Data filtering in context-aware multi-agent system for machine-to-machine communication

Abstract

Energy efficiency is an important aspect of Machine-to-Machine (M2M) systems since large number of devices is not connected to unlimited power supply. To tackle this problem, in our context-aware multi-agent system for M2M communication devices are in low-energy mode whenever they do not have any tasks to perform. Context information is exchanged between devices so that each device knows when other devices will be available for communication. On each device in the system, agents are deployed which exchange context information and adjust their wake-up times. In this paper we focus on decreasing energy consumption of M2M Devices which collect measurement data and forward it to back-end system. A filtering algorithm is developed to find repetitive data and to increase the interval for the next transmission. We assumed that when data values are similar to the previously observed values, it is not necessary to forward them to the gateway and back-end system so often. This approach was implemented on Libelium Waspmote devices and showed significant decrease in energy consumption during the period of 24 h.