Abstract
The diversity traffic requirements, reliability communication infrastructure, and the real-time end-to-end (E2E) latencies are some of the major communication challenges to support a diverse set of emerging Internet of Things (IoT) applications include Smart Grid (SG) applications. For instance, using point-to-point fibers between each device and the controller has been reported, previously, as one of the solutions to address the E2E latency requirements. However, even with the fiber capacity, utilizing the technique was limited due to its excessive cost. Hence, using a commercial multiservice cellular network such as Long-Term Evolution (LTE) and Long-Term Evolution-Advanced (LTE-A) is a considerable solution due to the high-performance metrics: high throughput, low latency, higher reliability, and large bandwidth.
In this paper, we propose an uplink LTE Cascaded Priority-based scheduling algorithm (CPb) that supports a diverse set of Smart Grid (SG) applications, and improves the performance metrics compared to other two well-known schedulers, Proportional Fairness (PF) and Round Robin (RR). The proposed CPb algorithm uses a differentiation technique, applying the Time Domain Scheduler (TDS) and the Frequency Domain Scheduler (FDS), to meet the various SG traffic requirements and types for massive Machin-to-Machine (M2M) devices. Four SG traffic types for each M2M device are used in this study: (1) SG delay sensitive event-driven traffic is used as a SG Distribution Automation (DA), (2) Time driven traffic is used for the other SG types of traffic, including video surveillance, (3) Power quality data, and (4) Periodic Advanced Meter Infrastructure (AMI) data. The CPb results show a significant improvement in the performance metrics compared to the PF and RR schedulers, according to the LTE QoS Class Identifier (QCI) parameters.