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Within this context, this article concentrates on adaptive sampling as a means of focusing a sensor's energy consumption on obtaining the most important data. Specifically, we develop a principled information metric based upon Fisher information and Gaussian process regression that allows the information content of a sensor's observations to be expressed. We then use this metric to derive three novel decentralized control algorithms for information-based adaptive sampling which represent a trade-off in computational cost and optimality. These algorithms are evaluated in the context of a deployed sensor network in the domain of flood monitoring. The most computationally efficient of the three is shown to increase the value of information gathered by approximately 83%, 27%, and 8% per day compared to benchmarks that sample in a na\u00efve nonadaptive manner, in a uniform nonadaptive manner, and using a state-of-the-art adaptive sampling heuristic (USAC) correspondingly. Moreover, our algorithm collects information whose total value is approximately 75% of the optimal solution (which requires an exponential, and thus impractical, amount of time to compute).<\/jats:p>","DOI":"10.1145\/1525856.1525857","type":"journal-article","created":{"date-parts":[[2009,6,9]],"date-time":"2009-06-09T12:44:12Z","timestamp":1244551452000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":65,"title":["Decentralized control of adaptive sampling in wireless sensor networks"],"prefix":"10.1145","volume":"5","author":[{"given":"Johnsen","family":"Kho","sequence":"first","affiliation":[{"name":"University of Southampton, Southampton, UK"}]},{"given":"Alex","family":"Rogers","sequence":"additional","affiliation":[{"name":"University of Southampton, Southampton, UK"}]},{"given":"Nicholas R.","family":"Jennings","sequence":"additional","affiliation":[{"name":"University of Southampton, Southampton, UK"}]}],"member":"320","published-online":{"date-parts":[[2009,6,4]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Bar-Shalom Y. 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