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One significant difference is that this problem requires attention to \u201cdata-awareness\u201d in addition to \u201cenergy-awareness\u201d. We formulate the maximum data extraction problem as a linear program and present a 1 + \u03c9 iterative approximation algorithm for it. As a practical distributed implementation we develop a faster greedy heuristic for this problem that uses an exponential metric based on the approximation algorithm. We then show through simulation results that the greedy heuristic incorporating this exponential metric performs near-optimally (within 1 to 10% of optimal, with low overhead) and significantly better than other energy aware routing approaches (developed mainly through intuition), particularly when nodes are heterogeneous in their energy and data availability. <\/jats:p>","DOI":"10.1080\/15501320590901874","type":"journal-article","created":{"date-parts":[[2005,9,20]],"date-time":"2005-09-20T19:31:27Z","timestamp":1127244687000},"page":"123-147","source":"Crossref","is-referenced-by-count":8,"title":["Maximizing Data Extraction in Energy-Limited Sensor Networks"],"prefix":"10.1177","volume":"1","author":[{"given":"Narayanan","family":"Sadagopan","sequence":"first","affiliation":[{"name":"Department of Computer Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bhaskar","family":"Krishnamachari","sequence":"additional","affiliation":[{"name":"Department of Computer Science"},{"name":"Department of Computer Engineering University of Southern California, Los Angeles, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2005,2,1]]},"reference":[{"key":"bibr11-15501320590901874","volume-title":"PEGASIS: Power Efficient Gathering in Sensor Information Systems","author":"Lindsey S.","year":"2001"},{"key":"bibr17-15501320590901874","doi-asserted-by":"publisher","DOI":"10.1145\/48014.61051"},{"key":"bibr18-15501320590901874","volume-title":"Introduction to Algorithms","author":"Cormen T. 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