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This paper proposes a logical correlation-based sleep scheduling mechanism (LCSSM) to implement energy-efficient wireless sensor networks (WSNs) in ambient-assisted homes (AAHs). LCSSM analyzes sensory data generated by different human behaviors to detect the logical correlations between sensor nodes in an AAH. By utilizing the particular logical correlations of an AAH to predict its usage status,...
In wireless sensor networks (WSNs), Energy consumption will be reduced by grouping all the sensor nodes into clusters and letting the data be aggregated at cluster heads(CHs). In this paper, we address the issue of how many tiers in a given clustering scheme are optimal in saving energy. We present a method to calculate the optimal tier number with consideration to the energy consumption both in data...
Energy efficiency is an important issue in wireless sensor networks. One available power saving strategy is having only a portion of nodes work, but this would always compromise data quality as a result. In this paper, we propose an adaptive nodes scheduling approach (ADNS) to conserve energy while maintaining the overall data quality. ADNS selects a subset of nodes to be active and puts the others...
Cooperative transmission technique is now widely considered as a promising approach to combat fading and achieve energy efficiency in wireless networks. In this paper we focus on the routing problem in energy-constrained wireless sensor networks (WSNs), of which a cooperative MISO-based routing strategy is adopted. We first analyze the physical layer energy consumption model of cooperative transmission...
Data samples sensed from a densely deployed sensor network often exhibit strong spatial and temporal correlation. Sampling and transmitting these highly correlated data through wireless channel would result in excessive energy consumption. One way to conserve energy is to set a portion of sensors into sleep mode provided their missing data can be well recovered by sensors that remain active. Different...
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