Although some excellent works have been done on networking, caching, and computing, these three important areas have traditionally been addressed separately in the literature. In this paper, we describe the recent advances in jointing networking, caching, and computing and present a novel integrated framework: software-defined networking, caching, and computing (SD-NCC). SD-NCC enables dynamic orchestration of networking, caching, and computing resources to efficiently meet the requirements of different applications and improve the end-to-end system performance. Energy consumption is considered as an important factor when performing resource placement in this paper. Specifically, we study the joint caching, computing, and bandwidth resource allocation for SD-NCC and formulate it as an optimization problem. In addition, to reduce computational complexity and signaling overhead, we propose a distributed algorithm to solve the formulated problem, based on recent advances in alternating direction method of multipliers (ADMM), in which different network nodes only need to solve their own problems without exchange of caching/computing decisions with fast convergence rate. Simulation results show the effectiveness of our proposed framework and ADMM-based algorithm with different system parameters.

Additional Metadata
Keywords Bandwidth, caching, Cloud computing, computing, Dynamic scheduling, Energy consumption, energy efficient, IEEE transactions, Networking, Programmable control, resource allocation, Resource management
Persistent URL dx.doi.org/10.1109/TNET.2017.2782216
Journal IEEE/ACM Transactions on Networking
Citation
Chen, Q. (Qingxia), Yu, F.R, Huang, T. (Tao), Xie, R. (Renchao), Liu, J. (Jiang), & Liu, Y. (Yunjie). (2018). Joint Resource Allocation for Software-Defined Networking, Caching, and Computing. IEEE/ACM Transactions on Networking. doi:10.1109/TNET.2017.2782216