{"id":"https://openalex.org/W2169821659","doi":"https://doi.org/10.1109/cdc.2008.4739329","title":"Dynamic ping optimization for surveillance in multistatic sonar buoy networks with energy constraints","display_name":"Dynamic ping optimization for surveillance in multistatic sonar buoy networks with energy constraints","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2169821659","doi":"https://doi.org/10.1109/cdc.2008.4739329","mag":"2169821659"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2008.4739329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2008.4739329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 47th IEEE Conference on Decision and Control","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/A5088297975","display_name":"Anshu Saksena","orcid":null},"institutions":[{"id":"https://openalex.org/I2802946424","display_name":"Johns Hopkins University Applied Physics Laboratory","ror":"https://ror.org/029pp9z10","country_code":"US","type":"facility","lineage":["https://openalex.org/I145311948","https://openalex.org/I2802946424"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anshu Saksena","raw_affiliation_strings":["Milton Eisenhower Research Center, Johns Hopkins University-Applied Physics Laboratory, Laurel, MD, USA"],"affiliations":[{"raw_affiliation_string":"Milton Eisenhower Research Center, Johns Hopkins University-Applied Physics Laboratory, Laurel, MD, USA","institution_ids":["https://openalex.org/I2802946424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109618222","display_name":"I-Jeng Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2802946424","display_name":"Johns Hopkins University Applied Physics Laboratory","ror":"https://ror.org/029pp9z10","country_code":"US","type":"facility","lineage":["https://openalex.org/I145311948","https://openalex.org/I2802946424"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"I-Jeng Wang","raw_affiliation_strings":["Milton Eisenhower Research Center, Johns Hopkins University-Applied Physics Laboratory, Laurel, MD, USA"],"affiliations":[{"raw_affiliation_string":"Milton Eisenhower Research Center, Johns Hopkins University-Applied Physics Laboratory, Laurel, MD, USA","institution_ids":["https://openalex.org/I2802946424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088297975"],"corresponding_institution_ids":["https://openalex.org/I2802946424"],"apc_list":null,"apc_paid":null,"fwci":1.4375,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.85292563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"18","issue":null,"first_page":"1109","last_page":"1114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11622","display_name":"Maritime Navigation and Safety","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7536738514900208},{"id":"https://openalex.org/keywords/ping","display_name":"Ping (video games)","score":0.6419655084609985},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.6077377200126648},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5830631256103516},{"id":"https://openalex.org/keywords/sonar","display_name":"Sonar","score":0.5606449842453003},{"id":"https://openalex.org/keywords/marine-mammals-and-sonar","display_name":"Marine mammals and sonar","score":0.5023446083068848},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5015864372253418},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.41883084177970886},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.2793336808681488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2770531177520752},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23818832635879517},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.1995123028755188},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.19621092081069946},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09505105018615723}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7536738514900208},{"id":"https://openalex.org/C156308498","wikidata":"https://www.wikidata.org/wiki/Q1347898","display_name":"Ping (video games)","level":2,"score":0.6419655084609985},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.6077377200126648},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5830631256103516},{"id":"https://openalex.org/C555745239","wikidata":"https://www.wikidata.org/wiki/Q133220","display_name":"Sonar","level":2,"score":0.5606449842453003},{"id":"https://openalex.org/C137184094","wikidata":"https://www.wikidata.org/wiki/Q6764300","display_name":"Marine mammals and sonar","level":3,"score":0.5023446083068848},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5015864372253418},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.41883084177970886},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2793336808681488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2770531177520752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23818832635879517},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.1995123028755188},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.19621092081069946},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09505105018615723},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cdc.2008.4739329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2008.4739329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 47th IEEE Conference on Decision and Control","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.142.4256","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.4256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.jhu.edu/~ijwang/pub/cdc08.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8199999928474426}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310145","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1982972967","https://openalex.org/W2014787937","https://openalex.org/W2071873857","https://openalex.org/W2091165295","https://openalex.org/W2122522721","https://openalex.org/W2131671515","https://openalex.org/W2137585588","https://openalex.org/W2155349500","https://openalex.org/W3016548437"],"related_works":["https://openalex.org/W2392611223","https://openalex.org/W2049105424","https://openalex.org/W2362175816","https://openalex.org/W2016800904","https://openalex.org/W4285109196","https://openalex.org/W3003593517","https://openalex.org/W3197465599","https://openalex.org/W2999206242","https://openalex.org/W2041835195","https://openalex.org/W580836668"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,145,165],"study":[4],"the":[5,53,74,85,101,105,120,133,142,156,167,170,177],"problem":[6],"of":[7,10,24,33,68,92,104,122,141,169,182],"dynamic":[8],"optimization":[9,116],"ping":[11,34,42,45,79,115],"schedule":[12],"in":[13,49,180],"an":[14,65],"active":[15],"sonar":[16,163],"buoy":[17],"network":[18,106],"deployed":[19],"to":[20,37,41,47,51,84,99,114],"provide":[21],"persistent":[22,60],"surveillance":[23,61],"a":[25,138,151],"littoral":[26],"area":[27],"through":[28],"multistatic":[29,158],"detection.":[30],"The":[31],"goal":[32],"scheduling":[35],"is":[36,62,71,81,97,117],"dynamically":[38],"determine":[39],"when":[40],"and":[43,173,185],"which":[44],"source":[46,80],"engage":[48],"order":[50],"achieve":[52],"desirable":[54],"detection":[55,110,183],"performance.":[56,111],"For":[57],"applications":[58],"where":[59],"needed":[63],"for":[64,95],"extended":[66],"period":[67],"time,":[69],"it":[70,175],"expected":[72],"that":[73,154],"energy":[75],"available":[76],"at":[77],"each":[78],"limited":[82],"relative":[83],"required":[86,102],"system":[87,186],"lifetime.":[88,187],"Hence":[89],"efficient":[90],"management":[91],"power":[93],"consumption":[94],"pinging":[96],"important":[98],"support":[100],"lifetime":[103],"while":[107],"maintaining":[108],"acceptable":[109],"Our":[112],"approach":[113,172],"based":[118,149],"on":[119,150],"application":[121],"approximate":[123],"partially":[124],"observable":[125],"Markov":[126],"decision":[127],"process":[128],"(POMDP)":[129],"techniques":[130,148],"such":[131],"as":[132],"rollout":[134],"algorithm.":[135],"To":[136],"enable":[137],"practical":[139],"implementation":[140],"policy":[143],"rollout,":[144],"apply":[146],"sampling-based":[147],"simplified":[152],"model":[153],"approximates":[155],"detailed":[157],"model.":[159],"Using":[160],"high":[161],"fidelity":[162],"simulations,":[164],"evaluate":[166],"performance":[168,184],"proposed":[171],"compare":[174],"with":[176],"greedy":[178],"technique":[179],"terms":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}