Energy-accuracy aware active node selection in wireless sensor networks

Khudonogova, Liudmila I.; Muravyov, Sergey V.

doi:10.1109/sibcon.2016.7491835

Cited by 1 publication

(1 citation statement)

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“…They proposed optimization models based on both primary points and perimeter coverage model to optimize both the coverage and the lifetime of WSNs. Some other approaches exploit the spatial correlation among the sensor data for making sleep/active schedule in order to increase the network lifetime [5,6,7,8,9]. In [5] the base station divides the nodes to N sets based on closeness factor.…”

Section: Literature Reviewmentioning

confidence: 99%

Sensor Activity Scheduling Protocol for Lifetime prolongation in Wireless Sensor Networks

Hussein

Idrees

2017

KJAR

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Abstract:In Wireless Sensor Network (WSN), the dense sensor nodes deployment in the sensing field can be exploited in conserving the energy of the whole network, where the data of these nodes can be highly correlated. Therefore, it is necessary to turn off the unnecessary nodes that sense similar sensor readings so as to reduce the redundant sensed readings and decrease the communication overhead thus extend the WSN lifetime. This article suggests a Sensor Activity Scheduling (SAS) protocol for lifetime improvement of WSNs. SAS works in a periodic way. It exploits the spatial correlation among sensed sensor data in order to produce the best sensor activities schedule in WSNs. SAS composed of three phases: data collection, decision-based optimization, and sensing. SAS measures the similarity degree among the sensed data that collected in the first phase. It makes a decision of which sensors stay active during the sensing phase in each period and put the other nodes into low power sleep whilst keeping a good accuracy level to the received data at the sink to conserve the power and enhance the lifetime of the WSN. Several experiments based on real sensed data and by using OMNeT++ simulator demonstrate that SAS can save energy and extend the WSN lifetime efficiently compared with the other methods.

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Section: Literature Reviewmentioning

confidence: 99%