A Diamond-based approximation algorithm for the shortest link scheduling in wireless networks under SINR model

The Internet of Things (IoT) is an important technology that is increasingly used in various new applications such as smart cities, smart transportation, mobile healthcare, etc. Link scheduling can effectively reduce latency, improve Quality-of-Service (QoS) and save energy consumption of devices in these networks. In this paper, we study the fundamental problem of shortest link scheduling (SLS) in wireless networks with uniform power assignment and under the Signal-to-Interference-plus-Noise-Ratio (SINR) interference model. We propose an $O\left( {{{\log }_{1 + \varepsilon }}\left( {{d_{{l_{\max }}}}/{d_{{l_{\min }}}}} \right)} \right)$ Diamond-based SLS (DSLS) algorithm, where ϵ > 0, and ${d_{{l_{\max }}}}$ and ${d_{{l_{\min }}}}$ are the length of the longest and shortest link, respectively. We partition the link set into disjoint classes and for each class, schedule the links by partitioning the link deployment plane into small diamonds. Theoretical analysis and simulation results show the correctness and efficiency of the DSLS algorithm.