Judicious data management for sustaining an energy harvesting sensor node. (19th September 2020)

• Record Type: Journal Article
• Authors: Singh, Kaumudi; Shukla, Pratyush; S. M., Sachin; Gnani, Nithish K.; T. V., Prabhakar; Kuri, Joy
• Other Names: Awan Irfan guestEditor.; Younas Muhammad guestEditor.; Benbernou Salima guestEditor.; Ogiela Lidia guestEditor.; Leu Fang‐Yie guestEditor.; Fiore Ugo guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 23(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-19
• Subjects: autoregressive models -- data sampling -- data transmission -- energy harvesting sensor node; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5997
• Languages: English
• ISSNs: 1532-0626

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.