M2M data aggregation over cellular networks: signaling-delay trade-offs

Abstract

Machine to machine (M2M) services are expected to have a compelling penetration in cellular networks. On account of predicted invading numbers of M2M devices, with restricted data needs, the resulting network signaling load poses a great challenge to cellular operators. Data aggregation is an attractive approach to deal with this situation; each aggregator node collects measurements from a group of M2M devices over a capillary network and relays the aggregated data over the cellular access network. In this paper, we conduct a detailed experimental study using state-of-the-art drive testing equipment in order to capture and analyze the impact of M2M data aggregation on signaling overhead in cellular networks with focus on static M2M devices such as smart meters and monitoring sensors. We complement this study with an analytical evaluation to quantify the trade-off between M2M data transmission delay and level of aggregation. Moreover, a case study is presented which provides practical insights on the feasibility, gains, and potential problems of implementing aggregation to reduce network signaling load for M2M smart meters.