{"id":"https://openalex.org/W2098840178","doi":"https://doi.org/10.1145/1791212.1791244","title":"Markov-optimal sensing policy for user state estimation in mobile devices","display_name":"Markov-optimal sensing policy for user state estimation in mobile devices","publication_year":2010,"publication_date":"2010-04-12","ids":{"openalex":"https://openalex.org/W2098840178","doi":"https://doi.org/10.1145/1791212.1791244","mag":"2098840178"},"language":"en","primary_location":{"id":"doi:10.1145/1791212.1791244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1791212.1791244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100364966","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-6294-1290"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Wang","raw_affiliation_strings":["University of Southern California, Los Angeles","University of Southern California , Los Angeles#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California , Los Angeles#TAB#","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063784062","display_name":"Bhaskar Krishnamachari","orcid":"https://orcid.org/0000-0002-9994-9931"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhaskar Krishnamachari","raw_affiliation_strings":["University of Southern California, Los Angeles","University of Southern California , Los Angeles#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California , Los Angeles#TAB#","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013788255","display_name":"Qing Zhao","orcid":"https://orcid.org/0000-0002-9590-4285"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Zhao","raw_affiliation_strings":["University of California, Davis","university of california, davis"],"affiliations":[{"raw_affiliation_string":"University of California, Davis","institution_ids":["https://openalex.org/I84218800"]},{"raw_affiliation_string":"university of california, davis","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018033573","display_name":"Murali Annavaram","orcid":"https://orcid.org/0000-0002-4633-6867"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murali Annavaram","raw_affiliation_strings":["University of Southern California, Los Angeles","University of Southern California , Los Angeles#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California , Los Angeles#TAB#","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100364966"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":15.7635,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.98980675,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"268","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696276903152466},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.6853652596473694},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.643528401851654},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5721651315689087},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.557527482509613},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5114575624465942},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.49619513750076294},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4895952343940735},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.4881806969642639},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4083341360092163},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3711341917514801},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.35159194469451904},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3125956058502197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21040722727775574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18202519416809082},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11735647916793823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10960036516189575},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06400108337402344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696276903152466},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.6853652596473694},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.643528401851654},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5721651315689087},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.557527482509613},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5114575624465942},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.49619513750076294},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4895952343940735},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.4881806969642639},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4083341360092163},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3711341917514801},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35159194469451904},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3125956058502197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21040722727775574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18202519416809082},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11735647916793823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10960036516189575},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06400108337402344},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1791212.1791244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1791212.1791244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G4270769856","display_name":null,"funder_award_id":"NSF CNS-0831545NSF ECS-0622200","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4464729335","display_name":null,"funder_award_id":"NSF CNS-0831545NSF ECS-0622200","funder_id":"https://openalex.org/F4320337388","funder_display_name":"Division of Computer and Network Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1518931405","https://openalex.org/W1570192122","https://openalex.org/W1576835806","https://openalex.org/W1731839985","https://openalex.org/W1856713324","https://openalex.org/W1966924243","https://openalex.org/W1973391103","https://openalex.org/W1988560007","https://openalex.org/W1991133427","https://openalex.org/W2004883573","https://openalex.org/W2015782794","https://openalex.org/W2036688595","https://openalex.org/W2047485015","https://openalex.org/W2064385972","https://openalex.org/W2065365821","https://openalex.org/W2068502909","https://openalex.org/W2125838338","https://openalex.org/W2130828423","https://openalex.org/W2132391423","https://openalex.org/W2134751203","https://openalex.org/W2135009572","https://openalex.org/W2141890671","https://openalex.org/W2149708663","https://openalex.org/W2150383149","https://openalex.org/W2157693300","https://openalex.org/W2162343230","https://openalex.org/W2162555816","https://openalex.org/W2165882932","https://openalex.org/W2170265372","https://openalex.org/W2198078890","https://openalex.org/W2341171179","https://openalex.org/W2531563875","https://openalex.org/W2764942935","https://openalex.org/W3026417138"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2194396582","https://openalex.org/W2082284720","https://openalex.org/W2116722627","https://openalex.org/W2537260108","https://openalex.org/W2379938888","https://openalex.org/W2566202039","https://openalex.org/W4233405330","https://openalex.org/W2792905593"],"abstract_inverted_index":{"Mobile":[0],"device":[1,33],"based":[2],"human-centric":[3],"sensing":[4,86,142],"and":[5,17,30,92,123,126],"user":[6,57,66,89,120],"state":[7,58,67,90,102],"recognition":[8],"provide":[9],"rich":[10],"contextual":[11,23],"information":[12,24],"for":[13,87],"various":[14],"mobile":[15,32],"applications":[16],"services.":[18],"However,":[19],"continuously":[20],"capturing":[21],"this":[22,37],"consumes":[25],"significant":[26],"amount":[27],"of":[28,114],"energy":[29,74],"drains":[31],"battery":[34],"quickly.":[35],"In":[36],"paper,":[38],"we":[39],"propose":[40],"a":[41,72],"computationally":[42],"efficient":[43],"algorithm":[44,109],"to":[45,110,119,133],"obtain":[46],"the":[47,53,56,80,95,100,108,129,139],"optimal":[48],"sensor":[49],"sampling":[50],"policy":[51,64,82,131],"under":[52],"assumption":[54],"that":[55,94,128],"transition":[59,103],"is":[60],"Markovian.":[61],"This":[62],"Markov-optimal":[63,81,130],"minimizes":[65],"estimation":[68],"error":[69],"while":[70],"satisfying":[71],"given":[73],"consumption":[75],"budget.":[76],"We":[77,105],"first":[78],"compare":[79],"with":[83],"uniform":[84,141],"periodic":[85],"Markovian":[88],"transitions":[91],"show":[93,127],"improvements":[96],"obtained":[97],"depend":[98],"upon":[99],"underlying":[101],"probabilities.":[104],"then":[106],"apply":[107],"two":[111],"different":[112],"sets":[113],"real":[115],"experimental":[116],"traces":[117],"pertaining":[118],"motion":[121],"change":[122],"inter-user":[124],"contacts":[125],"leads":[132],"an":[134],"approximately":[135],"20%":[136],"improvement":[137],"over":[138],"naive":[140],"policy.":[143]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}