Abstract
Machine-to-machine (M2M) communication is now a frequently used term owing to the knowledge of the Internet of Things. As the applications of the M2M increase, the number of M2M devices is predicted to highly increase in the next coming years. Presently, there is an attempt to improve the cellular networks to handle both human-to-human (H2H) and M2M communications. Integrating the M2M communication across the usual H2H communication is an important target owing to the predictable growth in the number of M2M devices that includes the distinctive features of the M2M traffic. To increase the efficiency of the usage of the LTE resource, the same resource is predicted to be used for H2H and M2M communications. Consequently, an efficient resource-scheduling plan is essential to manage an LTE network system including both M2M devices and H2H users. In this paper, we propose a delay-aware time-slotted resource allocation with a priority-based queuing model, which is designed especially for the LTE network including both M2M devices and H2H users. Resource scheduling provides the highest priority to H2H, in contrast to M2M, which is given the lowest priority. The high arrival rate of the users of H2H results in widespread starvation of M2M users; hence, it is likely to transmit some resources to M2M devices by postponing the H2H users up to QoS value, which does not have a negative impact on their quality. In the proposed schemes, the H2H users' priority is relaxed by delaying them in the LTE network up to the level that does not have a negative impact on the quality of the H2H users. Then, in addition to protecting the H2H users, the proposed schemes can increase the utilization of the M2M resource usage and reduce its average waiting delay. In addition, simulation and analytical models are developed in order to assess the performance measures of M2M in terms of average waiting delay (W) and average system delay (T). The results show that the proposed schemes provide better M2M performance while controlling the QoS level for H2H services.