Investigation on IMCP based clustering in LTE-M communication for smart metering applications

Abstract

Machine to Machine (M2M) is foreseen as an emerging technology for smart metering applications where devices communicate seamlessly for information transfer. The M2M communication makes use of long term evolution (LTE) as its backbone network and it results in long-term evolution for machine type communication (LTE-M) network. As huge number of M2M devices is to be handled by single eNB (evolved Node B), clustering is exploited for efficient processing of the network. This paper investigates the proposed Improved M2M Clustering Process (IMCP) based clustering technique and it is compared with two well-known clustering algorithms, namely, Low Energy Adaptive Clustering Hierarchical (LEACH) and Energy Aware Multihop Multipath Hierarchical (EAMMH) techniques. Further, the IMCP algorithm is analyzed with two-tier and three-tier M2M systems for various mobility conditions. The proposed IMCP algorithm improves the last node death by 63.15% and 51.61% as compared to LEACH and EAMMH, respectively. Further, the average energy of each node in IMCP is increased by 89.85% and 81.15%, as compared to LEACH and EAMMH, respectively.