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Zhang J.,Open Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan | Zhang J.,Southwest University of Science and Technology | Jiang H.,Open Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan | Jiang H.,Southwest University of Science and Technology | And 3 more authors.
Sensors (Switzerland) | Year: 2015

Technological advances have led to the emergence of wireless sensor nodes in wireless networks. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy conservation is very important in the wireless sensor network protocol design and the limited power resources are the biggest challenge in wireless network channels. Link adaptation techniques improve the link quality by adjusting medium access control (MAC) parameters such as frame size, data rate, and sleep time, thereby improving energy efficiency. In this paper we present an adaptive packet size strategy for energy efficient wireless sensor networks. The main goal is to reduce power consumption and extend the whole network life. In order to achieve this goal, the paper introduces the concept of a bounded MAB to find the optimal packet size to transfer by formulating different packet sizes for different arms under the channel condition. At the same time, in achieve fast convergence, we consider the bandwidth evaluation according to ACK. The experiment shows that the packet size is adaptive when the channel quality changes and our algorithm can obtain the optimal packet size. We observe that the MAB packet size adaptation scheme achieves the best energy efficiency across the whole simulation duration in comparison with the fixed frame size scheme, the random packet size and the extended Kalman filter (EKF). © 2015 by the authors; licensee MDPI, Basel, Switzerland.


Zhang J.,Open Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan | Zhang J.,Southwest University of Science and Technology | Jiang H.,Open Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan | Jiang H.,Southwest University of Science and Technology | And 2 more authors.
International Journal of Distributed Sensor Networks | Year: 2014

Cooperative communication has emerged as a new wireless network communication concept, in which parameter optimization such as cross-layer cooperation plays an important role. Heuristic evaluation postdecision state learning algorithm (HE-PDS) is proposed in cross-layer cooperation. The proposed algorithm exploits the determinate state information and jointly considers the transmitting power and channel state condition at the physical layer and the buffer congestion control at the media access control layer. The experimental results show that the cumulative average total costs of HE-PDS algorithm decrease about ten times and 8% under the maximum delay and throughput constraints and the power costs decrease about 50% and 28% under various delay limits and about 100% and 56% under the different throughput constraints than the traditional Q algorithm and PDS algorithm, demonstrating that the proposed algorithm has much better energy-efficient performance and faster convergence speed and outperforms the traditional Q learning algorithm and PDS learning algorithm. © 2014 Juan Zhang et al.

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