Paper Info
Title
Sustainable and Efficient Data Collection in Cognitive Radio Sensor Networks
Abstract
<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</bold> ognitive Radio is a promising technology that maximize spectrum efficiency and can apply to Wireless Sensor Networks. This paper proposes a system architecture which introduces enhancements at lower layers of a Software Defined Network of Wireless Sensors Network with Cognitive Radio capabilities for efficient sensors’ power management, energy consuming channel handoffs elimination, efficient spectrum brokerage, and QoS provision in terms of data rate to the sensors’ applications via the SDN flows. The large Wireless Sensors Network is divided into clusters for power efficiency - as sensor operate in lower power - which connect to a cloud-assisted Central Controller. The protocol encompasses an optimal reinforcement learning scheme for efficient spectrum utilization that enables efficient sensors’ data collection, while sustainability issues are satisfied. Software Defined Wireless Sensor Network dynamically adapts to the spectrum and interference conditions on per flow basis and predicts Primary Users’ traffic to totally avoid collision with the licensed users. The paper is concentrated on sustainable solutions for sensors’ data collection by the cluster heads leveraging the Cognitive Radio Network facilities and taking into account the demands of the applications running on the sensors. The Cognitive Radio Sensor Network is considered as large organized on a local basis to extend networks lifetime and allow resource reuse.
Year
DOI
Venue
2019
10.1109/TSUSC.2018.2830704
IEEE Transactions on Sustainable Computing
Keywords
DocType
Volume
Wireless sensor networks,Cognitive radio,Cloud computing,Data collection,Software defined networking,Resource management
Journal
4
Issue
Citations 
PageRank 
1
1
0.37
References 
Authors
0
2
Name
Order
Citations
PageRank
Ioanna Kakalou111.04
Kostas E. Psannis244329.71