A Cross-Layer Approach to Minimize the Energy Consumption in Wireless Sensor Networks

Energy efficiency represents one of the primary challenges in the development of wireless sensor networks (WSNs). Since communication is the most power consuming operation for a node, many current energy-efficient protocols are based on duty cycling mechanisms. However, most of these solutions are expensive from both the computational and the memory resources point of view and; therefore, they result in being hardly implementable on resources constrained devices, such as sensor nodes. This suggests to combine new communication protocols with hardware solutions able to further reduce the nodes’ power consumption. In this work, a cross-layer solution, based on the combined use of a duty-cycling protocol and a new kind of active wake-up circuit, is presented and validated by using a test bed approach. The resulting solution significantly reduces idle listening periods by awakening the node only when a communication is detected. Specifically, an MAC scheduler manages the awakenings of a commercial power detector connected to the sensor node, and, if an actual communication is detected, it enables the radio transceiver. The effectiveness of the proposed cross-layer protocol has been thoroughly evaluated by means of tests carried out in an outdoor environment. 1. Introduction Smart environments are expected to become the main actors of the Next Internet, which will be no longer seen as a means to connect people to services but to access the resources made available by small smart objects, first of all sensors and actuators, adopting the machine-to-machine (M2M) paradigm. This new vision of the Internet fits into the broader concept of the Internet of Things, according to which the everyday objects that surround us will become proactive actors of the global Internet, with the capability of generating and consuming information for advanced applications [1]. Among all the wireless technologies enabling the new vision of the Internet, wireless sensor networks (WSNs) are the ideal choice because sensor nodes are able to self-configure and self-organize. These characteristics make them useful to be deployed even in hostile environments in order to detect the environmental parameters (temperature, light, humidity, etc.) without human intervention. Then, exploiting the wireless channel and the multihop communication among nodes, the collected data are sent to a central processing point or are exploited by user-customized mash-up applications [2]. Other strengths of this technology are represented by the low cost of devices, their small size, and their low power