## 1 Introduction  
Reducing energy consumption of the mobile nodes extends the network life span which improves the effectiveness of the network. Nodes can also minimize the routing problem experienced within the Cognitive radio ad hoc network (CRAHN). CRAHN is a set of wireless mobile nodes, where each node collaborates to relay data packets to extend the transmission of source nodes beyond their communication zones. A steady and scalable network is ideal [1]. The advancement of technology, distributed computing, spectrum mobility, and the Internet of Things (IoT) has created large data sets requiring more spectrum for data communication. Unfortunately, the spectrum is a scarce resource that is non-deterministic and varies from one sector to another, as illustrated in Figure 1. Figure 1 shows the available channels known as the spectrum holes, which unlicensed users have the privilege to access only when they are idle [2, 3]. When licensed users are detected, the unlicensed users must vacate the spectrum to avoid interfering with the licensed user's transmission. The ad hoc networks exhibit unique characteristics, such as being aware and adaptive to their environment [4]. For example, they can alter their physical layer behavior based on their previous experience and current environmental characteristics. Ad hoc networks are made up of smart and spectrum-agile gadgets that can adjust their configurations based on the spectral environment [5]. Figure 1 depicts the spectrum holes that can be utilized by cognitive users opportunistically when they are idle. Bands with no signal characterize the spectrum holes. These bands are marked with the phrase \"Spectrum holes\" in Figure 1.  
Figure 1 shows the number of bands starting from \(b_{1}\), \(b_{2}\),..., \(b_{k}\), where the green, orange, and blue colors demonstrate the signals in various spectrum bands. The signals notify the secondary users (SUs) whenever the primary user (PU) is about to access the spectrum. The SUs must then find an alternative free spectrum holes to utilize and vacate the current spectrum without interfering with the PUs' activities. This study aims to improve the routing problem and reduce energy consumption and to allow cognitive users to effectively detect spectrum holes and utilize them while the life span of the network is extended due to efficiency in energy consumption. However, the coming of IoT and smart gadgets is increasing the requirements for spectrum and robust quality-of-service (QoS)-aware routing protocols [7]. Cognitive radio technology has emerged as an encouraging solution to address the spectrum challenge. It enables unlicensed users to use the spectrum when it is idle and to vacate the spectrum immediately once a licensed user is detected [8]. This technology is widely utilized in disaster management, vehicular networks, combat, mountainous areas, fire, earthquakes, acoustic underwater networks, forest fire detection, wildlife protection, rescue, and many more hazardous environments. However, mobile nodes in such environments have a limited amount of energy; moreover, this energy can be costly and not renewable [9]. Energy-efficient strategies are necessary to maximize both the network lifespan and the number of data packets transmitted. Various radio spectrum bands are obtainable, such as a global system for mobile GSM, television, wireless local area network (WLAN), military, and LTE that are causing spectral inefficiency whereby the spectrum for cognitive users are congested [10; 11]. From the previous methods utilized by researchers, the principal challenge of CRAHNs is the routing problem, which requires further attention because the present routing protocols that are utilized for conventional networks are not suitable for CRAHNs, since routing paths are affected by node mobility, spectrum mobility, and network partition [12]. There is a need to enhance or modify the existing routing protocols for CRAHNs or design new algorithms.