Improvement of energy conservation using blockchain-enabled cognitive wireless networks for smart cities

被引:11
|
作者
Rani, Shalli [1 ]
Babbar, Himanshi [1 ]
Shah, Syed Hassan Ahmed [2 ]
Singh, Aman [3 ,4 ,5 ]
机构
[1] Chitkara Univ, Inst Engn & Technol, Rajpura 140401, Punjab, India
[2] Calif State Univ Fullerton, Dept Comp Sci, Fullerton, CA 92831 USA
[3] Univ Europea Atlantico, Higher Polytech Sch, C Isabel Torres 21, Santander 39011, Spain
[4] Univ Int Iberoamer, Dept Project Management, Campeche 24560, Mexico
[5] Univ Int Iberoamer, Dept Engn, Arecibo, PR 00613 USA
关键词
ALGORITHM;
D O I
10.1038/s41598-022-16916-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In Smart Cities' applications, Multi-node cooperative spectrum sensing (CSS) can boost spectrum sensing efficiency in cognitive wireless networks (CWN), although there is a non-linear interaction among number of nodes and sensing efficiency. Cooperative sensing by nodes with low computational cost is not favorable to improving sensing reliability and diminishes spectrum sensing energy efficiency, which poses obstacles to the regular operation of CWN. To enhance the evaluation and interpretation of nodes and resolves the difficulty of sensor selection in cognitive sensor networks for energy-efficient spectrum sensing. We examined reducing energy usage in smart cities while substantially boosting spectrum detecting accuracy. In optimizing energy effectiveness in spectrum sensing while minimizing complexity, we use the energy detection for spectrum sensing and describe the challenge of sensor selection. This article proposed the algorithm for choosing the sensing nodes while reducing the energy utilization and improving the sensing efficiency. All the information regarding nodes is saved in the fusion center (FC) through which blockchain encrypts the information of nodes ensuring that a node's trust value conforms to its own without any ambiguity, CWN-FC pick high-performance nodes to engage in CSS. The performance evaluation and computation results shows the comparison between various algorithms with the proposed approach which achieves 10% sensing efficiency in finding the solution for identification and triggering possibilities with the value of alpha = 1.5 and gamma = 2.5 with the varying number of nodes.
引用
收藏
页数:10
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