The mobile communication industry has recently been subject to rapid evolution and innovations on mobile networking technologies. To accommodate a large number of services with diversified characteristics and performance requirements, network slicing, which partitions a single physical network into multiple isolated slices, has been proposed as a key enabling technology in the design of next-generation wireless networks. In this paper, we study the optimal network slicing problem that combines the server placement, capacity allocation, and task assignment decisions to be made by the operators in order to maximize their revenues. We first propose a mixed-integer linear programming (MILP) formulation for the network slicing problem. Then, we device two algorithms based on Benders decomposition that exploit the special structure of the proposed formulation. We also introduce valid inequalities and problem-specific cut generation techniques to improve the efficiency of the solution approach. The computational study on randomly generated test instances show that the proposed method significantly improves the solution quality and yields near-optimal results for even very large instances within the allocated time limit.
Betül Ahat is a PhD candidate in the Department of Industrial Engineering at Boğaziçi University, Istanbul. She received her BS and MS degrees in Industrial Engineering from Boğaziçi University in 2013 and 2015. Her research focuses on linear and combinatorial optimization, developing mixed-integer programming approaches to large-scale operations research related problems.