A Partition-Based Implementation of the Relaxed ADMM for Distributed Convex Optimization over Lossy Networks
In this paper we propose a distributed implementation of the relaxed Alternating Direction Method of Multipliers algorithm (R-ADMM) for optimization of a separable convex cost function, whose terms are stored by a set of interacting agents, one for each agent. Specifically the local cost stored by e...
Saved in:
| Published in: | Proceedings of the IEEE Conference on Decision & Control pp. 3379 - 3384 |
|---|---|
| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.12.2018
|
| Subjects: | |
| ISSN: | 2576-2370 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | In this paper we propose a distributed implementation of the relaxed Alternating Direction Method of Multipliers algorithm (R-ADMM) for optimization of a separable convex cost function, whose terms are stored by a set of interacting agents, one for each agent. Specifically the local cost stored by each node is in general a function of both the state of the node and the states of its neighbors, a framework that we refer to as 'partition-based' optimization. This framework presents a great flexibility and can be adapted to a large number of different applications. By recasting the problem into an operator theoretical framework, the proposed algorithm is shown to be provably robust against random packet losses that might occur in the communication between neighboring nodes. Finally, the effectiveness of the proposed algorithm is confirmed by a set of compelling numerical simulations run over random geometric graphs subject to i.i.d. random packet losses. |
|---|---|
| AbstractList | In this paper we propose a distributed implementation of the relaxed Alternating Direction Method of Multipliers algorithm (R-ADMM) for optimization of a separable convex cost function, whose terms are stored by a set of interacting agents, one for each agent. Specifically the local cost stored by each node is in general a function of both the state of the node and the states of its neighbors, a framework that we refer to as 'partition-based' optimization. This framework presents a great flexibility and can be adapted to a large number of different applications. By recasting the problem into an operator theoretical framework, the proposed algorithm is shown to be provably robust against random packet losses that might occur in the communication between neighboring nodes. Finally, the effectiveness of the proposed algorithm is confirmed by a set of compelling numerical simulations run over random geometric graphs subject to i.i.d. random packet losses. |
| Author | Todescato, M. Schenato, L. Carli, R. Bastianello, N. |
| Author_xml | – sequence: 1 givenname: N. surname: Bastianello fullname: Bastianello, N. organization: Department of Information Engineering (DEI), University of Padova, Italy – sequence: 2 givenname: R. surname: Carli fullname: Carli, R. organization: Department of Information Engineering (DEI), University of Padova, Italy – sequence: 3 givenname: L. surname: Schenato fullname: Schenato, L. organization: Department of Information Engineering (DEI), University of Padova, Italy – sequence: 4 givenname: M. surname: Todescato fullname: Todescato, M. organization: Bosch Center for Artificial Intelligence, Renningen, Germany |
| BookMark | eNotUE1PwjAYrkYTAbmbeOkfGLbrStsjDj9IQIzRM-nWt7G6raStCP56Z-T05Pk8PEN01vkOELqiZEIpUTflvJzkhMqJnFIlcnWCxkpIylnPmeL8FA1yLqZZzgS5QMMYPwhhShVsgJoZftYhueR8l93qCAYv2m0DLXRJ_4nYW5zeAb9Ao_e9O5uvVtj6gOcupuCqr9SLpe92sMfrbXKt-zn2dhDw0sd4wE-Qvn34jJfo3OomwviII_R2f_daPmbL9cOinC0zRwVPWV1pxai0oqJTrmVdF9ZIJomoaVEAgC1YbZjJqamMtFxzqSpueU6UNLRWio3Q9f-u69ObbXCtDofN8Rz2C9xzW6c |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IH CBEJK RIE RIO |
| DOI | 10.1109/CDC.2018.8619729 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan (POP) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP) 1998-present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE/IET Electronic Library url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISBN | 9781538613955 1538613956 |
| EISSN | 2576-2370 |
| EndPage | 3384 |
| ExternalDocumentID | 8619729 |
| Genre | orig-research |
| GroupedDBID | 29P 6IE 6IH 6IL 6IN AAWTH ABLEC ACGFS ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK IJVOP M43 OCL RIE RIL RIO |
| ID | FETCH-LOGICAL-i175t-cba9318f7b165a8cc4fd83807c144eeef43cd3d21dbd8f5a589b5f52098d1c993 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 8 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000458114803028&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 03:05:39 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i175t-cba9318f7b165a8cc4fd83807c144eeef43cd3d21dbd8f5a589b5f52098d1c993 |
| PageCount | 6 |
| ParticipantIDs | ieee_primary_8619729 |
| PublicationCentury | 2000 |
| PublicationDate | 2018-Dec. |
| PublicationDateYYYYMMDD | 2018-12-01 |
| PublicationDate_xml | – month: 12 year: 2018 text: 2018-Dec. |
| PublicationDecade | 2010 |
| PublicationTitle | Proceedings of the IEEE Conference on Decision & Control |
| PublicationTitleAbbrev | CDC |
| PublicationYear | 2018 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0039943 |
| Score | 1.7528478 |
| Snippet | In this paper we propose a distributed implementation of the relaxed Alternating Direction Method of Multipliers algorithm (R-ADMM) for optimization of a... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 3379 |
| SubjectTerms | ADMM Convergence Convex functions distributed optimization Nickel operator theory Optimization partition-based optimization Partitioning algorithms Peaceman-Rachford operator Peer-to-peer computing splitting methods Trajectory |
| Title | A Partition-Based Implementation of the Relaxed ADMM for Distributed Convex Optimization over Lossy Networks |
| URI | https://ieeexplore.ieee.org/document/8619729 |
| WOSCitedRecordID | wos000458114803028&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 | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8JAEJ4A8aAXH2B8Zw8eXWhtS3ePWCQeBDlowo1s95GQSCE8DP57Z9qCmnjx1mzTNp1J9_u2-818ALdekCodC58rRDMeKuFxaXTEkWw4G8i2cNLlZhPxYCBGIzmswN2uFsZam4vPbJMO8718M9Nr-lXWEm0yyZJVqMZxXNRqbWddxNkw2G5DerKVdBPSbYlmec0v85QcO3qH_3vqETS-i_DYcAcvx1Cx2Qkc_OgfWIf3DhtS6im4_AHxyLC82--0LCjK2MwxZHiMJG8bPNvp9vsMaSrrUr9csrrCwYSE5xv2gpPHtKzKZCTsZM8IoJ9sUAjFlw146z2-Jk-8tE_gE-QEK65TJfGLdXHqtyMltA6dEdRfXuMiCt_ShYE2gbn3TWqEi1QkZBo5ksUI42vkLadQy2aZPQMmjMalD4K7VjrUyHSNs56K_RDv5WwankOd4jaeFx0yxmXILv4evoR9Sk0hCrmC2mqxttewpz9Wk-XiJk_rF6vpptQ |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8JAEJ4gmqgXH2h8uwePLrR0S3ePWCQYoXLAhBtp95GQSDE8DP57Z9uCmnjx1mzTNp1J9_u2-818AHeOl8Qy4C6NEc0oi7lDhZI-RbJhtCca3AiTmU0EUcSHQ9Evwf2mFkZrnYnPdNUeZnv5aiqX9ldZjTesSZbYgm2fsbqbV2ut511EWuatNyIdUQtboVVu8Wpx1S_7lAw92gf_e-4hnHyX4ZH-BmCOoKTTY9j_0UGwAm9N0rfJt-GlD4hIimT9fidFSVFKpoYgxyNW9LbCs81Wr0eQqJKW7Zhrza5wMLTS8xV5weljUtRlEivtJF2E0E8S5VLx-Qm8th8HYYcWBgp0jKxgQWUSC_xmTZC4DT_mUjKjuO0wL3EZhW9pmCeVp-quShQ3fuxzkfjGCmO4ciUyl1Mop9NUnwHhSuLiB-FdxpJJ5LrKaCcOXIb3Mjph51CxcRu95z0yRkXILv4evoXdzqDXHXWfoudL2LNpyiUiV1BezJb6Gnbkx2I8n91kKf4Cg3eqGw |
| 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%3Abook&rft.genre=proceeding&rft.title=Proceedings+of+the+IEEE+Conference+on+Decision+%26+Control&rft.atitle=A+Partition-Based+Implementation+of+the+Relaxed+ADMM+for+Distributed+Convex+Optimization+over+Lossy+Networks&rft.au=Bastianello%2C+N.&rft.au=Carli%2C+R.&rft.au=Schenato%2C+L.&rft.au=Todescato%2C+M.&rft.date=2018-12-01&rft.pub=IEEE&rft.eissn=2576-2370&rft.spage=3379&rft.epage=3384&rft_id=info:doi/10.1109%2FCDC.2018.8619729&rft.externalDocID=8619729 |