Cross-layered and Interactive Techniques for Energy Minimization of M2M Networks
Machine to Machine (M2M) networks are severely constrained by the overall energy available for sensing and communication at sensor nodes. The existing techniques minimize energy focus on specific network components and optimize its energy consumption. This paper explores a unified approach to optimize for energy consumption in the overall M2M network. We consider challenges in the physical communication design, medium access control techniques and network topology of M2M networks that are designed to serve heterogeneous applications. We propose a set of cross-layered techniques specifying the optimal amount of time that each sensor node must transmit, sleep and access the network to minimize overall energy. Subsequently, we propose a dynamic technique to optimize the abovementioned resources for changes in traffic scenarios. We observe the performance of cross-layered and dynamic optimization techniques via numerical and network simulations and show exceptional amount of energy savings.