Optimized Virtual Resource Allocation in Random Access Procedure for Machine-to-Machine Communications in Software Defined Cellular Networks
Zhuo Wang, Enchang Sun, Meng Li, Jian Li and Yanhua Zhang
To optimize uplink random access procedure, improve resource utilization and allocate limited radio resources reasonably of Machine-to-Machine (M2M) communication in cellular networks, we propose a novel two-level controlling framework for M2M communications in software defined cellular networks with wireless network virtualization. In our proposed framework, substrate physical M2M network is abstracted and sliced into multiple virtual M2M networks, each is controlled by a virtual SDN controller. By decoupling control plane from the virtual base station and by the interaction between virtual controller and virtual equipments, random access procedures can be optimized and throughput can be increased. Furthermore, we propose a modified particle swarm optimization-simulated annealing (PSO-SA) algorithm, named temperature in SA changing inertia weight PSO algorithm (TCIWPSO-SA), to allocate virtual radio resources reasonably in order to maximize fairness among virtual networks. Extensive simulation results with different system parameters are presented to show that the proposed scheme and algorithm can achieve considerable performance gains in both throughput and fairness of virtual resource allocation.
Keywords: Random access, machine-to-machine communications, software defined networks, wireless network virtualization, resource allocation.