A queuing theory based delay-efficient packet scheduler for machine type communication

Abstract

Lately, there is a drastic change in the telecommunication industry due to emergence of Internet of Things (IoT). Machine to Machine (M2M) plays a very important role in enabling IoT. As the LTE is mainly suitable for Human-to-Human (H2H) communication, MTC faces some challenges in LTE like radio resource management and uplink-scheduling algorithms are not suitable for MTC. In this paper, we use a queuing theory and propose a packet scheduler, which would model the regular and event-driven traffic and schedule the jobs in queue for request processing. Then using the Markov Chain process, we calculate the queue length and determine the blocking probability. If there is high blocking probability and still there are some requests in queue, then those requests will be processed in virtual server for maximum network usage.