A Distributed Unselfish Spectrum Assignment for Smart Microgrid Cognitive Wireless Sensor Networks

Aroua, Sabrine; Korbi, Inès El; Ghamri‐Doudane, Yacine; Saı̈dane, Leı̈la Azouz

doi:10.1109/wcnc.2017.7925719

Cited by 5 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Secondly, the smart grid communications structure shall cover home areas, neighborhood areas, and vast areas. Consequently, it is a fundamentally heterogeneous communication network with several complementary technologies, which requires intelligent devices/terminals to control the communications within individual subarea and the connections between various service ranges [17].…”

Section: Related Workmentioning

confidence: 99%

Cognitive Radio for Smart Grid: A Decentralized Emergency Management Approach

Rajab

Kamel²,

Hamoud

et al. 2022

2022 32nd International Telecommunication Networks and Applications Conference (ITNAC)

View full text Add to dashboard Cite

With the remarkable advancements in wireless technology, the scarcity of the available spectrum has become more severe. Cognitive Radio (CR) technology is introduced as an emerging solution to alleviate the imbalance between spectrum under-utilization and high spectrum demands. CR enables unlicensed users to opportunistically transmit data through spectrum holes in licensed bands. In the context of smart grids, CR has become a key component to improve communication efficiency and spectrum usage. In particular emergency situations, some nodes are prone to failure, however the network must remain connected to the designated destination. In addition, the generated emergency communication and disaster relief cause high load of traffic that in turn will lead to congestion and affect the network coverage and capacity. In this paper, we introduced an efficient CR-based architecture for Smart Grid networks to enhance capacity coverage and scalability in the disaster and emergency case. The architecture is decentralized and consists of a set of clusters that communicate with each other in a secure way through number of gateways. CRT-based group key management has been used to manage the distribution of keys between gateways. In addition, the asymmetric encryption will assure the confidentiality of transmitted packets.

show abstract

Section: Related Workmentioning

confidence: 99%

Cognitive Radio for Smart Grid: A Decentralized Emergency Management Approach

Rajab

Kamel²,

Hamoud

et al. 2022

2022 32nd International Telecommunication Networks and Applications Conference (ITNAC)

View full text Add to dashboard Cite

show abstract

“…Aroua et al 45 presented unselfish distributed channel allocation using a partially observable Markov decision process (POMDP) to improve spectrum utilization for smart microgrid-based CRSNs. Hassan et al 46 proposed the use of unlicensed TVWS spectra for CR operators to guarantee QoS for SG applications.…”

Section: Related Workmentioning

confidence: 99%

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

Ogbodo

Dorrell

Abu‐Mahfouz

2021

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

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.

show abstract

“…Each temperature and humidity sensing unit consists of the data acquisition, the computing capability, the short-range radio transmitter, the data storage, and the power supply [3][4][5][6][7]. AWSNs have been applied in many important areas such as intelligent family, military, automated assistance for the elderly monitors, environmental, multimedia surveillance, and traffic avoidance [8,9].…”

Section: Introductionmentioning

confidence: 99%

Elite Immune Ant Colony Optimization-Based Task Allocation for Maximizing Task Execution Efficiency in Agricultural Wireless Sensor Networks

Zhou

2020

Journal of Sensors

View full text Add to dashboard Cite

The research of agricultural wireless sensor networks (AWSNs) plays an important role in the field of facility agricultural technology. The temperature and humidity nodes in AWSNs are so tiny that they are limited on computation, network management, information collection, and storage size. Under this condition, task allocation plays a key role in improving the performance of AWSNs to reduce energy consumption and computational constraints. However, the optimization of task allocation is a nonlinearly constrained optimization problem whose complexity increases when constraints such as limited computing capabilities and power are undertaken. In this paper, an elite immune ant colony optimization (EIACO) is proposed to deal with the problem of task allocation optimization, which is motivated by immune theory and elite optimization theory. The EIACO uses ant colony optimization (ACO) to combine the clone operator and elite operator together for the optimization of task allocation. The performances of EIACO with different numbers of temperature and humidity sensor nodes and tasks have been compared by both genetic algorithm (GA) and simulated annealing (SA) algorithm. Simulation results show that the proposed EIACO has a better task execution efficiency and higher convergence speed than GA and SA. Furthermore, the convergence speed of EIACO is faster than GA and SA. Therefore, the whole system efficiency can be improved by the proposed algorithm.

show abstract

A Distributed Unselfish Spectrum Assignment for Smart Microgrid Cognitive Wireless Sensor Networks

Cited by 5 publications

References 11 publications

Cognitive Radio for Smart Grid: A Decentralized Emergency Management Approach

Cognitive Radio for Smart Grid: A Decentralized Emergency Management Approach

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

Elite Immune Ant Colony Optimization-Based Task Allocation for Maximizing Task Execution Efficiency in Agricultural Wireless Sensor Networks

Contact Info

Product

Resources

About