Network Slicing on 5G Vehicular Cloud Computing Systems

Abstract

Fifth generation Vehicular Cloud Computing (5G-VCC) systems support various services with strict Quality of Service (QoS) constraints. Network access technologies such as Long-Term Evolution Advanced Pro with Full Dimensional Multiple-Input Multiple-Output (LTE-A Pro FD-MIMO) and LTE Vehicle to Everything (LTE-V2X) undertake the service of an increasing number of vehicular users, since each vehicle could serve multiple passenger with multiple services. Therefore, the design of efficient resource allocation schemes for 5G-VCC infrastructures is needed. This paper describes a network slicing scheme for 5G-VCC systems that aims to improve the performance of modern vehicular services. The QoS that each user perceives for his services as well as the energy consumption that each access network causes to user equipment are considered. Subsequently, the satisfactory grade of the user services is estimated by taking into consideration both the perceived QoS and the energy consumption. If the estimated satisfactory grade is above a predefined service threshold, then the necessary Resource Blocks (RBs) from the current Point of Access (PoA) are allocated to support the user’s services. On the contrary, if the estimated satisfactory grade is lower than the aforementioned threshold, additional RBs from a Virtual Resource Pool (VRP) located at the Software Defined Network (SDN) controller are committed by the PoA in order to satisfy the required services. The proposed scheme uses a Management and Orchestration (MANO) entity implemented by a SDN controller, orchestrating the entire procedure avoiding situations of interference from RBs of neighboring PoAs. Performance evaluation shows that the suggested method improves the resource allocation and enhances the performance of the offered services in terms of packet transfer delay, jitter, throughput and packet loss ratio.