Consensus Based Distributed Spectral Radius Estimation
A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of the adjacency matrix, and is a useful characterization of the network graph. Conventionally, centralized methods are used to compute the spec...
Uloženo v:
| Vydáno v: | IEEE signal processing letters Ročník 27; s. 1045 - 1049 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 1070-9908, 1558-2361 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of the adjacency matrix, and is a useful characterization of the network graph. Conventionally, centralized methods are used to compute the spectral radius, which involves eigenvalue decomposition of the adjacency matrix of the underlying graph. Our distributed algorithm uses a simple update rule to reach consensus on the spectral radius, using only local communications. We consider time-varying graphs to model packet loss and imperfect transmissions, and provide the convergence characteristics of our algorithm, for both static and time-varying graphs. We prove that the convergence error is a function of principal eigenvector of adjacency matrix of the graph and reduces as <inline-formula><tex-math notation="LaTeX">\mathcal {O}(1/t)</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">t</tex-math></inline-formula> is the number of iterations. The algorithm works for any connected graph structure. Simulation results supporting the theory are also presented. |
|---|---|
| AbstractList | A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of the adjacency matrix, and is a useful characterization of the network graph. Conventionally, centralized methods are used to compute the spectral radius, which involves eigenvalue decomposition of the adjacency matrix of the underlying graph. Our distributed algorithm uses a simple update rule to reach consensus on the spectral radius, using only local communications. We consider time-varying graphs to model packet loss and imperfect transmissions, and provide the convergence characteristics of our algorithm, for both static and time-varying graphs. We prove that the convergence error is a function of principal eigenvector of adjacency matrix of the graph and reduces as [Formula Omitted], where [Formula Omitted] is the number of iterations. The algorithm works for any connected graph structure. Simulation results supporting the theory are also presented. A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of the adjacency matrix, and is a useful characterization of the network graph. Conventionally, centralized methods are used to compute the spectral radius, which involves eigenvalue decomposition of the adjacency matrix of the underlying graph. Our distributed algorithm uses a simple update rule to reach consensus on the spectral radius, using only local communications. We consider time-varying graphs to model packet loss and imperfect transmissions, and provide the convergence characteristics of our algorithm, for both static and time-varying graphs. We prove that the convergence error is a function of principal eigenvector of adjacency matrix of the graph and reduces as <inline-formula><tex-math notation="LaTeX">\mathcal {O}(1/t)</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">t</tex-math></inline-formula> is the number of iterations. The algorithm works for any connected graph structure. Simulation results supporting the theory are also presented. |
| Author | Spanias, Andreas Tepedelenlioglu, Cihan Muniraju, Gowtham |
| Author_xml | – sequence: 1 givenname: Gowtham orcidid: 0000-0003-0532-2896 surname: Muniraju fullname: Muniraju, Gowtham email: gmuniraj@asu.edu organization: School of ECEE, Arizona State University, Tempe, AZ, USA – sequence: 2 givenname: Cihan orcidid: 0000-0002-9180-1158 surname: Tepedelenlioglu fullname: Tepedelenlioglu, Cihan email: cihan@asu.edu organization: School of ECEE, Arizona State University, Tempe, AZ, USA – sequence: 3 givenname: Andreas orcidid: 0000-0003-0306-9348 surname: Spanias fullname: Spanias, Andreas email: spanias@asu.edu organization: School of ECEE, Arizona State University, Tempe, AZ, USA |
| BookMark | eNp9UE1LAzEQDVLBtnoXvBQ8b50k-5E5aq0fUFCsnkM2O4WUuluT7MF_39QWDx48zYN5b968N2KDtmuJsUsOU84BbxbL16kAAVMJIIWsTtiQF4XKhCz5IGGoIEMEdcZGIawBQHFVDFk569pAbejD5M4Eaib3LkTv6j4mvNySjd5sJm-mcYkxD9F9mui69pydrswm0MVxjtnHw_x99pQtXh6fZ7eLzArkMRMFNxWVZCzmvGoaYYWSVKKpS1J10aR1rRCbyqA1glsEwgaxlvkKwIKVY3Z9uLv13VdPIep11_s2WWqRCwGykgoSCw4s67sQPK301qdH_bfmoPft6NSO3rejj-0kSflHYl38iZYCu81_wquD0BHRrw9yjlWRyx3mlXML |
| CODEN | ISPLEM |
| CitedBy_id | crossref_primary_10_1109_LSP_2021_3050056 crossref_primary_10_3390_fi15050183 crossref_primary_10_1002_eng2_12710 crossref_primary_10_1016_j_sigpro_2022_108530 crossref_primary_10_1007_s11424_021_1218_6 crossref_primary_10_3390_math9233020 |
| Cites_doi | 10.1016/j.laa.2009.01.005 10.1109/JPROC.2011.2157884 10.1109/SSPD.2017.8233241 10.1016/0095-8956(86)90069-9 10.1109/TSP.2012.2211593 10.1109/TSIPN.2019.2945639 10.1109/JSAC.2005.843548 10.1109/ACC.2011.5990911 10.37236/2735 10.1109/IEEECONF44664.2019.9049018 10.1109/ACSSC.2018.8645297 10.2200/S00829ED1V01Y201802COM013 10.1016/j.laa.2007.06.005 10.1007/11533382_11 10.1109/CDC.2006.377282 10.1016/j.laa.2012.05.021 10.1109/TSP.2014.2355778 10.1109/43.159993 10.3390/s8084821 10.1007/978-3-540-74466-5_55 10.5614/ejgta.2014.2.1.5 10.1109/TSIPN.2018.2866322 10.1109/JSEN.2016.2612642 10.1016/j.sysconle.2013.03.002 10.1016/S0167-5060(08)70511-9 10.1137/1030002 10.1145/1284680.1284681 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D |
| DOI | 10.1109/LSP.2020.3003237 |
| DatabaseName | IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Xplore CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1558-2361 |
| EndPage | 1049 |
| ExternalDocumentID | 10_1109_LSP_2020_3003237 9119754 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: NSF CPS – fundername: Arizona State University funderid: 10.13039/100007482 |
| GroupedDBID | -~X .DC 0R~ 29I 3EH 4.4 5GY 5VS 6IK 85S 97E AAJGR AARMG AASAJ AAWTH AAYJJ ABAZT ABFSI ABQJQ ABVLG ACGFO ACGFS ACIWK AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 E.L EBS EJD F5P HZ~ H~9 ICLAB IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TAE TN5 VH1 AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D |
| ID | FETCH-LOGICAL-c291t-251a7e6eac9417dd2c283e69ab6e8b5d51ab899d7a9ca21c90e9d99b34f00c0c3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 6 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000546881400003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1070-9908 |
| IngestDate | Sun Nov 09 06:29:37 EST 2025 Sat Nov 29 01:48:54 EST 2025 Tue Nov 18 20:15:39 EST 2025 Wed Aug 27 02:36:38 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c291t-251a7e6eac9417dd2c283e69ab6e8b5d51ab899d7a9ca21c90e9d99b34f00c0c3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0003-0306-9348 0000-0003-0532-2896 0000-0002-9180-1158 |
| PQID | 2422037380 |
| PQPubID | 75747 |
| PageCount | 5 |
| ParticipantIDs | crossref_citationtrail_10_1109_LSP_2020_3003237 ieee_primary_9119754 crossref_primary_10_1109_LSP_2020_3003237 proquest_journals_2422037380 |
| PublicationCentury | 2000 |
| PublicationDate | 20200000 2020-00-00 20200101 |
| PublicationDateYYYYMMDD | 2020-01-01 |
| PublicationDate_xml | – year: 2020 text: 20200000 |
| PublicationDecade | 2020 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | IEEE signal processing letters |
| PublicationTitleAbbrev | LSP |
| PublicationYear | 2020 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | ref13 ref12 ref30 zhang (ref16) 2019 thomason (ref2) 1978; 3 ref11 ref10 zhang (ref14) 2018 zhang (ref15) 2018; 10 ref1 ref17 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 ref8 ref7 stevanovi? (ref9) 2015 ref4 ref3 ref6 ref5 |
| References_xml | – year: 2019 ident: ref16 article-title: Distributed network center area estimation – ident: ref6 doi: 10.1016/j.laa.2009.01.005 – start-page: 33 year: 2015 ident: ref9 article-title: Walk counts and the spectral radius of graphs publication-title: Bulletin – ident: ref21 doi: 10.1109/JPROC.2011.2157884 – ident: ref17 doi: 10.1109/SSPD.2017.8233241 – ident: ref10 doi: 10.1016/0095-8956(86)90069-9 – ident: ref28 doi: 10.1109/TSP.2012.2211593 – ident: ref24 doi: 10.1109/TSIPN.2019.2945639 – ident: ref3 doi: 10.1109/JSAC.2005.843548 – ident: ref20 doi: 10.1109/ACC.2011.5990911 – ident: ref1 doi: 10.37236/2735 – ident: ref25 doi: 10.1109/IEEECONF44664.2019.9049018 – ident: ref26 doi: 10.1109/ACSSC.2018.8645297 – volume: 10 start-page: 1 year: 2018 ident: ref15 publication-title: Synthesis Lectures on Communications doi: 10.2200/S00829ED1V01Y201802COM013 – ident: ref5 doi: 10.1016/j.laa.2007.06.005 – ident: ref4 doi: 10.1007/11533382_11 – ident: ref12 doi: 10.1109/CDC.2006.377282 – ident: ref7 doi: 10.1016/j.laa.2012.05.021 – ident: ref18 doi: 10.1109/TSP.2014.2355778 – ident: ref13 doi: 10.1109/43.159993 – ident: ref23 doi: 10.3390/s8084821 – year: 2018 ident: ref14 article-title: Distributed location detection in wireless sensor networks – ident: ref22 doi: 10.1007/978-3-540-74466-5_55 – ident: ref8 doi: 10.5614/ejgta.2014.2.1.5 – ident: ref27 doi: 10.1109/TSIPN.2018.2866322 – ident: ref30 doi: 10.1109/JSEN.2016.2612642 – ident: ref19 doi: 10.1016/j.sysconle.2013.03.002 – volume: 3 start-page: 259 year: 1978 ident: ref2 article-title: Hamiltonian cycles and uniquely edge colourable graphs publication-title: Annals of Discrete Mathematics doi: 10.1016/S0167-5060(08)70511-9 – ident: ref29 doi: 10.1137/1030002 – ident: ref11 doi: 10.1145/1284680.1284681 |
| SSID | ssj0008185 |
| Score | 2.3379314 |
| Snippet | A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1045 |
| SubjectTerms | Algebraic connectivity Algorithms Computer simulation consensus Convergence Distributed algorithms distributed estimation Eigenvalues Eigenvalues and eigenfunctions Eigenvectors Estimation Graphs Packet loss Signal processing algorithms Spectra spectral radius |
| Title | Consensus Based Distributed Spectral Radius Estimation |
| URI | https://ieeexplore.ieee.org/document/9119754 https://www.proquest.com/docview/2422037380 |
| Volume | 27 |
| WOSCitedRecordID | wos000546881400003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-2361 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0008185 issn: 1070-9908 databaseCode: RIE dateStart: 19940101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8NAEB5q8aAHX1WsVsnBi2DsZjfJZo4-WjxIKT6gt5DsbqEgrfTh73cmSUNBEbwtZDcJM7s73-zszAdwhTKw1kbGV7lNyEGJnI-YGz8ka2sx4tQBU5BN6MEgGY1w2ICbOhfGOVdcPnO33Cxi-XZmVnxU1kWOeUXhFmxprctcrXrXZcNT3i8U9DWRrEOSArvPr0NyBCX5pzSFJTOeb5igglPlx0ZcWJf-_v_-6wD2KhTp3ZVqP4SGmx7B7kZtwRbETMXJPBYL754slfUeuUQus1tRm1nn-YjDe8nshHr0aKGXOYzH8N7vvT08-RVJgm8kBkuf8EmmXUz7J4aBtlYaAgwuxiyPXZJHlh7n5FNZnaHJZGBQOLSkDhWOhTDCqBNoTmdTdwoerXenGIGhUmTns0TlUT62CYG4ELWQbeiu5ZaaqoI4E1l8pIUnITAlSacs6bSSdBuu6xGfZfWMP_q2WLJ1v0qobeisVZNWy2uREq6QgmsyibPfR53DDr-7PCvpQHM5X7kL2DZfy8liflnMnG-cS76V |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1ZS8NAEB5qFdQHb7FaNQ--CMZuNuc8erRUrKVohb6FZHcLBWmlh7_fmSQNBUXwbSGzbPj2mGN35gO4QulorX1lu6mOyEHxjY2YKtsjbavR59QBlZFNhN1uNBhgrwI3ZS6MMSZ7fGZuuZnd5euJWnCorIF85-V7a7Due5508myt8txl1ZO_MBQ0noiWl5ICG523HrmCkjxUWsSSOc9XlFDGqvLjKM70S2v3f3-2BzuFHWnd5RO_DxUzPoDtleqChxAwGSczWcyse9JV2nrkIrnMb0Vt5p3nIIf1mugRSTRpq-dZjEfw3mr2H9p2QZNgK4nO3CYLJQlNQCcoek6otVRkMpgAkzQwUepr-pySV6XDBFUiHYXCoKYJcb2hEEoo9xiq48nYnIBFO964bIOh65KmTyI39dOhjsiM8zAUsgaNJW6xKmqIM5XFR5z5EgJjQjpmpOMC6Rpclz0-8_oZf8geMrKlXAFqDerLqYmLDTaLybKQgqsyidPfe13CZrv_0ok7T93nM9jicfLISR2q8-nCnMOG-pqPZtOLbBV9A7U7wdw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Consensus+Based+Distributed+Spectral+Radius+Estimation&rft.jtitle=IEEE+signal+processing+letters&rft.au=Muniraju%2C+Gowtham&rft.au=Tepedelenlioglu%2C+Cihan&rft.au=Spanias%2C+Andreas&rft.date=2020&rft.pub=IEEE&rft.issn=1070-9908&rft.volume=27&rft.spage=1045&rft.epage=1049&rft_id=info:doi/10.1109%2FLSP.2020.3003237&rft.externalDocID=9119754 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1070-9908&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1070-9908&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1070-9908&client=summon |