DFPC: Dynamic Fuzzy-based Primary User Aware clustering for Cognitive Radio Wireless Sensor Networks

Abstract

Clustering-based routing solutions have proven to be efficient for wireless networks such as Wireless Sensor Networks (WSNs), Vehicular Ad Hoc Networks (VANETs), etc. Cognitive Radio WSN (CR-WSN) is a class of WSNs that consists of several resource-constrained Secondary Users (SUs), sink, and Primary Users (PUs). Compared to WSNs, there are several challenges in designing the clustering technique for CR-WSNs. As a result, one cannot directly apply the WSN clustering protocols to CR-WSNs. Developing a clustering protocol for CR-WSNs must address challenges such as ensuring PU protection, and SU connectivity, selecting the optimal Cluster Head (CH), and discovering the optimal cluster size. Present CR-WSN clustering solutions failed to resolve the trade-off among all essential clustering objectives. To address these challenges, this study presents a novel approach called Dynamic Fuzzy-based PU aware Clustering (DFPC) for CR-WSNs. DFPC uses a dynamic approach to discover the number of clusters, a fuzzy-based algorithm for optimal CH selection, and reliable multi-hop data transmission to ensure PU protection. To enhance the performance of CR-WSNs, an effective strategy was designed to define the optimal number of clusters using the network radius and live node. Fuzzy logic rules were formulated to assess the four CR-specific parameters for optimal CH selection. Finally, reliable intra- and intercluster data transmission routes are discovered to protect the PUs from malicious activities. The simulation results showed that the DFPC protocol achieved an improved average throughput of 48.04 and 46.49, a PDR of 93.36 and 84.37, and a reduced delay of 0.0271 and 0.0276 in static and dynamic topologies, respectively, which were better than those of ABCC, ATEEN, and LEACH protocols.

Enhancing Cognitive Radio WSN Communication through Cluster Head Selection Technique

“…The effectiveness of the CSCO protocol in CH selection was validated by comparing its performance with that of traditional protocols, namely ISSMCRP [9], ESAUC [10], sensing-after prediction scheme [18], and Dynamic Fuzzybased PU aware Clustering (DFPC) [19]. Comparative validation of the designed CSCO protocol in CH selection was performed for 1000 rounds.…”

Energy-Efficient and Reliable Routing for Real-time Communication in Wireless Sensor Networks

“…ACo_QoSR [28] aims for routes that meet specific delay and energy residual ratio criteria, selecting forwarders based on residual energy and pheromone values. The lack of consideration for hop count, buffer size and link quality compromises delay and network longevity [31][32].…”

Comparative Study of Radio Resource Distribution Algorithms

“…A widely used logical strategy to implement resource fairness involves the recursive application of the RR scheduling scheme. This iterative approach is designed to ensure an equitable distribution of resources to all users, with the overarching objective of maximizing the average resource allocation rate for all users while adhering to specific fairness criteria [15][16][17][18]. In this context, the term "fair resources" denotes the principle of equitably distributing available resources, such as time slots or frequency bands, among all active users.…”