A Comparative Performance Evaluation of Wake-Up Radio-Based Data Forwarding for Green Wireless Networks

The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. In this paper, we present a comparative performance evaluation of three different data forwarding strategies for green wireless networks, namely, CTP-WUR, GREENROUTES, and WHARP, which have been shown to outperform previous state-of-art solutions. Through GreenCastalia-based simulations we analyze and provide insights into the impact on performance of diverse forwarding design choices, ranging from traditional tree-based routing (CTP- WUR), to end-to-end energy-driven route selection (GREENROUTES), to the use of sophisticated learning models (WHARP). Results show that tree- based routing obtains lesser packet delivery radio than WHARP, thus indicating that including energy harvesting awareness in route selection results in performance advantages. However, the proactive nature of route computation of CTP-WUR results in faster packet delivery and lower energy consumption, requesting further optimization of the cross-layer forwarding of GREENROUTES and WHARP.