An adaptive data compression mechanism for Wireless Sensor Networks in the Smart Grid Scenarios

The smart grids (SG) present a new architecture for the generation, transmission, and distribution of electrical energy, combined with new information and communication technologies aimed at guaranteeing the required demand, quality, availability and reliability of energy supply to its consumers. The Smart Meter (SM) is installed in each residence whose functionality is to record information related to consumption and send it to the Electric Power Company (EPC) through a two-way communication infrastructure. However, a large amount of data transmitted by the SG network can cause significant congestion in the communication infrastructure, leading to packet loss, increased latency and other issues affecting decision-making, which must be done in real-time. Thus, this work presents a performance analysis of the two-way communication infrastructure of SG in two experimental scenarios: with and without the application of an adaptive data compression mechanism. The communication infrastructure is presented logically and in practice, where a testbed is deployed using IEEE 802.11 communication technologies on the Message Queuing Telemetry Transport (MQTT) protocol to represent the communication infrastructure and analyze network performance using the Wireshark tool in a real scenario.