Payload-Size and Deadline-Aware Scheduling for Time-critical Cyber Physical Systems.

Compared to former mobile networks, Long Term Evolution (LTE) offers highertransfer speeds, significantly lower latencies and a widespread availability,qualifying LTE for a wide range of different applications and services in thefield of conventional Human-to-Human (H2H) as well as fast growing Vehicle-To-X(V2X) and Cyber Physical Systems (CPS) communications. As a result, a steadygrowth of mobile data traffic, which is reflected in an increased interactionbetween different traffic classes, can be observed. In order to ensure timelytransmissions of time-critical data in the future, we propose the novelPayload-Size and Deadline-Aware (PayDA) scheduling approach and compare itsperformance regarding the compliance for deadlines with those of other commonpacket scheduling mechanisms. The performance analysis is done with the complexand open-source LTE simulation environment LTE-Sim. The results show that theaverage latency can be reduced by the factor of 20 and the mean data rates canbe enhanced by a factor of about 3.5 for a high miscellaneous data traffic. Inthe case of a heavy homogeneous and time-critical data traffic the meanDeadline-Miss-Ratio (DMR) can be decreased by about 35%.