Joint optimization of IoT devices access and bandwidth resource allocation for network slicing in edge-enabled radio access networks

With the rapid development of the Internet-of-Things (IoT) and the continuous progress in software technologies, IoT devices (IoTDs) have been applied to various scenarios for executing computation-intensive applications. Limited by many restrictions, IoTDs usually cannot fully meet the demands of these applications. In this context, the mobile edge computing (MEC) paradigm was proposed. In MEC paradigm, IoTDs and edge servers (ESs) form an edge-enabled radio access network (E-RAN) so that the IoTDs can solve the problem of their poor computational resources by transmitting data or tasks to the ES. In order to improve the Quality-of-Service (QoS) of E-RAN, network slicing technology is widely used. Although the combination of MEC and network slicing technology has effectively made up for the deficiencies of IoTDs, the resource efficiency of network slicing is still a serious challenge. This paper considers a multi-IoTD and multi-ES network system, where there are multiple service providers (SPs) with different priorities. In this system, the joint optimization of IoTDs access and bandwidth resource allocation is formulated, whose objective is to maximize the system th. To address this problem, we develop an optimization algorithm including greedy-based devices access and bandwidth resource allocation optimization (GDABRA) algorithm. Extensive simulation results are provided to demonstrate the system throughput growth of the proposed algorithm in comparison with benchmark algorithms.