gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks
KAUST DepartmentComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2016-09-08
Print Publication Date2016-04
Permanent link to this recordhttp://hdl.handle.net/10754/622554
MetadataShow full item record
AbstractWireless 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.
CitationAlhalafi A, Sboui L, Naous R, Shihada B (2016) gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks. 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). Available: http://dx.doi.org/10.1109/INFCOMW.2016.7562060.
Conference/Event name35th IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2016