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Efficient Routing Protocol for Optimal Route Selection in Cognitive Radio Networks Over IoT Environment

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Abstract

In recent times, Cognitive Radio Networks (CRNS) have been broadly investigated in light of the unceasingly growing demands of the Internet of Things (IoT) applications, paving the path to equipping IoT objects with Cognitive Radio (CR) technology. Thus, the implementation of these two technologies in unison has been attracting research interests. Today, CR technology is implemented in Ad-Hoc Networks (AHNs). This combination has several benefits, namely better coverage, lower costs, and simpler maintenance compared to infrastructure-based networks. Nonetheless, a limited number of researchers have lately paid attention to the area of Quality of Service (QoS) for being one of the key routing metrics adopted to define the optimal paths for the Cognitive Radio Ad Hoc Network (CRAHN). Accordingly, this work recommends the stability of a route in CRAHN and proposes Half -Duplex (HD) CRAHN routing protocol without Common Control Channel (CCC) using the control packets’ multicast transmission, referred to as Stability Based Multipath Downstream Quality Routing Protocol (SMDQRP). Interestingly, many CRN overheads have been reduced in the proposed routing protocol such as avoiding the overhead of transmitting the Route Request Packet (RRQP) over all channels and nodes. To be precise, we allow each node to transmit over all of its available channels instead of using all channels in the network. Further, every necessary calculation is made while the RRQP is being sent from the source to the destination not vice versa. Data transmission in HD mode with path recovery is used to test the proposed protocol, along with a compound accumulative routing metric named Stability Based Multipath Downstream Quality (SMDQ) to select the required QoS paths featured with the highest level of stability and maximal throughput. The path is recovered in data transmission by allowing the nodes in the path to use the already saved available channels between every two consecutive nodes in case of failure of any suggested channel. Moreover, a unique sensing technique based on energy level extracted from the received signals at a CR node along with waveform-based detection is factored in for their suitability to our proposed routing protocol as we aim to solve the problems in Multi-Cast-based Half Duplex Routing Protocol (MC-HDRP). The performance of the newly presented protocol is assessed and compared with the most relevant protocols called Probabilistic and Deterministic Path Selection (PDPS) and MC-HDRP by conducting several related simulation experiments and scenarios with the use of a special technologically advanced simulator based on Java language. Contrary to the MC-HDRP, the simulation’s results demonstrate an explicit significant improvement related to throughput, packet drop ratio, and the number of disconnected networks.

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Data is available upon request from the corresponding author.

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Custom code is available upon request from the corresponding author.

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KD and HK formulated the study idea, developed the protocol, and wrote the article draft. RA, SA, and HB edited the entire article.

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Correspondence to Khalid A. Darabkh.

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Darabkh, K.A., Al-Khazaleh, H.F., Al-Zubi, R.T. et al. Efficient Routing Protocol for Optimal Route Selection in Cognitive Radio Networks Over IoT Environment. Wireless Pers Commun 129, 209–253 (2023). https://doi.org/10.1007/s11277-022-10093-6

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