Context-Aware Machine to Machine Communications in Cellular Networks

Cellular network based Machine-to-Machine (M2M) communications have been growing rapidly in recent years, being used in a wide range of services such as security, metering, health, remote control, tracking and so on. A critical issue that needs to be considered in M2M communications is the energy efficiency, typically the machines are powered by batteries of low capacity and it is important to optimize the way the power is consumed. In search of better M2M systems, we propose a context-aware framework for M2M communications so the machine type communication (MTC) devices dynamically adapt their settings depending on a series of characteristics such as data reporting mode and quality of service (QoS) features so higher energy efficient is achieved, extending the operating lifetime of the M2M network. Simulations were performed with four commonly used M2M applications: home security, telehealth, climate and smart metering, achieving considerable energy savings and operating lifetime extension on the network. Thus, it is shown that contexts play an important role on the energy efficiency of a M2M system.