QC2: A QoS Control Scheme with Quick Convergence in Wireless Sensor Networks

In wireless sensor networks, too many or too few power-on sensors may cause the waste of resources or poor sensing efficiency; thus, controlling the number of active sensors to meet the predicted target number is the purpose of this research. However, the total number of sensors may be unstable because of the increment and damage to the sensors. It is difficult to control the number of active sensors to meet the predicted target in this condition. Previous studies proposed the Gur Game algorithm to solve this problem. However, the convergence time of the Gur Game algorithm is too long, which causes sensors to consume excessive power and waste resources. Therefore, this paper proposed the QoS Control with Quick Convergence (QC2). This method utilizes total virtual value to accelerate the convergence operation from the number of sensors to the target number. The experiment result shows that the QC2 method can cause the number of sensors to converge rapidly with the target value and that QC2 can be over a hundred times faster than the Gur Game algorithm with regard to convergence. 1. Introduction With the recent technological developments of the wireless networks and multifunctional sensors with processing and communication capabilities, wireless sensor networks (WSNs) have been used in an increasing number of applications. WSNs can provide a more accurate or reliable monitoring service for different classes of applications. Quality of service can be an important mechanism to guarantee that the distinct requirements for different classes of applications are met. A WSN consists of a large number of small sensors and a sink (base) station. Sensors are small devices with limited energy supply and low computational capability. They are used for covering and monitoring a sensing field to collect useful information. Sensor networks are useful in a variety of domains, such as environmental observation, health care, and military monitoring. Sensors are usually placed randomly in a sensor field. The concept of redundancy is applied to WSNs to achieve a high degree of reliability. One or more sensors may cover the same region and gather similar data; thus, numerous redundant data are sent to the sink. Redundant data collection should be avoided to conserve energy in WSNs. Sensors are scheduled to be periodically active and idle. Only several sensors are active in a given period of time, resulting in high reliability and low data redundancy. The assumption that a sensor network has a fixed number of nodes is unreasonable because sensor nodes usually have limited