Rapid Node Cardinality Estimation in Heterogeneous Machine-to-Machine Networks

Machine-to-Machine (M2M) networks are an emerging technology with applications in various fields, including smart grids, healthcare, vehicular telematics and cities. Heterogeneous M2M contain different types of nodes, e.g., nodes that send emergency, periodic, normal type data. An important problem is to rapidly estimate the number active each node every time frame such a network. In this paper, we design two schemes for estimating cardinalities heterogeneous network T where ? 2 arbitrary integer. Our consist phases- phase 1, coarse estimates computed, 2, these used compute final required accuracy. We analytically derive condition one our can be decide as which possible approaches should minimize its execution time. The expected slots execute energy consumption under analysed. Using simulations, show proposed require significantly fewer compared estimation designed prior work, also, separately executing well-known protocol homogeneous work times types, even though all obtain same