{"id":"https://openalex.org/W4406860636","doi":"https://doi.org/10.1109/ipccc59868.2024.10850123","title":"The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning","display_name":"The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning","publication_year":2024,"publication_date":"2024-11-22","ids":{"openalex":"https://openalex.org/W4406860636","doi":"https://doi.org/10.1109/ipccc59868.2024.10850123"},"language":"en","primary_location":{"id":"doi:10.1109/ipccc59868.2024.10850123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipccc59868.2024.10850123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Performance, Computing, and Communications Conference (IPCCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5062394655","display_name":"Manh V. Nguyen","orcid":"https://orcid.org/0009-0003-6909-9766"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manh V. Nguyen","raw_affiliation_strings":["Kennesaw State University,College of Computing and Software Engineering,Georgia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,College of Computing and Software Engineering,Georgia,USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012329541","display_name":"Liang Zhao","orcid":"https://orcid.org/0000-0003-0678-489X"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Zhao","raw_affiliation_strings":["Kennesaw State University,College of Computing and Software Engineering,Georgia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,College of Computing and Software Engineering,Georgia,USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100940541","display_name":"Bobin Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bobin Deng","raw_affiliation_strings":["Kennesaw State University,College of Computing and Software Engineering,Georgia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,College of Computing and Software Engineering,Georgia,USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054738532","display_name":"William Severa","orcid":"https://orcid.org/0000-0002-8740-220X"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Severa","raw_affiliation_strings":["Sandia National Laboratories,Department of Cognitive &#x0026; Emerging Computing,New Mexico,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories,Department of Cognitive &#x0026; Emerging Computing,New Mexico,USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067350458","display_name":"Honghui Xu","orcid":"https://orcid.org/0000-0002-0053-5676"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honghui Xu","raw_affiliation_strings":["Kennesaw State University,College of Computing and Software Engineering,Georgia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,College of Computing and Software Engineering,Georgia,USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100743605","display_name":"Shaoen Wu","orcid":"https://orcid.org/0000-0002-4768-6930"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaoen Wu","raw_affiliation_strings":["Kennesaw State University,College of Computing and Software Engineering,Georgia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,College of Computing and Software Engineering,Georgia,USA","institution_ids":["https://openalex.org/I172980758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9995999932289124,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9869999885559082,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9768999814987183,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8078454732894897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7947669625282288},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6242749691009521},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5505332350730896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46506693959236145},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.41013967990875244},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.34329357743263245}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8078454732894897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947669625282288},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6242749691009521},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5505332350730896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46506693959236145},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.41013967990875244},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.34329357743263245},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipccc59868.2024.10850123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipccc59868.2024.10850123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Performance, Computing, and Communications Conference (IPCCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1484004770","https://openalex.org/W2978015420","https://openalex.org/W2984844508","https://openalex.org/W3120009304","https://openalex.org/W3192649393","https://openalex.org/W3202425151","https://openalex.org/W3213984553","https://openalex.org/W4226357425","https://openalex.org/W4283790910","https://openalex.org/W4307438232","https://openalex.org/W4365143606","https://openalex.org/W4385568263","https://openalex.org/W4385767965","https://openalex.org/W4386432086","https://openalex.org/W4386623177","https://openalex.org/W4389795421","https://openalex.org/W4392910825","https://openalex.org/W6728757088","https://openalex.org/W6752012617","https://openalex.org/W6769862319","https://openalex.org/W6838820759","https://openalex.org/W6849975662","https://openalex.org/W6853215400","https://openalex.org/W6856400181","https://openalex.org/W6862324516"],"related_works":["https://openalex.org/W3126544799","https://openalex.org/W3104333581","https://openalex.org/W2542565870","https://openalex.org/W3111828357","https://openalex.org/W3018398156","https://openalex.org/W2770593030","https://openalex.org/W2920832517","https://openalex.org/W4388827557","https://openalex.org/W3154990682","https://openalex.org/W4391549771"],"abstract_inverted_index":{"Spiking":[0],"Neural":[1,24],"Networks":[2,25],"(SNNs)":[3],"have":[4],"recently":[5],"gained":[6],"significant":[7],"interest":[8],"in":[9,12,74,168],"on-chip":[10],"learning":[11],"embedded":[13],"devices":[14,46],"and":[15,47,58,173,176],"emerged":[16],"as":[17,131,133],"an":[18],"energy-efficient":[19],"alternative":[20],"to":[21,28,31,91,112,124,130],"conventional":[22],"Artificial":[23],"(ANNs).":[26],"However,":[27],"extend":[29],"SNNs":[30,70,106],"a":[32,82],"Federated":[33,84],"Learning":[34,85],"(FL)":[35],"setting":[36],"involving":[37],"collaborative":[38],"model":[39,154,174],"training,":[40],"the":[41,44,48,52,66,93,102,116,120,136,139,145,166],"communication":[42,73,146,171],"between":[43],"local":[45],"remote":[49],"server":[50],"remains":[51],"bottleneck,":[53],"which":[54],"is":[55],"often":[56],"restricted":[57],"costly.":[59],"In":[60],"this":[61,78],"paper,":[62],"we":[63,80],"first":[64],"explore":[65],"inherent":[67],"robustness":[68],"of":[69,122,135,138,170],"under":[71],"noisy":[72],"FL.":[75],"Building":[76],"upon":[77],"foundation,":[79],"propose":[81],"novel":[83],"with":[86,105,183],"Top-\u03ba":[87],"Sparsification":[88],"(FLTS)":[89],"algorithm":[90],"reduce":[92],"bandwidth":[94,109],"usage":[95],"for":[96,179],"FL":[97,182],"training.":[98,155],"We":[99,142],"discover":[100],"that":[101,160],"proposed":[103,162],"scheme":[104],"allows":[107],"more":[108],"savings":[110],"compared":[111],"ANNs":[113],"without":[114],"impacting":[115],"model\u2019s":[117],"accuracy.":[118],"Additionally,":[119],"number":[121],"parameters":[123],"be":[125,128],"communicated":[126],"can":[127],"reduced":[129],"low":[132],"6%":[134],"size":[137],"original":[140],"model.":[141],"further":[143],"improve":[144],"efficiency":[147],"by":[148],"enabling":[149],"dynamic":[150],"parameter":[151],"compression":[152],"during":[153],"Extensive":[156],"experiment":[157],"results":[158],"demonstrate":[159],"our":[161],"algorithms":[163],"significantly":[164],"outperform":[165],"baselines":[167],"terms":[169],"cost":[172],"accuracy":[175],"are":[177],"promising":[178],"practical":[180],"network-efficient":[181],"SNNs.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
