# An Accuracy-Aware Energy-Efficient Multipath Routing Algorithm for WSNs
## 1 Introduction  
Wireless sensor networks (WSNs) are composed of many small, energy-limited, and low-cost sensor nodes deployed in a certain area, forming a multihop self-organizing network system through wireless communication. In fields like industrial production or safety monitoring, WSN applications have high requirements for data quality. In these applications, the reliability of data transmission and the accuracy of received data directly affect the response and handling of user applications to emergencies such as fire or toxic gas leakage. However, in environments like factories or outdoors, the wireless channels used in WSN communication exhibit the characteristics of unreliability, time variation, and susceptibility to interference [1, 2]. These characteristics pose challenges in ensuring the reliability of the transmission path and the accuracy of received data, leading to widespread concerns in recent years [3]. An important technology for ensuring transmission reliability lies in the deployment of highly reliable routing algorithms [4, 5, 6], with multipath routing standing out as a widely adopted strategy to improve the reliability of data transmission in WSNs. In contrast to single-path routing, multipath routing augments data transmission reliability by establishing multiple paths between source and destination nodes. To achieve greater throughput, enhanced failure resilience, faster mobility and reduced latency, coding-based multipath routing schemes have garnered increasing research attention in recent years [7, 8, 9]. These routing schemes typically segment the original data into multiple coding packets in uniform size, containing some redundant information. The coding packets are then distributed across multiple paths for transmission. Intermediate nodes process the data through techniques such as data aggregation or compression to reduce the number of packets. Once a certain quantity of coding packets is collected, the destination node recovers the original data through decoding and data fusion [10]. However, it is worth noting that the aggregation of multiple coding packets at intermediate or sink nodes along the path may lead to a reduction in data accuracy [11; 12]. This reduction in accuracy can have repercussions on the result of data analysis or decision-making. Consequently, maintaining data accuracy poses a challenge for coding-based multipath routing. To address this challenge, current research efforts can be categorized into two main approaches. One approach focuses on improving the routing schemes to reduce the number of data copies by reasonably selecting or minimizing the transmission paths. In the literature [13], a combination of multipath routing and a tree-based aggregation algorithm was employed. During path construction, a node is selected and remains as the first node of aggregation, and convergence proceeds step by step from this node to the destination. In the literature [14], the authors combined the clustering method with multipath routing and utilized spatio-temporal correlation to aggregate sampled data at the source node to reduce the volume of transmitted data. The second approach to improving aggregation algorithms is to guarantee data accuracy by reducing the accuracy loss. [PERSON] and [PERSON] proposed a Scalable Counting (SC) algorithm to guarantee data accuracy [11]. The SC algorithm inherits the idea of the Linear Counting (LC) algorithm, which incorporates a hash function with arrays to reduce the accuracy loss caused by aggregation calculation. In the literature [15], a routing tree is established for data transmission. It calculates the maximum allowable data accuracy loss of each subtree in proportion to the size of the routing tree. The data compression ratio at each node is then determined based on the maximum allowable accuracy loss to ensure accuracy.