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In this paper, we propose SWIFTNET: a fast-reactive data acquisition scheme. SWIFTNET is built on the synergies between compressive sensing and prediction algorithms and limits the energy consumption in environmental monitoring and surveillance networks. We show how this approach dramatically reduces the amount of communication required to monitor the sensor readings in a deployment. We use a wildfire...
Data reduction strategy is one of the schemes employed to extend network lifetime. In this paper we present an implementation of a light-weight forecasting algorithm for sensed data which saves packet transmission in the network. The proposed Naive algorithm achieves high energy savings with a limited computational overhead on a node. Simulation results from realistic Building monitoring application...
Data reduction strategy is one of the schemesemployed to extend network lifetime. In this paper we present an implementation of a light-weight forecasting algorithm for sensed data which saves packet transmission in the network. The proposed Naive algorithm achieves high energy savings with a limited computational overhead on a node. Simulation results from realistic Building monitoring application...
The longevity of wireless sensor network (WSN) deployments is often crucial for real-time monitoring applications. Minimizing energy consumption by utilizing intelligent information processing is one of the main ways to prolong the lifetime of a network deployment. Data streams from the sensors need to be processed within the resource constraints of the sensing platforms to reduce the energy consumption...
Wireless sensor network (WSN) technologies have been employed in recent years for monitoring purposes in various domains from engineering industry to our home environment due to their ability to intelligently monitor remote locations. In this paper, we have developed a purely deterministic model that utilizes clustering to organize the WSN. We propose a deterministic energy-efficient clustering protocol...
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