gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

Abdullah Al-Halafi, Lokman Sboui, Rawan Naous, Basem Shihada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor's energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named 'green Task-Based Sensing' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.
Original languageEnglish (US)
Title of host publication2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages136-143
Number of pages8
ISBN (Print)9781467399555
DOIs
StatePublished - Sep 8 2016

Fingerprint Dive into the research topics of 'gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks'. Together they form a unique fingerprint.

Cite this