A Non-cooperative Game Algorithm for Task Scheduling in Wireless Sensor Networks

Abstract

Scheduling tasks in wireless sensor networks is one of the most challenging problems. Sensing tasks should be allocated and processed among sensors in minimum times, so that users can draw prompt and effective conclusions through analyzing sensed data. Furthermore, finishing sensing task faster will benefit energy saving, which is critical in system design of wireless sensor networks. But sensors may refuse to take pains to carry out the tasks due to the limited energy. To solve the potentially selfish problem of the sensors, a non-cooperative game algorithm (NGTSA) for task scheduling in wireless sensor networks is proposed. In the proposed algorithm, according to the divisible load theory, the tasks are distributed reasonably to every node from SINK based on the processing capability and communication capability. By removing the performance degradation caused by communications interference and idle, the reduced task completion time and the improved network resource utilization are achieved. Strategyproof mechanism which provide incentives to the sensors to obey the prescribed algorithms, and to truthfully report their parameters, leading to an effient task scheduling and execution. A utility function related with the total task completion time and tasks allocating scheme is designed. The Nash equilibrium of the game algorithm is proved. The simulation results show that with the mechanism in the algorithm, selfish nodes can be forced to report their true processing capability and endeavor to participate in the measurement, thereby the total time for accomplishing the task is minimized and the energy-consuming of the nodes is balanced.

Game theoretic application for energy efficient mobility handling in wireless sensor network

“…Task allocation is required in certain application in WSN where allocation of different task to different sensors or to group of sensors is to be done. Cooperation enforcement is used in References 67,68 in WSN for task allocation.…”

GATE, a game theory approach on traffic volume aware channel width adaptation for WBAN medical applications

“…In the game, players compete with each other and the problem is converted to an optimization problem that each player leads the system toward a social equilibrium . Mathematical representation of a noncooperative game is which represents a set of players, action space, and set of payoff functions of a player i , respectively .…”

“…It is clear that the relation (9) becomes (16) what means that maximum gain is reached when the node with high priority transmits with extend bandwidth while others delay their transmissions.…”

Game Theory for Wireless Sensor Networks: A Survey

“…Therefore, incentives should be provided to force nodes to obey the prescribed algorithms and report truthfully their capacity. Mechanism design in GT can resolve this problem [ 55 ].…”

“…u i (·) is the utility function of an agent, that u i (·) = p i (·) − v i ( t i , λ ). t i is the true value, and t̃ i is the implementation value [ 55 ]. Define vector t = ( t 1 ,t 2 ,…,t n ), b = ( b 1 ,b 2 ,…,b n ), t̃ = t̃ 1 , t̃ 2 , ⋯, t̃ n ), and the output vector λ ( b ) = ( λ 1 ( b ), λ 2 ( b ),…, λ n ( b )).…”