Multi-objective optimization model and algorithm for network slicing with demand exceeding resources

Network slicing allocation is a new kind of task and resource scheduling technique for 5G and 6G networks and provides the high quality service by allocating the limited infrastructure network resources to massive heterogeneous user requests (various network slices). Currently, most existing studies only consider the situation that infrastructure network resources can meet the demands of all users. However, with the quick increase of network users, the infrastructure network resources usually cannot satisfy the demands of all users. To tackle this problem, this paper designs a two-objective optimization model to maximize the service provider revenue and the user experience. To solve the model effectively, a new evolutionary algorithm based on NSGA-II framework is proposed, in which the tailor-made encoding scheme, decoding scheme and evolutionary operators are designed, respectively. The simulation results indicate that the proposed algorithm can provide diverse resource allocation solutions and is superior in scenarios where the user resource demands exceed the total available resources in the infrastructure network.