## 2 Related Works
In this method, only part of the nodes closer to the target path would be woken up and participate in the tracking. The simulation results demonstrated that the average energy consumption could be reduced effectively. These studies designed different sleep/wake modes for application scenarios to balance energy consumption and performance, but they did not limit the switching between the two states. We note that switching between the sleep and wakeup states also takes a lot of energy and time, so this paper introduces a wakeup threshold to reduce the frequency of state switching [19]. In the wakeup threshold mechanism, wakeup is performed after a certain amount of information has been accumulated, which will also increase the average latency to a certain extent. Therefore, it is necessary to introduce a reasonable access control mechanism to mitigate this adverse effect. The tail --drop method is the default congestion management technique for wireless networks, which adopts the principle of first --come -- first -- serve. When the cache is full, newly arrived packets will be dropped directly [20]. This method can only react when congestion occurs in the system, and cannot prevent congestion from occurring. Random early detection (RED) is a widely used method of queue management that can effectively prevent system congestion [21; 22]. In [23], a variety of queueing models were established and analyzed according to whether there were RED and tail --drop mechanisms or priority packets. Numerical results showed that dividing packets into multiple priorities could improve the quality of service of the network, and the introduction of RED and tail --drop mechanisms could effectively alleviate congestion. However, this RED method required two thresholds (minimum and maximum thresholds) and a maximum probability for joint regulation, which is more complex to implement. In [24], considering the ignorance of queue information, a probabilistic access method for wireless sensor networks was proposed to control system congestion. When a sensor was in the sleep state, it received newly arrived packets with probability \(p\); when it was in the wakeup state, it received the newly arrived packets with probability \(q\). Based on this strategy, a Markov -- chain model was constructed, and numerical results verified its effectiveness. However, this method of using a fixed value as the access probability was difficult to adapt to the changing network environment. In [25], an access control strategy with a dynamic access threshold was proposed. A reasonable dynamic access threshold was set according to different packet arrival rates to constrain the access behavior of packets. Numerical experiments verified the effectiveness of the strategy in energy saving. This method was similar to the wakeup threshold used in this paper; however, if congestion is to be effectively avoided, other mechanisms need to be introduced to regulate it. Therefore, we propose a dynamic access probability mechanism that will reduce access probability when many packets are retained in the system based on the influence of real -- time queue length rather than the packet arrival rate. Compared with the RED method used in literature [23], the dynamic access probability mechanism used in this paper requires fewer control parameters and is simpler to implement. Compared with the fixed access probability method in [24], the dynamic access probability mechanism is more suitable for dynamically changing network environments. Compared with the method in [25], our method can alleviate congestion further. In summary, this paper studies the packet forwarding mechanism of the CH in UWSNs with different latency sensitivities. Taking into account the trade--off between latency and energy consumption, wakeup threshold and dynamic access probability are introduced to control the CH's state switching and packet access behavior, respectively.