Development of novel wireless sensor networks and potential optimization via Kalman filtering

Abstract

Data aggregation is an important area of wireless sensor networks. The importance of efficient data aggregation in wireless sensor networks is due to the fact of the networks which are volatile and ad hoc in nature. Problems associated include efficient energy consumption and routing techniques. Zone Efficient Localized Data Aggregation (Zelda) Algorithm has been proposed. This algorithm employs the data funneling technique and zonal nodes in order to send information over a wireless sensor network thereby reducing amounts of energy and traffic required. The energy consumption is estimated at the setup phase of the algorithm, which can be compared with data funneling. The results show that the proposed scheme is a better candidate for applications using the pseudo stationary wireless sensor networks. In addition, the Kalman filter and feedback control scheme is proposed for potential optimization of wireless sensor network systems. Wireless sensor networks topology control is proposed using Kalman filters and feedback control schemes as well.