# A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks
## 2 QoS Control Algorithms
### Related Works  
Many studies have been conducted on the different aspects of QoS of sensor networks, such as power-saving [11; 12; 13; 14; 15; 16; 17; 18; 19], routing [20; 21; 22; 23; 24; 25; 26], throughput of networks [27], enhancement performance [28; 29] and coverage [30; 31; 32], and. The main goal of this study was to autonomously control the number of active sensors. Considering that the sensor network may be in a harsh environment, a feasible approach must be able to reach the goal quickly, have strong robustness, and power-saving properties to cope with the harsh network environment. Figure 3: Finite-state machine in the ACK algorithm. There are two types of distributed control that use finite state automata to control the number of active sensors: (1) Gur Game-based and (2) random access-based algorithms. In the Gur Game, when the number of active sensors (QoS) reaches the target value, the sensor does not change its state, resulting in uneven power usage of the sensors. In [5], the network lifetime is defined as when the power of the first sensor node is exhausted, and the lifetime ends. In [6], the system begins to execute until the number of active sensors cannot maintain the target value and the network lifetime ends. In [11; 12; 13; 14; 15; 16; 17; 18; 19], the authors aim to solve the problem of sensor power imbalance and maximize the lifetime of the network system regardless of the definition. To solve the problem of the Gur Game in terms of power imbalance, the mechanism of using sensors to exchange states at a predetermined time can improve the network lifetime [12]. However, the sensor undergoes state exchange without considering the remaining power of the sensors and does not overcome the power imbalance problems. Therefore, in [13], the authors improved the state transition strategy in the finite state machine and modified the reward function for the relationship between QoS and the target value, aiming to speed up the convergence speed and make the power of the sensor even. In [14], the authors proposed a new adaptive method for QoS and energy management in IEEE 802.15.4 networks, called the \"skip game\", which aims to maintain a trade-off between QoS and extending the lifetime of networks. In [15], the authors proposed a QoS control algorithm called the Gureen Game. A Gureen Game divides the sensor state into active, standby, and sleep states. The standby state is the same as the Gur Game sleep state, whereas the sleep state turns off all of the functions of the sensor depending on whether the QoS is too high or too low. Adjust the reward probability of the situation. Each sensor uses a timer to change its state to achieve power-saving effects. Similar to the Gureen Game, in [16], the sensor state is divided into \(T_{1}\), \(T_{2}\), \(R\), and S states, and the sensor in the \(S\) state will turn off all functions, thereby allowing the sensor to achieve true dormancy. The sensor in the \(S\) state will change to the \(T_{1}\) state at the desired time to achieve the purpose in terms of power balance. Fast convergence can prevent the sensor from consuming unnecessary power resources and bandwidth. In [28], the authors proposed a fast convergence control method called QC2, which is mainly based on the relationship between the QoS and the target value, and using the virtual target shortens the convergence time. However, this method faces an environment in which the sensors continue to die. Due to continuous changes in QoS, the aim of power saving cannot be achieved. In the multi-objective QoS control algorithm, the authors combined the two control objectives of QoS and coverage and proposed a compound control method that can control the coverage ratio in addition to QoS [30]. In [19; 31; 32], combining the two control objectives of QoS and node density, the control strategies for rectangular, circular, and various elliptical regions are given, and a dynamic adjustment mechanism based on the Gur Game algorithm is designed.