen et al., “An integrated framework for software defined networking, caching, and computing,” IEEE Netw., vol. 31, no. 3, pp. 46–55, May/Jun. 2017.
[10] Qingxia Chen, F. Richard Yu, Tao Huang, Renchao Xie, Jiang Liu, and Yunjie Liu, “Joint Resource Allocation for Software-Defined Networking, Caching, and Computing”, IEEE/ACM Transactions on Networking, vol. 26, no. 1, February 2018.