## 2 Background and Related Works  
In this section, we analyze current in-network video processing techniques in wireless networks and discuss the characteristics and problems of existing QoS routing protocols in sensor networks.  
Most of the existing works provide QoS guarantees by properly distributing network traffic, without considering the removal of unnecessary multimedia loads. In-network compression [19] can effectively reduce the number of packets transmitted in the network and guarantee the accurate reconstruction of compressed data at the sink. The work in [20] takes advantage of high spatial correlation of observation retrieved from proximal video sensor to process in-network video through differential coding, which can reduce a lot of redundant data in routing. The problem of how to choose relay nodes with differential coding to reduce redundant multimedia data in a multi-sink environment is taken into account in [20]. A centralized clustering algorithm is proposed in [21], in which cluster heads use a hybrid CS mechanism to transfer data to the sink through a backbone tree. However, it ignores the situation that sparse random matrices can be used in each cluster to reduce the number of packets transmitted. Ref. [22] presents a cluster-based data aggregation method with sparse random measurements in a star topology-based sensor network. Unfortunately, the cluster structure of star topology may lead to an increase in intra-cluster energy consumption. CBCA [23] is a greedy clustering algorithm on top of a logical chain to minimize the average compression ratio of all clusters. This work provides a valuable reference for hierarchical compressive data gathering in sensor networks.  
Most of the prior works on QoS routing protocols in wireless sensor networks are designed to support two performance metrics: delay and reliability [24; 25; 26; 27]. MMSPEED [28] takes a cross-layer design approach to distinguish the communication flows with different delay and reliability demands and provide end-to-end QoS guarantees. The primary problem for MMSPEED is that it lacks control for redundant data, so there is an increase in communication congestion. In [29], SCEEM is proposed for CRSNs that jointly overcomes the formidable limitations of energy and spectrum without damaging multimedia quality. However, the process of data transmission may interfere with and even affect the primary users' transmission. EARQ [30] can provide real-time, reliable and energy-aware data delivery in industrial sensor networks, where the path selection depends on the local information estimation value. QMOR [25] is a QoS-aware multi-sink opportunistic routing protocol working together with differential coding for multimedia sensor networks. The authors in [31] propose a QoS and energy-aware dynamic routing protocol for multimedia sensor networks. This scheme creates multiple paths within an inclination angle and a certain range around the direction to the destination. Although these two protocols can deliver multimedia information under QoS constraints, they do not support CR and are not directly tailored for CVSNs.  
Despite the reduction of communication cost with in-network video processing, there are still many challenges in delivering data subject to QoS constraint. An effective way to improve network performance is to combine DCS with QoS routing. After studying relevant literature, we realize that there is no comprehensive study concerning the joint design of DSC and spectrum-aware QoS routing in CVSNs.