Spectrum-aware bio-inspired routing in cognitive radio sensor networks for smart grid applications

2017 ◽  
Vol 101 ◽  
pp. 106-120 ◽  
Author(s):  
E. Fadel ◽  
M. Faheem ◽  
V.C. Gungor ◽  
L. Nassef ◽  
N. Akkari ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Smart Grid ◽  
Cognitive Radio Sensor Networks ◽  
Grid Applications

Secure and reliable surveillance over cognitive radio sensor networks in smart grid

2015 ◽  
Vol 22 ◽  
pp. 3-15 ◽  
Author(s):  
Uthpala Subodhani Premarathne ◽  
Ibrahim Khalil ◽  
Mohammed Atiquzzaman
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Smart Grid ◽  
Cognitive Radio Sensor Networks

scholarly journals Heterogeneous Cognitive Radio Sensor Networks for Smart Grid: Markov Analysis and Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Ling Luo ◽  
Jian Zhou ◽  
Ping Ling ◽  
Sumit Roy ◽  
Zhiyong Chen ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Smart Grid ◽  
Blocking Probability ◽  
Service Rate ◽  
Spectrum Utilization ◽  
Queuing Model ◽  
Markov Analysis ◽  
Cognitive Radio Sensor Networks ◽  
Secondary Systems

Cognitive radio sensor networks (CRSN) have the potential to vastly improve spectrum utilization among heterogeneous applications for smart grid. To date, there has been little queueing theoretic modeling conducted of such systems that provide a quantitative estimate of the benefits from CRSN. We propose a novel queuing model which incorporates service rate and functional heterogeneity on the servers and implement preemptive priority among the varying service classes. Initially, we present a continuous-time Markov chain for performance analysis of CRSN for two colocated cognitive systems with various priority classes and bandwidth requirements. Closed form results for spectrum utilization, blocking probability, and optimal traffic intensities are then derived for the scenario of two heterogeneous secondary systems. A channel packing scheme is then proposed to pack smaller bandwidth users into clusters of adjacent channels to alleviate blockage of users requiring larger bandwidth requirements. Based on the numerical results of benefits of our scheme, we propose a feasible application for smart grid.

Cognitive Radio Sensor Networks in Smart Grid

Smart Grid ◽  
2017 ◽  
pp. 29-51
Author(s):  
Ozgur Ergul ◽  
Oktay Cetinkaya ◽  
Ozgur Baris Akan
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Smart Grid ◽  
Cognitive Radio Sensor Networks

scholarly journals Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid

2021 ◽  
Vol 17 (7) ◽  
pp. 155014772110283
Author(s):  
Emmanuel Ogbodo ◽  
David Dorrell ◽  
Adnan Abu-Mahfouz
Keyword(s):  
Quality Of Service ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Smart Grid ◽  
Sensor Network ◽  
Smart Grids ◽  
Cognitive Radio Sensor Networks ◽  
Cognitive Radio Sensor Network ◽  
Guaranteed Quality

The development of a modern electric power grid has triggered the need for large-scale monitoring and communication in smart grids for efficient grid automation. This has led to the development of smart grids, which utilize cognitive radio sensor networks, which are combinations of cognitive radios and wireless sensor networks. Cognitive radio sensor networks can overcome spectrum limitations and interference challenges. The implementation of dense cognitive radio sensor networks, based on the specific topology of smart grids, is one of the critical issues for guaranteed quality of service through a communication network. In this article, various topologies of ZigBee cognitive radio sensor networks are investigated. Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. The performance of the proposed ZigBee cognitive radio sensor network model with its control algorithms is analyzed and compared with existing ZigBee sensor network topologies within the smart grid environment. The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. The simulation results confirm that the proposed topology model is preferable for sensor network deployment in smart grids based on reduced bit error rate, end-to-end delay (latency), and energy consumption. Smart grid applications require prompt, reliable, and efficient communication with low latency. Hence, the proposed topology model supports heterogeneous cognitive radio sensor networks and guarantees network connectivity with spectrum-awareness. Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.

scholarly journals An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

Sensors ◽  
2015 ◽  
Vol 15 (8) ◽  
pp. 19783-19818 ◽  
Author(s):  
Ibrahim Mustapha ◽  
Borhanuddin Ali ◽  
Mohd Rasid ◽  
Aduwati Sali ◽  
Hafizal Mohamad
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cognitive Radio Sensor Networks
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