
doi: 10.1049/ic.2011.0090
This paper presents wireless sensor network (WSN) for environmental monitoring with optimized lifetime. The node is equipped with multimode sensors for sensing different environmental parameters. An efficient utilization of power is essential in order to use networks for long duration, hence it is needed to reduce data traffic inside sensor networks, reduce amount of data that need to send to sink. This paper aims at studying different strategies to maximize the WSN lifetime, including routing, data aggregation, data accuracy and energy consumption. The main idea is to define a multi-metrics protocol that takes into account the residual energy within sensor nodes, data aggregation and data accuracy.This paper considers three optimization metrics. First of all, it considers the construction of routing tree with energy and distance parameters.The objective is to maximize the number of data gathering queues answered until the first node m the network fails. Secondly, data aggregation is done by gathering data in an energy efficient manner The aim of the proposed work is to compare the performance in terms of energy efficiency in comparison with and without data aggregation in WSN. Thirdly, the trade-off between data quality and energy consumption to increase the lifetime of WSN is considered.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
