%0 Book Section %1 springerlink:10.1007/978-3-642-12607-9_14 %A Constandache, Ionut %A Gaonkar, Shravan %A Sayler, Matt %A Choudhury, Romit Roy %A Cox, Landon %B Mobile Computing, Applications, and Services %D 2010 %E Akan, Ozgur %E Bellavista, Paolo %E Cao, Jiannong %E Dressler, Falko %E Ferrari, Domenico %E Gerla, Mario %E Kobayashi, Hisashi %E Palazzo, Sergio %E Sahni, Sartaj %E Shen, Xuemin (Sherman) %E Stan, Mircea %E Xiaohua, Jia %E Zomaya, Albert %E Coulson, Geoffrey %E Phan, Thomas %E Montanari, Rebecca %E Zerfos, Petros %I Springer Berlin Heidelberg %K energy localisation wlanpos mybsc %P 203-222 %T Energy-Efficient Localization via Personal Mobility Profiling %U http://dx.doi.org/10.1007/978-3-642-12607-9_14 %V 35 %X Location based services are on the rise, many of which assume GPS based localization. Unfortunately, GPS incurs an unacceptable energy cost that can reduce the phone’s battery life to less than ten hours. Alternate localization technology, based on WiFi or GSM, improve battery life at the expense of localization accuracy. This paper quantifies this important tradeoff that underlies a wide range of emerging applications. To address this tradeoff, we show that humans can be profiled based on their mobility patterns, and such profiles can be effective for location prediction. Prediction reduces the energy consumption due to continuous localization. Driven by measurements from Nokia N95 phones, we develop an energy-efficient localization framework called EnLoc. Evaluation on real user traces demonstrates the possibility of achieving good localization accuracy for a realistic energy budget. %@ 978-3-642-12607-9

@incollection{springerlink:10.1007/978-3-642-12607-9_14, abstract = {Location based services are on the rise, many of which assume GPS based localization. Unfortunately, GPS incurs an unacceptable energy cost that can reduce the phone’s battery life to less than ten hours. Alternate localization technology, based on WiFi or GSM, improve battery life at the expense of localization accuracy. This paper quantifies this important tradeoff that underlies a wide range of emerging applications. To address this tradeoff, we show that humans can be profiled based on their mobility patterns, and such profiles can be effective for location prediction. Prediction reduces the energy consumption due to continuous localization. Driven by measurements from Nokia N95 phones, we develop an energy-efficient localization framework called EnLoc. Evaluation on real user traces demonstrates the possibility of achieving good localization accuracy for a realistic energy budget.}, added-at = {2010-10-13T11:57:51.000+0200}, affiliation = {Duke University Durham NC USA}, author = {Constandache, Ionut and Gaonkar, Shravan and Sayler, Matt and Choudhury, Romit Roy and Cox, Landon}, biburl = {https://www.bibsonomy.org/bibtex/253008692f2f3bc3383a16b8ba168be3d/kw}, booktitle = {Mobile Computing, Applications, and Services}, editor = {Akan, Ozgur and Bellavista, Paolo and Cao, Jiannong and Dressler, Falko and Ferrari, Domenico and Gerla, Mario and Kobayashi, Hisashi and Palazzo, Sergio and Sahni, Sartaj and Shen, Xuemin (Sherman) and Stan, Mircea and Xiaohua, Jia and Zomaya, Albert and Coulson, Geoffrey and Phan, Thomas and Montanari, Rebecca and Zerfos, Petros}, interhash = {5c1d1c89d00aaaaa16893c9b1ec46e25}, intrahash = {53008692f2f3bc3383a16b8ba168be3d}, isbn = {978-3-642-12607-9}, keyword = {Computer Science}, keywords = {energy localisation wlanpos mybsc}, note = {10.1007/978-3-642-12607-9_14}, pages = {203-222}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering}, timestamp = {2012-08-24T14:02:31.000+0200}, title = {Energy-Efficient Localization via Personal Mobility Profiling}, url = {http://dx.doi.org/10.1007/978-3-642-12607-9_14}, volume = 35, year = 2010 }