Improved Estimation Performance of Sensor in Wireless Sensor Network Using Suboptimal Technique

ABSTRACT--This paper presents a novel network lifetime extension technique. In order to collect information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Clustering provides an effective way to prolong the lifetime of WSNs. Current clustering approaches often use two methods: selecting cluster heads with more residual energy, and rotating cluster head periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, most of the previous algorithms have not considered the expected residual energy, only consider the estimation performance. In this paper we propose a probabilistic based transmission using clustering algorithm. Probabilistic transmission control at which is to minimize the mean squared error of estimation by increasing the packet transmission success probability of only sensors having high observation SNR. These newly available sensors are partitioned into several sensor sets select the cluster head to maintain the same estimation performance. The simulation results show that the proposed approach is more efficient than other distributed algorithms. It is believed that the technique presented in this paper could be further applied to large-scale wireless sensor networks

Exploiting data-dependent transmission control and MAC timing information for distributed detection in sensor networks

[[abstract]]In this paper, we propose a data-dependent transmission control policy over the slotted ALOHA MAC protocol and a cross-layered fusion rule that exploits MAC timing information for distributed detection in sensor networks. In this system, each sensor first makes a local decision at the beginning of each observation period and transmits the decision to the fusion center over a random access channel. Based on the slotted ALOHA random access protocol, we propose a class of data-dependent transmission control policies that assign to sensors their transmission probabilities according to the reliability of their local decisions. For the case with i.i.d. observations in each time slot, we show that the optimal transmission control function takes on the form of a thresholding function. That is, a sensor will transmit in a given time slot if and only if its local log-likelihood ratio exceeds a certain threshold. When observations are made only every several time slots, the message arrival time at the fusion center, which is spread over the observation period of duration K > 1, will embed the reliability of the received sensors' decisions as a result of the data-dependent transmission control. This timing information can be accounted for in the fusion rule to further enhance performance. Finally, we extend the proposed strategies to multicluster sensor network scenarios, where the sensors' local decisions are transmitted to the fusion center in a two-hop fashion. We show, through numerical simulations, that the proposed schemes outperform both conventional slotted ALOHA and TDMA-based schemes that do not adopt cross-layered transmission and fusion strategies.[[fileno]]2030137010014[[department]]電機工程學