{"id":"https://openalex.org/W2020185638","doi":"https://doi.org/10.1145/1460412.1460493","title":"On the scaling properties of low power wireless links","display_name":"On the scaling properties of low power wireless links","publication_year":2008,"publication_date":"2008-11-05","ids":{"openalex":"https://openalex.org/W2020185638","doi":"https://doi.org/10.1145/1460412.1460493","mag":"2020185638"},"language":"en","primary_location":{"id":"doi:10.1145/1460412.1460493","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1460412.1460493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM conference on Embedded network sensor systems","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/A5048625305","display_name":"Tal Rusak","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tal Rusak","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060306684","display_name":"Philip Levis","orcid":"https://orcid.org/0000-0003-2934-2701"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip A. Levis","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048625305"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":0.2808,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58246425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9940999746322632,"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":0.9940999746322632,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9926999807357788,"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/T11187","display_name":"Nonlinear Dynamics and Pattern Formation","score":0.9824000000953674,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/burstiness","display_name":"Burstiness","score":0.9765822887420654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7310786247253418},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6466029286384583},{"id":"https://openalex.org/keywords/self-similarity","display_name":"Self-similarity","score":0.6241304278373718},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.5952407121658325},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5715400576591492},{"id":"https://openalex.org/keywords/physical-layer","display_name":"Physical layer","score":0.5183385610580444},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45880451798439026},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.4541941285133362},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.44830644130706787},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3837617337703705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13879293203353882},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12822824716567993},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09437909722328186}],"concepts":[{"id":"https://openalex.org/C2781023610","wikidata":"https://www.wikidata.org/wiki/Q17006304","display_name":"Burstiness","level":3,"score":0.9765822887420654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7310786247253418},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6466029286384583},{"id":"https://openalex.org/C119453123","wikidata":"https://www.wikidata.org/wiki/Q262372","display_name":"Self-similarity","level":2,"score":0.6241304278373718},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.5952407121658325},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5715400576591492},{"id":"https://openalex.org/C19247436","wikidata":"https://www.wikidata.org/wiki/Q192727","display_name":"Physical layer","level":3,"score":0.5183385610580444},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45880451798439026},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.4541941285133362},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.44830644130706787},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3837617337703705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13879293203353882},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12822824716567993},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09437909722328186},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1460412.1460493","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1460412.1460493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM conference on Embedded network sensor systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.6700000166893005,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1607632979","https://openalex.org/W2046430378","https://openalex.org/W2047282676","https://openalex.org/W2105818147","https://openalex.org/W2108481447","https://openalex.org/W2122471531","https://openalex.org/W2125580772","https://openalex.org/W2753297910","https://openalex.org/W3160254190"],"related_works":["https://openalex.org/W2153423886","https://openalex.org/W1544251502","https://openalex.org/W2205758592","https://openalex.org/W2128796442","https://openalex.org/W4236369288","https://openalex.org/W4243420524","https://openalex.org/W2016840637","https://openalex.org/W267165598","https://openalex.org/W2048912196","https://openalex.org/W2208977523"],"abstract_inverted_index":{"We":[0,15,73],"study":[1],"the":[2,10,25,33,36,78,81],"time-scaling":[3],"characteristics":[4,97],"of":[5,32,35],"low-power":[6],"wireless":[7,50],"communication":[8],"at":[9,21,70],"physical":[11,82],"and":[12,91,104],"link":[13],"layers.":[14],"observe":[16],"that":[17,45,80],"links":[18,54],"are":[19,55],"bursty":[20],"many":[22,49,71],"time":[23,37],"scales:":[24],"packet":[26],"reception":[27],"rate":[28],"(PRR)":[29],"varies":[30],"regardless":[31],"length":[34],"scale":[38],"considered.":[39],"Using":[40],"wavelet":[41],"analysis,":[42],"we":[43],"find":[44],"RSSI":[46,75],"variations":[47],"in":[48],"sensor":[51],"network":[52],"(WSN)":[53],"consistent":[56,85],"with":[57,62,86],"statistical":[58],"self-similarity":[59],"but":[60],"not":[61,94],"long":[63],"range":[64],"dependence,":[65],"which":[66],"can":[67],"explain":[68],"burstiness":[69],"scales.":[72],"relate":[74],"variance":[76],"to":[77,101],"probability":[79],"layer":[83],"is":[84],"self-similarity.":[87],"Current":[88],"simulation":[89,103],"models":[90],"protocols":[92],"do":[93],"take":[95],"these":[96],"into":[98],"account,":[99],"leading":[100],"inaccurate":[102],"sub-optimal":[105],"protocol":[106],"performance.":[107]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
