Judicious data management for sustaining an energy harvesting sensor node

Abstract

Summary Perpetual lifetimes and low maintenance are few of the attractive aspects of sensor nodes that harvest ambient energy. However, their operation depends heavily on the energy profiles of their harvesting source(s). In this work, we study the suitability of energy harvesting sensor (EHS) Nodes, powered using indoor lighting and vibrations, for a simple temperature monitoring application. To help these nodes sustain, we have proposed schemes that allow the nodes to sample and transmit data judiciously. Along with an adaptive sampling based on autoregressive (AR) model, we have proposed a regulating function based transmission scheme that regulates the amount of transmitted data based on the energy available at the node and the characteristics of the data so that even with limited transmissions the fidelity of the data is not lost. With the help of thorough evaluations, we can conclude that an EHS node fares quite well. Results show that adaptive sampling and transmissions based on regulating function not only save energy at the sensor nodes, but they also reduce the amount of data generated and accumulated in a network.

Convergence of cloud, Internet of Things, and big data: New platforms and applications

“…Singh et al 7 carried out investigations into the suitability of energy harvesting sensor (EHS) nodes, powered by indoor lighting and vibrations, for a simple temperature monitoring application. This article proposed an autoregressive (AR) model based adaptive sampling algorithm that switches to different sampling rates and resolutions depending on the energy available at the node and the variations in temperature.…”