Energy-aware scheduling of computational and communications tasks on battery-less IoT devices.

The Internet of Things (IoT) vision has enabled the wireless connection of billions of battery-powered devices to the Internet. However, batteries are expensive, bulky, cause pollution and degrade after a few years. Replacing and disposing of billions of dead batteries every year is costly and unsustainable. We posit the vision of a sustainable Internet of Battery-Less Things. We imagine battery-less devices storing small amounts of energy in capacitors, harvested from their environment. Using this energy, these intermittently-powered devices can cooperatively perform sensing, actuation and communication tasks. Existing battery-less technology has many shortcomings. Such devices, usually based on passive RFID and backscatter, only support simple sensing, unable to handle more complex application logic. The goal of this project is to bring battery-less technology to the next level. We envision battery-less devices and networks that support complex sensing and actuation applications. To achieve this, we will investigate a novel energy-aware task scheduler for intermittent devices that intelligently decides which application and network tasks to execute at which time, considering task deadlines, data freshness, expected energy consumption of interconnected tasks and available and expected harvested energy. To further improve performance, cooperative task scheduling extensions to support offloading of computing tasks to powered cloud edge devices will also be investigated.

Keywords:RESOURCE ALLOCATION, SENSOR NETWORKS, INTERNET OF THINGS

Disciplines:Communication networks, Performance modelling, Distributed systems, Networking and communications