Abstract Wireless sensor networks (WSNs) require support for differentiated services across multiple business lines and efficient resource utilization across the entire network. QoS routing is one of the key technologies for solving this problem. Based on the analysis of the QoS routing problem in WSNs, this paper extends the existing ant colony algorithm and proposes a distributed QoS routing algorithm that combines the minimum energy consumption and minimum hop count information of path nodes. A simulation model is also established. Simulation results show that, compared with traditional QoS routing algorithms, this algorithm can better support the allocation of resource requirements for different business lines under mixed business modes with different proportions, achieving balanced energy consumption across the entire network. Furthermore, it also has good adaptability to WSNs. Keywords Wireless sensor network; Quality of service; Network model; Ant colony algorithm 1. Introduction Wireless sensor network consists of a large number of small sensor nodes. The nodes have limited energy and limited data sensing, information processing and wireless communication capabilities. The nodes are connected in a wireless multi-hop decentralized manner. The network topology is dynamically variable. They sense, collect and process information or events of target objects in the coverage area through mutual cooperation. It has flexible deployment, nodes close to the target, can achieve high-precision sensing, supports multi-node data aggregation and fusion, can achieve "quantity for quality", and supports multi-user multi-task concurrent operation. It has a wide range of application potential and is one of the current research hotspots in the field of computer science. However, how to efficiently utilize node energy to maximize the network life cycle is the primary challenge faced by wireless sensor network. With the deepening of wireless sensor network applications, different services have put forward different requirements for the quality of service (QoS) of wireless sensor network [1]. In recent years, some experts and scholars have proposed some QoS routing protocols, most of which only focus on 1 to 2 parameters. This paper proposes a novel QoS route discovery method based on the ant colony algorithm, solving the NP-hard problem of QoS routing with multiple independent parameters, while maximizing the lifetime of wireless sensor networks. 2. Network Requirements and Network Model 2.1 Network Requirements In the network layer of wireless sensor networks, data distribution modes are analyzed. These are mainly divided into three modes: query-driven, event-driven, and continuous transmission. The query-driven mode is initiated by the observation node, and the sensor node matching the query sends the sensed data to the observation node, which is a one-to-many communication. This mode is often used in interactive scenarios, emphasizing timeliness and reliability of data transmission. The event-driven mode is initiated by the sensor node, which immediately reports to the observation node after discovering an event of interest, which is a many-to-one communication. This mode is often used in event detection scenarios, also emphasizing timeliness and reliability of data transmission. Data traffic is bursty, prone to congestion, and node data has high redundancy. The continuous transmission mode, also known as the periodic transmission mode, is agreed upon by both parties, where the sensor node periodically reports the sensed data to the observation node, which is a many-to-many communication. This mode is often used in data reporting scenarios with predefined rates. If the transmitted data is real-time data, such as voice, image or video, the focus is on transmission delay and bandwidth. If it is non-real-time data, such as temperature, humidity or air pressure, the focus is on reliability [2]. Reliability and real-time performance are still the main performance evaluation indicators of sensor networks. However, from the perspective of the three data distribution modes, the data between nodes is based on non-end-to-end data transmission, and there is a lot of redundancy in the data. In the transmission process, aggregation or fusion methods are often required. Therefore, statistical QoS metrics can better reflect the characteristics of network data transmission, such as defining the packet loss rate, delay or random distribution of transmission bandwidth under a certain fusion rate. Research on Routing Protocols for Wireless Sensor Networks Based on QoS (Full Text Download)