## 1 Introduction
Combining a new network structure model with the original energy consumption model, a new method to determine the optimal number of clusters was proposed in [12], and through the AGglomerative NESting (AGNES) algorithm, including: (1) introduction of distance variance, (2) the dual-cluster heads (D-CHs) division of the energy balance strategy, and (3) the node dormancy mechanism, it can achieve a reduction in the network energy consumption decay rate and prolong the network lifetime. In the process of cluster construction, we can also consider the use of principal component analysis [13], fuzzy logic [1], K-means [14], Markov models [15], the introduction of mobile nodes [16; 17], etc., to construct a reliable and secure sensor network [18; 19; 20]. Meanwhile, it is necessary to consider the optimization problem of the information transmission path between the CHs in the clustering process, which must involve the concept of multi-hops [21]. Common path optimization algorithms include the Dijkstra algorithm [22; 23; 24], the ant colony optimization (ACO) algorithm [25], etc. Through the proper path optimization, the phenomenon of premature death of the CHs and information congestion [26] could be alleviated effectively. In addition, a large amount of data is generated during the WSN's environmental monitoring [27]. How to obtain the most complete and effective information possible while minimizing the amount of redundant information is related to the WSN's quality of service (QoS) [28]. How to build a compliant WSN through a reasonable node deployment [17], [29; 30] has also become one of the factors to consider in the protocol. In [31], a clustering technique is proposed that uses the fuzzy c-means clustering method for the formation of clusters and a cluster head is selected based on four parameters: sensor's location within cluster, location with respect to the fusion center (FC), its signal-to-noise (SNR), and its residual energy. In real life, a WSN often faces two problems: (1) There are often some monitoring targets in the monitoring area that have key roles. Compared with other points, these targets often have higher coverage requirements. Therefore, for these points we need to arrange more sensor nodes around them to meet their coverage requirements. (2) With the continuous operation of the WSN, the CH far from the BS tends to die prematurely due to the long transmission distance. Therefore, how to build an energy-efficient and reliable information transmission path between the CHs is also worthy of our attention. It is worth noting that the above two problems are still in [12]. The random node deployment strategy in [12] does not guarantee the obtained information's QoS and thus must not meet the requirement of the QoS for the actual application. In addition, it does not consider the inter-cluster routing mechanism, which will cause some CHs to deplete energy prematurely because of the long transmission distances from the BS. From the perspective of the two aspects above, this paper proposes an energy-efficient clustering routing protocol based on a high-QoS node deployment with an inter-cluster routing mechanism (EECRP-HQSND-ICRM). The basic premise is as follows: For all the monitoring target points with a coverage requirement of two, this paper proposes a series of definition formulas for information integrity, validity, and redundancy and a node deployment strategy based on twofold coverage. Subsequently, in order to satisfy the uniformity of the CH distribution, the BS is divided into four small cells, and the CHs are selected in the respective cells. Finally, combined with the practical application of the WSN, this paper optimizes the Dijkstra algorithm, including: (1) nonessential path neglecting considerations, and (2) a simultaneous introduction of end-to-end weights and path weights, achieving the selection of optimal information transmission paths between the CHs.