Multi-Objective Optimization of Orchestra Scheduler for Traffic-Aware Networks

Highlights What are the main findings? OPTIMAOrchestra_ch4 achieves 0.72 mA current consumption with 100% reliability in static networks. The inmobile networks used in this study, i.e., both OPTIMAOrchestra variants, maintain 100% reliability with 6.36 mA current consumption. What is the implication of the main finding? The proposed scheduler enhances network efficiency, balancing latency-energy trade-offs effectively. It supports large-scale, heterogeneous network deployments, crucial for the development of robust smart city infrastructures.Highlights What are the main findings? OPTIMAOrchestra_ch4 achieves 0.72 mA current consumption with 100% reliability in static networks. The inmobile networks used in this study, i.e., both OPTIMAOrchestra variants, maintain 100% reliability with 6.36 mA current consumption. What is the implication of the main finding? The proposed scheduler enhances network efficiency, balancing latency-energy trade-offs effectively. It supports large-scale, heterogeneous network deployments, crucial for the development of robust smart city infrastructures.Abstract The Internet of Things (IoT) presents immense opportunities for driving Industry 4.0 forward. However, in scenarios involving networked control automation, ensuring high reliability and predictable latency is vital for timely responses. To meet these demands, the contemporary wireless protocol time-slotted channel hopping (TSCH), also referred to as IEEE 802.15.4-2015, relies on precise transmission schedules to prevent collisions and achieve consistent end-to-end traffic flow. In the realm of diverse IoT applications, this study introduces a new traffic-aware autonomous multi-objective scheduling function called OPTIMAOrchestra. This function integrates slotframe and channel management, adapts to varying network sizes, supports mobility, and reduces collision risks. The effectiveness of two versions of OPTIMAOrchestra is extensively evaluated through multi-run experiments, each spanning up to 3600 s. It involves networks ranging from small-scale setups to large-scale deployments with 111 nodes. Homogeneous and heterogeneous network topologies are considered in static and mobile environments, where the nodes within a network send packets to the server with the same and different application packet intervals. The results demonstrate that OPTIMAOrchestra_ch4 achieves a current consumption of 0.72 mA while maintaining 100% reliability and 0.86 mA with a 100% packet delivery ratio in static networks. Both proposed Orchestra variants in mobile networks achieve 100% reliability, with current consumption recorded at 6.36 mA. Minimum latencies of 0.073 and 0.02 s are observed in static and mobile environments, respectively. On average, a collision rate of 5% is recorded for TSCH and RPL communication, with a minimum of 0% collision rate observed in the TSCH broadcast in mobile networks. Overall, the proposed OPTIMAOrchestra scheduler outperforms existing schedulers regarding network efficiency, time, and usability, significantly improving reliability while maintaining a balanced latency-energy trade-off.