Maximum Throughput Under Admission Control With Unknown Queue-Length in Wireless Sensor Networks

In a Wireless Sensor Network (WSN) node, as the input traffic increases, the throughput can be assumed to first increase and then start to decrease, indicating congestion in the buffer. This suggests the need for an admission control mechanism to maintain high throughput as the arrival traffic increases. Considering the stochastic nature of WSNs, the information of the queue-length of arrival or newly sensed data packets can be unknown to a sensor node. This paper proposes a probabilistic admission control model with the maximum throughput for the node. In the proposed model, a reward when a data packet arriving to a sensor is accepted (not rejected) for transmission is considered, but a holding cost per unit time for the delay of accepted data packets in the sensor is also incurred. For the sensor node, by constructing a suitable Markov decision process (MDP), a probabilistic admission control algorithm on how to accept data packets on sleep and active phases to achieve a maximum throughput is proposed. Furthermore, for the identified (p;q) model, the energy consumption of the node in active and sleep phases, as well as the energy consumption switching from active to sleep per unit time and vice versa is investigated. An extensive simulation is implemented. The numerical results show that the problem is effectively solved by an optimal scheme with high energy efficiency. The results of this paper can be applied in designing optimal sensor nodes in WSNs.