Research
Energy Efficient Weighted Clustering Algorithm in Wireless Sensor Networks
With the advancement in communication and internet technologies, recently there have been many research efforts in the area of Wireless Sensor Networks (WSNs) to conserve energy. Clustering mechanisms have been applied to WSNs to enhance the network performance while reducing the necessary energy consumption. The goal of Weighted Clustering Algorithm (WCA) is to determine the cluster heads dynamically based on a combined weight metric that includes one or more parameters such as node degree, distances with respect to a nodes neighbors, node speed and the time spent as a cluster head. In this work, we have proposed a refined and improved version of WCA known as Energy Efficient Weighted Clustering Algorithm (EEWCA) to prolong the network lifetime by reducing energy consumption. EEWCA is designed and simulated with additional constraint on energy for the selection of cluster heads. Both the WCA and EEWCA schemes have been simulated using MATLAB. The proposed EEWCA behaves better than WCA for longer system lifetime. The proposed work is simulated and performance is tested for number of clusters and average execution time. Simulation results show that the EEWCA outperforms WCA in terms of both the number of clusters formed and the execution time.
Dynamic and Channel Adaptive Error Control Scheme in Wireless Sensor Networks
The application of wireless technology is increasingly influencing the deployment of sensor networks at low cost and maintainance in all walks of life. Poor channel conditions, severe power constraints, fading, interference and the low power communication requirements magnify the need for energy efficient and preferably cross layer error control schemes in Wireless Sensor Networks (WSNs). The main goal of error control mechanisms in WSNs is to reduce the energy expenditure while taking care of reliable and fast delivery of the sensed data. In this paper, we propose a �Dynamic and Channel Adaptive Error Control Scheme in Wireless Sensor Networks� (DCAECS) that estimates the channel errors and controls errors dynamically based on channel characteristics and noise power observed at the receiver. This motivates the error control strategy to vary as the channel conditions change in terms of noise level. In this paper, we have come up with the models for both the error and channel estimation. Analysis and simulation results for various message sizes and error conditions show that there is an improvement in terms of throughput, BER and the probability of retransmission as compared to �ARQ Scheme With Adaptive Error Control� (ASAEC).
