A Balancing Energy Efficiency and Security in CR-LoRaWAN Ecosystems
Abstract
Cognitive Radio-enabled Long Range Wide Area Networks (CR-LoRaWAN) plays an important role in IoT applications. However, due to the limitations of devices and dynamic scheduling mechanisms of the channels, there is still a challenge to balance energy efficiency against security. This paper proposes two developed algorithms that address these challenges: Algo A and Algo B. Algo A ensures key security by mitigating nonce generation vulnerabilities through the replacement of insecure random numbers with prime numbers. Algo B develops this basis by further improving energy efficiency through optimization in session key generation and device management, adding security to it. Both the algorithms incorporate prime numbers in their session key generation that are verified by the Rabin-Miller test and the Sieve of Eratosthenes, with incorporated solar energy harvesting to give a longer life to such devices. Cognitive radio technology is integrated into it for dynamic and intelligent channel selection. Extensive simulations demonstrate that Algo A is much better at handling data with key security, while Algo B outperforms Algo A on energy consumption reduction by 20% and enhancement of overall network security by 15%. These results reveal that Algo B has a better trade-off between security and energy efficiency; hence, Algo B is more suitable for practical deployment. The work further enhances the sustainability and reliability of CR-LoRaWAN networks, especially in resource-constrained environments.
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