2020/02/18 by Wei‐Kun Chen, Chen, Wei-Kun, Ya‐Feng Liu +5 · 1 citation
Computer Science · #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Information Theory (cs.IT) #Network Security and Intrusion Detection #Networking and Internet Architecture (cs.NI) #Optimization and Control (math.OC) #Signal Processing (eess.SP) #Software System Performance and Reliability #Software-Defined Networks and 5G #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.07380
openalex publication_date 2020/02/18 · openalex created_date 2020/02/24 · openalex updated_date 2026/07/28
Network function virtualization is a promising technology to simultaneously support multiple services with diverse characteristics and requirements in the fifth generation and beyond networks. In practice, each service consists of a predetermined sequence of functions, called service function chain (SFC), running on a cloud environment. To make different service slices work properly in harmony, it is crucial to select the cloud nodes to deploy the functions in the SFC and flexibly route the flow of the services such that these functions are processed in sequence, the end-to-end (E2E) latency constraints of all services are guaranteed, and all resource constraints are respected. In this paper, we propose a new (mixed binary linear program) formulation of the above network slicing problem that optimizes the system energy efficiency while jointly considers the resource budget, functional instantiation, flow routing, and E2E latency requirement. Numerical results show the advantage of the proposed formulation compared to the existing ones.