## 1 Introduction  
The need for efficient spectrum utilization [1] has recently brought about the new paradigm of cognitive radio sensor networks (CRSNs). The two major drives toward this paradigm are the underutilization of the spectrum below 3 GHz and the congestion problem in both licensed and unlicensed bands. As challenging as this paradigm may appear, the effort of recent studies such as [2,3] are gradually making this paradigm a reality. Meanwhile, as the World gradually develops into an Internet of Things, the ubiquity of wireless sensor networks (WSNs) is accordingly becoming imperative. This, by implication, further complicates the issue of the congestion of the industrial, scientific and medical (ISM) spectrum and the unlicensed national information infrastructure (UNII), as evidenced by [4, 5, 6]. Notwithstanding the predicted ubiquity of WSNs, other wireless systems such as WiMAX, Bluetooth and Wi-Fi also operate in these bands, along with cordless phones and microwaves. The normal IEEE 802.15.4 standard defines 16 channels, each with a bandwidth of 2 MHz, in the 2.4-GHz ISM band, among which only four are not overlapping with the IEEE 802.11 22-MHz bandwidth channels. It should be noted that these channels sometimes overlap with the channels of IEEE 802.11. If the Wi-Fi deployment uses channels other than 1, 6 and 11, then overlapping will occur. Furthermore, a recent and practical study performed on the co-existence issue showed that, in reality, only three of these channels are actually non-overlapping [7]. In extreme cases where all other networks (e.g., medical sensor networks, security networks, disaster communications, PDAs, Bluetooth devices and many more applications envisioned in the very near future) compete for these four channels, the congestion issue becomes more urgent. The authors of [8,9] have shown that IEEE 802.11 degrades the performance of 802.15.4 when they operate in overlapping bands, and in [7] a highly variable IEEE 804.15.4 performance drop of approximately 41% was demonstrated. Furthermore, as computing/networking heads toward ubiquity, various WSNs will form a great percentage of this phenomenon. The concept of CRSN aims to address this spectrum utilization challenge by offering sensor nodes temporary usage of vacant primary user (PU) spectra via dynamic spectrum access (DSA) with the condition that they will vacate that spectrum once the presence of the incumbent is detected. With the successful implementation of DSA via cognitive radio (CR), other advantages are exploited by the WSN. The most enticing of these advantages are that the node energy can be significantly conserved by the reduction of collisions, which invariably results in the reduction of retransmission of lost packets. Energy conservation can also be achieved by employing nodes that dynamically change their transmission parameters to suit channel characteristics, thus providing full management control of these valuable resources. This practice, in effect, can also enable the coexistence of various WSNs deployed in a spatially overlapping area in terms of communication and resource utilization. Notwithstanding the potential of this concept, the CRSN comes with its own unique challenges. For example, the practical development/implementation of a CR sensor node is still an unsolved issue. Additionally, because the DSA characteristic affects the entire communication framework of a conventional WSN [2], previous protocols proposed for classical WSNs cannot be directly applied to a CRSN, nor can the communication protocols for _ad-hoc_ networks perfectly fit this context due to the resource constraints. Incorporating the idea of DSA into a WSN changes not only the MAC and PHY layers, but also affects all of the communication. However, the fact that WSNs still remain the launchpad for protocol design in CRSNs necessitates a performance study of WSN routing strategies _vis-a-vis_ CRSN requirements [2, 10, 11].