• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.175-183
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• 2008

In wireless sensor networks with ad hoc networking capability, sensor nodes are battery operated and are usually disposable once deployed. As a result, each sensor node senses and communicates with limited energy and, thus, energy efficiency has been studied as a key design factor which determines lifetime of a wireless sensor network, and it is more improved recently by using so-called cross-layer optimization technique. In this paper, we propose and implement a new energy saving mechanism that reduces energy consumption during data collection by controlling transmission power at sensor nodes and then measure its performance in terms of lifetime improvement for the wireless sensor network platform ZigbeX. When every sensor node transmits sensed data to its clusterhead, it controls its transmission power down to as low level as communication is possible, resulting in energy saving. Each sensor node controls its transmission power based on RSSI(Received Signal Strength Indicator) of the packet received from its clusterhead. In other words, the sensor node can save energy by controlling its transmission power down to an appropriate level that its clusterhead safely receives the packet it transmits. According to the repetitive experiment of the proposed scheme on the ZigbeX platform using the packet analyzer developed by us, it is observed that the network lifetime is prolonged by up to 21.9% by saying energy during the data collection occupying most amount of network traffic.

• Journal of KIISE:Information Networking
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• v.36 no.5
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• pp.413-424
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• 2009

Wireless sensor network is based on an event driven system. Sensor nodes collect the events in surrounding environment and the sensing data are relayed into a sink node. In particular, when events are detected, the data sensing periods are likely to be shorter to get the more correct information. However, this operation causes the traffic congestion on the sensor nodes located in a routing path. Since the traffic congestion generates the data queue overflows in sensor nodes, the important information about events could be missed. In addition, since the battery energy of sensor nodes exhausts quickly for treating the traffic congestion, the entire lifetime of wireless sensor networks would be abbreviated. In this paper, a new congestion control method is proposed on the basis of genetic algorithm. To apply genetic algorithm, the data traffic rate of each sensor node is utilized as a chromosome structure. The fitness function of genetic algorithm is designed from both the average and the standard deviation of the traffic rates of sensor nodes. Based on dominant gene sets, the proposed method selects the optimal data forwarding sensor nodes for relieving the traffic congestion. In experiments, when compared with other methods to handle the traffic congestion, the proposed method shows the efficient data transmissions due to much less queue overflows and supports the fair data transmission between all sensor nodes as possible. This result not only enhances the reliability of data transmission but also distributes the energy consumptions across the network. It contributes directly to the extension of total lifetime of wireless sensor networks.