CARD: Context-Aware Resource Discovery for mobile Internet of Things scenarios

Abstract

The occurrence of short but recurrent opportunistic contacts between static infrastructure and mobile devices largely characterizes recent Internet of Things (IoT) applications for Smart Cities and Smart Buildings scenarios. In order to efficiently exploit such existing communication opportunities to access services, share and collect data, IoT applications cannot rely on standard discovery mechanisms that periodically probe the environment to discover resources. Discovery protocols resilient to different contact opportunities and able to optimize energy consumption when device contacts are not present are therefore required in order to avoid waste of energy especially in battery operated user devices. Additionally, such new discovery protocols need to optimize the time available for communication operations, while being able to adjust to application requirements, and balance energy consumption with respect to latency for contacts discovery. To this aim, we introduce CARD, a Context Aware Resource Discovery framework that leveraging Q-Learning techniques extends the functionalities of asynchronous neighbor discovery protocols, while being capable to reduce energy wastage and discovery latency. Simulation results show that CARD performs better than existing approaches and is resilient to a variety of real scenarios characterizing Smart Cities and Smart Building deployments.