Abstract

In 5G Slice Networks, the multi-tenant multi-tier heterogeneous network will be critical in meeting the Quality of Service (QoS) requirement of the different slice use cases; Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) reduction for mobile network operators. Hence, the 5G slice networks should be as flexible as possible to accommodate the different network dynamics such as of user location and distribution, different slice use case QoS requirement, cell load, intra-cluster interference and Mobile Virtual Network Operators (MVNOs) Service Level Agreement (SLA). Motivated by this, this paper addresses a latency-aware dynamic resource allocation problem for 5G Slice Networks in a multi-tenant multi-tier heterogeneous environment, for efficient radio resource allocation. The latency-aware dynamic resource allocation problem is formulated as a maximum utility optimisation problem. The optimisation problem is transformed and the hierarchical decomposition technique is adopted to reduce the complexities in solving the optimisation problem. Furthermore, we proposed a Genetic Algorithm (GA) Intelligent Latency-Aware Resource Allocation scheme (GI-LARE). Our findings have been obtained by extensive Monte Carlo numerical simulations and comparisons were carried out with the static allocation scheme and a branch and bound method. The genetic algorithm schemes out perform the static scheme.

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