Abstract Wireless Sensor Networks (WSNs) have been utilized by many critical applications such as military and health care monitoring. Such applications require special Quality of Service (QoS) treatment. However, the components of sensor nodes suffer from different limitations including the scarce energy source, limited processing capabilities, and limited storage space. At the same time, nodes are supposed to live for long time. This could occur when the energy is balanced on the active nodes in the network. This paper handles the problem of QoS in Wireless Sensor Networks (WSNs). The paper considers the limitation of the nodes in handling many messages at the same time especially the sink node. Therefore, nodes can coordinate with each other to minimize the number of dropped message. Defining some nodes to send to the sink node at certain time allows other nodes to go to sleep. Certainly, this QoS control enhances the operation of the network and positively affect the nodes’ consumed energy. This work applies one of the game theory schemes which is Gur game. The paper proposes two QoS control techniques with Quick Convergence called Periodic Gur Game (PGur) and Adaptive Periodic Gur Game (APGur). These two approaches are evaluated using different sets of experiments.
[1]
Rajesh Krishnan,et al.
Efficient clustering algorithms for self-organizing wireless sensor networks
,
2006,
Ad Hoc Networks.
[2]
Wendi Heinzelman,et al.
Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks
,
2022
.
[3]
Leonard Kleinrock,et al.
QoS control for sensor networks
,
2003,
IEEE International Conference on Communications, 2003. ICC '03..
[4]
Hao-Li Wang,et al.
Shuffle: An Enhanced QoS Control by Balancing Energy Consumption in Wireless Sensor Networks
,
2010,
GPC.
[5]
Ivan Stojmenovic,et al.
Handbook of Sensor Networks: Algorithms and Architectures
,
2005,
Handbook of Sensor Networks.
[6]
Yao Liang,et al.
Gureen Game: An energy-efficient QoS control scheme for wireless sensor networks
,
2011,
2011 International Green Computing Conference and Workshops.