Network Slice Admission Model: Tradeoff between Monetization and Rejections

Network slicing is an emerging paradigm aiming to provide use case tailored virtual networks. However, it poses new challenges for slice resource assignment. Specifically, new admission control policies are required to model delay-tolerant slices. Fair admission of requests from different willingness-to-pay subscribers while maximizing resource monetization is another major problem. This paper proposes a novel slice admission model with delayed admission and quota constraints to maximize the monetization and minimize the service agreement violation. We investigate a tradeoff between the monetization and the admission rate, that rise due to quota-driven resource allocation. We map the slice admission to the multiple knapsack problem, formulate an integer programming model, and present a partially adaptive greedy (PAGE) algorithm to tackle this combinatorial optimization problem. Simulation results validate the efficacy of the PAGE over classical heuristics.