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Abstract. The goal of energy aware routing algorithms is to increase the lifetime and long-term connectivity of the wireless sensor networks. However, most of those algorithms do not use the newest states of nodes for retrieving routing information. In this paper, we propose an efficient energy-aware routing algorithm for wireless sensor networks. In our algorithm, the energy drain rate and residual energy of each sensor node are used for selecting candidate routes. Information is retrieved with energy awareness per almost every communication. Simulation results show that our approach outperforms the previous works with respect to long term connectivity by as much as 30%.

We present a study on the development and testing of a wireless electronic nose network (WENn) for monitoring real-time gas mixture, NH 3 and H 2S, main malodors in various environments. The proposed WENn is based on an embedded PC, an electronic olfactory system and wireless sensor network (WSN) technology and neuro-fuzzy network algorithms. The WENn used in this work takes advantage of recent advances in low power wireless communication platforms and uses micro-gas sensors with Sn02-CuO and Sn02-Pt sensing films for detecting the presence of target gases. Each node in the network realtimely performs classification and concentration estimation of the binary gas mixtures using the fuzzy ART and ARTMAP neural networks and calculation of the measured humidity and temperature in a located point and then transmits the computed results from the measured data set to a sink node via a Zigbeeready RF transceiver. In addition, a monitoring manager virtual instrument (MMVI) is developed using LabVIEW to monitor efficiently the analyzed gas information from the sensor node. To test the reproducibility and reliability of the WENn, on-line experiments are conducted with the gas monitoring system.Keywords-wireless electronic nose network; gas monitoring system; micro-gas sensor array; wireless sensor network; embedded system I.