Payload-Size and Deadline-Aware scheduling for time-critical Cyber Physical Systems

High transfer speeds, low latencies and a widespread availability qualify Long Term Evolution (LTE) for various applications and services in the field of Human-to-Human (H2H) as well as fast growing Vehicle-To-X (V2X) and Cyber Physical Systems (CPS) communications. As a result, a steady growth of mobile data traffic causing an increasing interaction of different traffic classes can be observed. In order to ensure timely transmissions of time-critical data in the future, we propose the novel Payload-Size and Deadline-Aware (PayDA) scheduling approach and compare its performance regarding the compliance with deadlines with those of other common packet scheduling mechanisms. The performance analysis is done with the complex and open-source LTE simulation environment LTE-Sim. The results show that the average latency can be reduced by the factor of 20 and the mean goodput can be enhanced by a factor of about 3.5 for a high miscellaneous data traffic. In case of a heavy homogeneous and time-critical data traffic the mean Deadline-Miss-Ratio (DMR) can be decreased by about 35%.