Joint Resource Allocation for Software-Defined Serverless Service-Centric Networking

Recently, there are significant advances in networking, computing, and caching (NCC). Nevertheless, few attempts have been made to explore the potential of the promising server-less computing paradigm in NCC integrated frameworks. In this paper, we consider a software-defined serverless service-centric networking (SD-SSCN) framework that not only dynamically orchestrates NCC by combining software-defined networking and service-centric networking technologies but also strongly focuses on the context of serverless computing. To achieve a cost-efficient green SD-SSCN system, we first formulate the joint resource allocation problem to minimize an overall average cost model. We derive this problem as a nonlinear integer programming problem, then we relax it as a quadratic programming problem and develop a primal-dual interior-point algorithm to find joint resource allocation solutions. Simulation results show that our proposed SD-SSCN framework significantly outperforms the traditional networks in terms of the average cost in the context of serverless computing.