Artificial intelligence inspired energy and spectrum aware cluster based routing protocol for cognitive radio sensor networks

Abstract

A Cognitive Radio Sensor Network (CRSN) is a distributed network of sensor nodes, which senses event signals and collaboratively communicates over dynamically available spectrum bands in a multi-hop mode. All nodes participating in CRSN have to be cognitive of the network environment and autonomous in decision making for resolving issues related to throughput maximization, delay, and energy minimization. Clustering in CRSN is proven to tackle such issues and enlarges the network’s lifetime. However, the existing clustering algorithms designed for WSNs do not consider the CR functionalities and challenges, and CR based networks work on the assumption of unlimited energy. This paper proposes an energy and spectrum aware unequal cluster based routing (ESUCR) protocol intending to resolve the issues of clustering and routing in CRSN. In ESUCR, cluster formation is mainly performed considering the residual energy of the secondary users (SUs) and relative spectrum awareness such that the common data channels for clusters are selected based on the appearance probability of PUs. ESUCR performs energy-efficient channel sensing by deciding the channel state with the statistic previous channel states. The premature death of cluster heads (CHs) is minimized by selecting and rotating the CHs based on intra-cluster channel stability, energy, distance, and neighbor connectivity. During event detection, ESUCR performs energy-efficient data routing towards the sink node by employing hop by hop forwarding through the CHs and primary/secondary gateways. The performance of the proposed ESUCR protocol is proved through extensive simulations and compared to those of the state-of-the-art protocols under a dynamic spectrum-aware data transmission environment.