A  Novel Clustering Scheme For Heterogeneous Cognitive Radio Wireless Sensor Networks

Gyanendra Prasad Joshi; Sudan  Jha

doi:10.16925/2357-6014.2020.03.04

A Novel Clustering Scheme For Heterogeneous Cognitive Radio Wireless Sensor Networks

Research Articles

https://doi.org/10.16925/2357-6014.2020.03.04

Gyanendra Prasad Joshi Ver Biografía

Sejong University,

Sudan Jha

University, Panjab

Introduction: This article is the product of the research “Learning-based Spectrum Analysis and Prediction in Cognitive Radio Sensor Networks”, developed at Sejong University in the year 2019.

Problem: Most of the clustering schemes for distributed cognitive radio-enabled wireless sensor networks consider homogeneous cognitive radio-enabled wireless sensors. Many clustering schemes for such homogeneous
cognitive radio-enabled wireless sensor networks waste resources and suffer from energy inefficiency because of the unnecessary overheads.

Objective: The objective of the research is to propose a node clustering scheme that conserves energy and prolongs network lifetime.

Methodology: A heterogeneous cognitive radio-enabled wireless sensor network in which only a few nodes have a cognitive radio module and the other nodes are normal sensor nodes. Along with the hardware cost, the
proposed scheme is efficient in energy consumption.

Results: We simulated the proposed scheme and compared it with the homogeneous cognitive radio-enabled wireless sensor networks. The results show that the proposed scheme is efficient in terms of energy
consumption.

Conclusion: The proposed node clustering scheme performs better in terms of network energy conservation and network partition.

Originality: There are heterogeneous node clustering schemes in the literature for cooperative spectrum sensing and energy efficiency, but to the best of our knowledge, there is no study that proposes a non-cognitive
radio-enabled sensor clustering for energy conservation along with cognitive radio-enabled wireless sensors.

Limitations: The deployment of the proposed special device for cognitive radio-enabled wireless sensors is complicated and requires special hardware with better battery powered cognitive sensor nodes.

Keywords: CR-WSNs, cognitive radio-enabled sensors, energy efficiency, energy conservation

G. P. Joshi, S. Y. Nam, and S. W. Kim, “Cognitive radio wireless sensor networks: Applications, challenges and research trends,” Sensors (Switzerland), vol. 13, no. 9, pp. 11196–11228, 2013. [Online]. doi: 10.3390/s130911196

S. Salim, S. Moh, D. Choi, and I. Chung, “An Energy-Efficient and Compact Clustering Scheme with Temporary Support Nodes for Cognitive Radio Sensor Networks,” Sensors, vol. 14, no. 8, pp. 14634–14653, Aug. 2014. [Online]. doi: 10.3390/s140814634.

G. P. Joshi and S. W. Kim, “A survey on node clustering in cognitive radio wireless sensor networks,” Sensors (Switzerland), vol. 16, no. 9, pp. 1465–1465, 2016. [Online]. doi: 10.3390/s16091465

S. Wang, H. Liu, and K. Liu, “An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 11, no. 10, pp. 1–7, Oct. 2015. [Online]. doi: 10.1155/2015/136948.

B. Jan, H. Farman, H. Javed, B. Montrucchio, M. Khan, and S. Ali, “Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey,” Wireless Communications and Mobile Computing, vol. 2017, no. 6457942, pp. 1–14, Oct. 2017. [Online]. doi: 10.1155/2017/6457942.

Y. Yang, L. Dai, J. Li, S. Mumtaz, and J. Rodriguez, “Optimal spectrum access and power control of secondary users in cognitive radio networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 1, pp. 98–98, May 2017. [Online]. doi: 10.1186/s13638-017-0876-5.

D. Wu, Y. Cai, L. Zhou, and J. Wang, “A cooperative communication scheme based on coalition formation game in clustered wireless sensor networks,” IEEE Transactions on wireless commu-nications, vol. 11, no. 3, pp. 1190–1200, 2012

H. Zhang, Z. Zhang, H. Dai, R. Yin, and X. Chen, “Distributed spectrum-aware clustering in cognitive radio sensor networks,” in IEEE Global Telecommunications Conference-GLOBECOM 2011, 2011, pp. 1–6

M. Ozger and O. B. Akan, “Event-driven spectrum-aware clustering in cognitive radio sen-sor networks,” in IEEE INFOCOM, Turin, Italy, 2013, pp. 1483–1491. [Online]. doi: 10.1109/INFCOM.2013.6566943.

G. P. Joshi, “Clustering in Cognitive Radio-based Wireless Sensor Networks,” in 2016 International Conference on Advanced Computing, Communications and Information Science, Cebu, Philippines., May 2016, vol. 1, pp. 99–99, Accessed: Apr. 22, 2020. [Online]. Available: http://kasdba.org /icacci2016/proceedings/ICACCI2016_Proceedings.pdf.

Z. Qu, Y. Xu, and S. Yin, “A novel clustering-based spectrum sensing in cognitive radio wireless sensor networks,” in IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, Shenzhen, China, 2014, pp. 695–699.

A. Rauniyar and S. Y. Shin, “A Novel Energy-Efficient Clustering Based Cooperative Spectrum Sensing for Cognitive Radio Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 11, no. 6, pp. 1–8, Jun. 2015. [Online]. doi: 10.1155/2015/198456.

M. A. S. Cuervo and J. A. M. Lara, “Prototipo de plataforma para vigilancia de inmuebles rurales usando computación en la nube y supervisión con drones,” Ingeniería Solidaria, vol. 14, no. 24, pp. 3–17, Jan. 2018. [Online]. doi: 10.16925/in.v14i24.2160

D. F. G. Triana, C. E. M. Marín, and P. A. G. García, “Lenguaje de dominio especifico para configuración de dispositivos de redes,” Ingeniería Solidaria, vol. 12, no. 20, pp. 83–94, Oct. 2016. [Online]. doi: 10.16925/in.v19i20.1417.

G. Joshi and S. Kim, “A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks,” Sensors, vol. 16, no. 9, pp. 1465–1465, Sep. 2016. [Online]. doi: 10.3390/s16091465.

V. Srividhya and T. Shankar, “Energy proficient clustering technique for lifetime enhancement of cognitive radio–based heterogeneous wireless sensor network,” International Journal of Distributed Sensor Networks, vol. 14, no. 3, p. 1550147718767598, Mar. 2018. [Online]. doi: 10.1177/1550147718767598

S. Salim, S. Moh, D. Choi, and I. Chung, “An energy-efficient and compact clustering scheme with temporary support nodes for cognitive radio sensor networks,” Sensors (Switzerland), vol. 14, no. 8, pp. 14634–14653, Aug. 2014. [Online]. doi: 10.3390/s140814634.

R. M. Eletreby, H. M. Elsayed, and M. M. Khairy, “CogLEACH: A spectrum aware clustering pro-tocol for cognitive radio sensor networks,” in 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Jun. 2014, pp. 179–184. [Online]. doi: 10.4108/icst.crowncom.2014.255370

S. Kumar and A. K. Singh, “A localized algorithm for clustering in cognitive radio networks,” Journal of King Saud University - Computer and Information Sciences, vol. In press, pp. 1–8, Apr. 2018. [Online]. doi: 10.1016/j.jksuci.2018.04.004.

D. Zhang et al., “Energy-Harvesting-Aided Spectrum Sensing and Data Transmission in Heterogeneous Cognitive Radio Sensor Network,” IEEE Transactions on Vehicular Technology, vol. 66, no. 1, pp. 831–843, Jan. 2017. [Online]. doi: 10.1109/TVT.2016.2551721

G. A. Shah, F. Alagoz, E. A. Fadel, and O. B. Akan, “A Spectrum-Aware Clustering for Efficient Multimedia Routing in Cognitive Radio Sensor Networks,” IEEE Transactions on Vehicular Technology, vol. 63, no. 7, pp. 3369–3380, Sep. 2014. [Online]. doi: 10.1109/TVT.2014.2300141

M. J. Handy, M. Haase, and D. Timmermann, “Low energy adaptive clustering hierarchy with deterministic cluster-head selection,” in 2002 4th International Workshop on Mobile and Wireless Communications Network, MWCN 2002, 2002, pp. 368–372. [Online]. doi: 10.1109/MWCN.2002.1045790.

C. Cordeiro, K. Challapali, D. Birru, and S. Shankar, “IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios,” vol. 1, no. 1, pp. 38–47, 2006.

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G. Prasad Joshi and S. Jha, “A Novel Clustering Scheme For Heterogeneous Cognitive Radio Wireless Sensor Networks”, ing. Solidar, vol. 16, no. 3, Sep. 2020, doi: 10.16925/2357-6014.2020.03.04.

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Vol. 16 No. 3 (2020)

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2020-09-01

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