WLAN Power Save with Offset Listen Interval for Machine-to-Machine Communications

Abstract

Large scale deployment of machine-to-machine (M2M) communication networks hinges on the cost and energy efficient design of the embedded devices. Standard WLAN power save mechanisms, which are designed for human communications, experience performance degradation and unbalanced energy consumptions in M2M communication networks. We develop a novel analytical model that takes into account the fundamentally different network architecture and traffic patterns of M2M communications. Our model accurately characterizes the high contention and long packet delay found in M2M communication networks, while previous models underestimate such measures. To combat such performance decline, we propose a new algorithm that enhances existing power save mechanisms to extend the lifetime of a M2M communication network. We call this the Offset ListenInterval (OLi) Algorithm. The OLi algorithm spreads the M2M traffic evenly with calculated offsets to alleviate network contention and reduce packet delay. Our analytical model is then used to evaluate the energy efficiency of our OLi algorithm and compare with the standard power save mechanisms. Our results show that the proposed OLi algorithm extends the lifetime by up to 40%, and scales up to thousands of nodes in a M2M communication network.