{"id":"https://openalex.org/W2099220942","doi":"https://doi.org/10.1145/1298306.1298345","title":"A data streaming algorithm for estimating entropies of od flows","display_name":"A data streaming algorithm for estimating entropies of od flows","publication_year":2007,"publication_date":"2007-10-24","ids":{"openalex":"https://openalex.org/W2099220942","doi":"https://doi.org/10.1145/1298306.1298345","mag":"2099220942"},"language":"en","primary_location":{"id":"doi:10.1145/1298306.1298345","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1298306.1298345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM SIGCOMM conference on Internet measurement","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/A5050937458","display_name":"Haiquan Zhao","orcid":"https://orcid.org/0000-0003-0198-1384"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haiquan (Chuck) Zhao","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA","Georgia Institute of Technology Atlanta, GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085185917","display_name":"Ashwin Lall","orcid":"https://orcid.org/0009-0003-2046-0055"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashwin Lall","raw_affiliation_strings":["University of Rochester, Rochester, NY","University of Rochester; Rochester, NY"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY","institution_ids":["https://openalex.org/I5388228"]},{"raw_affiliation_string":"University of Rochester; Rochester, NY","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019383096","display_name":"Mitsunori Ogihara","orcid":"https://orcid.org/0000-0002-5690-7854"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mitsunori Ogihara","raw_affiliation_strings":["University of Rochester, Rochester, NY","University of Rochester; Rochester, NY"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY","institution_ids":["https://openalex.org/I5388228"]},{"raw_affiliation_string":"University of Rochester; Rochester, NY","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049422372","display_name":"Oliver Spatscheck","orcid":"https://orcid.org/0000-0003-1555-6303"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oliver Spatscheck","raw_affiliation_strings":["AT&amp;T Labs - Research, Florham Park, NJ"],"affiliations":[{"raw_affiliation_string":"AT&amp;T Labs - Research, Florham Park, NJ","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404622","display_name":"Jia Wang","orcid":"https://orcid.org/0000-0001-8271-4936"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jia Wang","raw_affiliation_strings":["AT&amp;T Labs - Research, Florham Park, NJ"],"affiliations":[{"raw_affiliation_string":"AT&amp;T Labs - Research, Florham Park, NJ","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025728584","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-0046-8119"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA","Georgia Institute of Technology Atlanta, GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5050937458"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":5.2242,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.96462012,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7359908819198608},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6759592890739441},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5962887406349182},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5558887124061584},{"id":"https://openalex.org/keywords/streaming-algorithm","display_name":"Streaming algorithm","score":0.54388028383255},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4221819341182709},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39501795172691345},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3391638398170471},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19075638055801392},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17896440625190735}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7359908819198608},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6759592890739441},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5962887406349182},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5558887124061584},{"id":"https://openalex.org/C187166803","wikidata":"https://www.wikidata.org/wiki/Q2835831","display_name":"Streaming algorithm","level":3,"score":0.54388028383255},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4221819341182709},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39501795172691345},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3391638398170471},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19075638055801392},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17896440625190735},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1298306.1298345","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1298306.1298345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM SIGCOMM conference on Internet measurement","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.117.7879","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.7879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.rochester.edu/~alall/imc07.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.154.9530","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.9530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cc.gatech.edu/~chz/reprints/odentropy-imc2007.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1518702348","https://openalex.org/W1603123426","https://openalex.org/W1628908379","https://openalex.org/W1965972569","https://openalex.org/W1970202913","https://openalex.org/W1977141583","https://openalex.org/W2004287727","https://openalex.org/W2044177275","https://openalex.org/W2044807855","https://openalex.org/W2045345437","https://openalex.org/W2045533739","https://openalex.org/W2058944878","https://openalex.org/W2069980026","https://openalex.org/W2099480861","https://openalex.org/W2104254326","https://openalex.org/W2108673751","https://openalex.org/W2109885200","https://openalex.org/W2113061123","https://openalex.org/W2130583399","https://openalex.org/W2130598205","https://openalex.org/W2146189323","https://openalex.org/W2146801187","https://openalex.org/W2164210932","https://openalex.org/W2499382624","https://openalex.org/W2621193479","https://openalex.org/W2799002609","https://openalex.org/W4205637966","https://openalex.org/W4206137901","https://openalex.org/W4231690667","https://openalex.org/W4241915340","https://openalex.org/W4254460663","https://openalex.org/W6751060025"],"related_works":["https://openalex.org/W2378994405","https://openalex.org/W2385974820","https://openalex.org/W2373478030","https://openalex.org/W2378679551","https://openalex.org/W3149739944","https://openalex.org/W2392363776","https://openalex.org/W2063051341","https://openalex.org/W2591066345","https://openalex.org/W1494563618","https://openalex.org/W2357022711"],"abstract_inverted_index":{"Entropy":[0],"has":[1,15,38],"recently":[2],"gained":[3],"considerable":[4],"significance":[5],"as":[6],"an":[7,42],"important":[8],"metric":[9],"for":[10,96],"network":[11],"measurement.":[12],"Previous":[13],"research":[14],"shown":[16,110],"its":[17],"utility":[18],"in":[19,115],"clustering":[20],"traffic":[21,24,32,53,120],"and":[22,74],"detecting":[23],"anomalies.":[25],"While":[26],"measuring":[27],"the":[28,31,49,52,63,76],"entropy":[29,50],"of":[30,51,79],"observed":[33],"at":[34,103,123],"a":[35,104,124],"single":[36],"point":[37],"already":[39],"been":[40],"studied,":[41],"interesting":[43],"open":[44],"problem":[45],"is":[46,94,109],"to":[47,66,111],"measure":[48],"between":[54],"every":[55],"origin-destination":[56],"pair.":[57],"In":[58],"this":[59,67],"paper,":[60],"we":[61],"propose":[62],"first":[64],"solution":[65],"challenging":[68],"problem.":[69],"Our":[70,107],"sketch":[71,78],"builds":[72],"upon":[73],"extends":[75],"Lp":[77],"Indyk":[80],"with":[81],"significant":[82],"additional":[83],"innovations.":[84],"We":[85],"present":[86],"calculations":[87],"showing":[88],"that":[89],"our":[90],"data":[91],"streaming":[92],"algorithm":[93,108],"feasible":[95],"high":[97],"link":[98],"speeds":[99],"using":[100,119],"commodity":[101],"CPU/memory":[102],"reasonable":[105],"cost.":[106],"be":[112],"very":[113],"accurate":[114],"practice":[116],"via":[117],"simulations,":[118],"traces":[121],"collected":[122],"tier-1":[125],"ISP":[126],"backbone":[127],"link.":[128]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
