Swarm-Based Energy Efficient Scheduling for Wireless Sensor Networks

In recent years, wireless sensor networks have become attractive to industries due to their low operational cost and potential productivity gain. Designed to operate on batteries, some devices can operate several years without requiring human intervention. However, scheduling reliable wireless communication becomes challenging when considering the energy consumption of the devices. Furthermore, actual industrial network deployments and data traffic are often unpredictable as they greatly vary depending on the field of application. While application-specific solutions exist, an adaptive and application-agnostic solution is preferred. This work proposes a new wireless scheduling algorithm to address the reliability issue in wireless sensor networks, while considering the energy cost. The algorithm operates as a swarm and optimizes the number of communication resources allocated to each device in a short time. Tested on the IEEE 802.15.4 TSCH communication protocol, the algorithm is compared to the Minimal Scheduling Function (MSF), state of the art of TSCH scheduling. The algorithm highlights a strong performance in terms of packets reception ratio and latency. Furthermore, it shows an increased energy efficiency measured in current consumed per delivered packet.