Memory Efficient Edge Addition Designs for Large and Dynamic Social Networks
The availability of large volumes of social network data from a variety of social and socio-technical networks has greatly increased. These networks provide critical insights into understanding various domains including business, healthcare, and disaster management. The relationships and interaction...
Uloženo v:
| Vydáno v: | 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) s. 975 - 984 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.06.2021
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | The availability of large volumes of social network data from a variety of social and socio-technical networks has greatly increased. These networks provide critical insights into understanding various domains including business, healthcare, and disaster management. The relationships and interactions between different entities represented in most of these data sources are constantly evolving. Graph processing and analysis methodologies that can effectively integrate data changes while minimizing recomputations are needed to handle these dynamic networks. In addition, the size of these information sources is constantly increasing, therefore we need designs that can perform analysis that are memory efficient in order to address resource constraints. In this paper, we show how our anytime anywhere framework can be used to construct memory-efficient closeness centrality algorithms. In particular, we will show how dynamic edge additions can be efficiently handled in the proposed scheme. |
|---|---|
| AbstractList | The availability of large volumes of social network data from a variety of social and socio-technical networks has greatly increased. These networks provide critical insights into understanding various domains including business, healthcare, and disaster management. The relationships and interactions between different entities represented in most of these data sources are constantly evolving. Graph processing and analysis methodologies that can effectively integrate data changes while minimizing recomputations are needed to handle these dynamic networks. In addition, the size of these information sources is constantly increasing, therefore we need designs that can perform analysis that are memory efficient in order to address resource constraints. In this paper, we show how our anytime anywhere framework can be used to construct memory-efficient closeness centrality algorithms. In particular, we will show how dynamic edge additions can be efficiently handled in the proposed scheme. |
| Author | Santos, Eunice E. Murugappan, Vairavan Korah, John |
| Author_xml | – sequence: 1 givenname: Eunice E. surname: Santos fullname: Santos, Eunice E. email: eesantos@illinois.edu organization: University of Illinois at Urbana-Champaign,School of Information Sciences,Champaign,IL,USA – sequence: 2 givenname: Vairavan surname: Murugappan fullname: Murugappan, Vairavan email: vm13@illinois.edu organization: University of Illinois at Urbana-Champaign,School of Information Sciences,Champaign,IL,USA – sequence: 3 givenname: John surname: Korah fullname: Korah, John email: jkorah@cpp.edu organization: California State Polytechnic University,Department of Computer Science,Pomona,CA,USA |
| BookMark | eNotzN1KwzAYgOEIeuCmVyBIbqA1X36bw7FWN6g6mOLhyPIzgmsiaUF69wp69B488C7QZcrJI3QPpAYg-mG7a3f7D0GVhpoSCjUhIMQFWoCUgjOhFFyj_tkPucy4CyHa6NOEO3fyeOVcnGJOuPVjPKURh1xwb8ovmeRwOyczRIv32UZzxi9--s7lc7xBV8GcR3_73yV6f-ze1puqf33arld9FSlhU3U0DgwIR7QNVoAWTh8DkY3lSjlJmLCqcYZ7KrnRkiltRGCuMQyCA8cpW6K7v2_03h--ShxMmQ-aSyKlYj8bOksI |
| CODEN | IEEPAD |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/IPDPSW52791.2021.00155 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 1665435771 9781665435772 |
| EndPage | 984 |
| ExternalDocumentID | 9460667 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i203t-bad1a15d09cfc5195d9bf068c477d6035c78da4e264a96379a5f3d8a31fd1d423 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000689576200125&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Thu Jun 29 18:38:10 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i203t-bad1a15d09cfc5195d9bf068c477d6035c78da4e264a96379a5f3d8a31fd1d423 |
| PageCount | 10 |
| ParticipantIDs | ieee_primary_9460667 |
| PublicationCentury | 2000 |
| PublicationDate | 2021-June |
| PublicationDateYYYYMMDD | 2021-06-01 |
| PublicationDate_xml | – month: 06 year: 2021 text: 2021-June |
| PublicationDecade | 2020 |
| PublicationTitle | 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) |
| PublicationTitleAbbrev | IPDPSW |
| PublicationYear | 2021 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.7668223 |
| Snippet | The availability of large volumes of social network data from a variety of social and socio-technical networks has greatly increased. These networks provide... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 975 |
| SubjectTerms | Anytime anywhere algorithms Conferences Disaster management Distributed processing Graph algorithms and analysis Heuristic algorithms Large-scale dynamic social network analysis Medical services Memory efficient graph algorithms Memory management Parallel/Distribated algorithms Social networking (online) |
| Title | Memory Efficient Edge Addition Designs for Large and Dynamic Social Networks |
| URI | https://ieeexplore.ieee.org/document/9460667 |
| WOSCitedRecordID | wos000689576200125&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/eLvHCXMwlV1NSwMxEB1q8eBJpRW_ycGjaTe72U1yFNuiUMuCir2VJJOVXrbSD8F_b5ItFcGLtxBIAhPCvCTvzQO4MR52u7xwVPFUUy4do6ZSkqLIrM0l-vubjWYTYjKR06kqW3C708I45yL5zPVCM_7l48JuwlNZX_EAt8Ue7AlRNFqtreiXJar_WA7K57c8FSrc-1LWi3jgl2tKTBqjw_8tdwTdH_UdKXd55Rharu7A-ClQYr_IMJZ88OPIEN8duUOMnCsyiEyMFfEYlIwDu5voGsmg8ZsnjQiXTBrO96oLr6Phy_0D3Toh0HmaZGtqNDLNckyUrWyoB4PKVEkhLRcCiyTLrZCoufPoRvsTJZTOqwylzliFDD1iOoF2vajdKRCmeeInsR6uSu6EMtZm2vCUG-6RhOJn0AmRmH00xS5m2yCc_919AQch1A136hLa6-XGXcG-_VzPV8vruEPfcUmUSg |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NSwMxEB1qFfSk0orf5uDRbTe72SY5im1pcbsUrNhbyWay0stW-iH4702ypSJ48RYCSWBCyJvkvXkA97mF3SbpmECySAVMGBrkhRQB8ljrRKDN37Q3m-BZJqZTOa7Bw04LY4zx5DPTck3_l48LvXFPZW3JHNzme7CfMJv3VGqtreyXhrI9HHfHL29JxKXL_CLa8ojgl2-Kvzb6x_9b8ASaP_o7Mt7dLKdQM2UD0pEjxX6Rni_6YMeRHr4b8ojoWVek67kYK2JRKEkdv5uoEkm3cpwnlQyXZBXre9WE135v8jQItl4IwTwK43WQK6SKJhhKXWhXEQZlXoQdoRnn2AnjRHOBihmLb5Q9U1yqpIhRqJgWSNFipjOol4vSnAOhioV2Em0Bq2CGy1zrWOUsYjmzWEKyC2i4SMw-qnIXs20QLv_uvoPDwWSUztJh9nwFRy7sFZPqGurr5cbcwIH-XM9Xy1u_W99YOZeR |
| 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=2021+IEEE+International+Parallel+and+Distributed+Processing+Symposium+Workshops+%28IPDPSW%29&rft.atitle=Memory+Efficient+Edge+Addition+Designs+for+Large+and+Dynamic+Social+Networks&rft.au=Santos%2C+Eunice+E.&rft.au=Murugappan%2C+Vairavan&rft.au=Korah%2C+John&rft.date=2021-06-01&rft.pub=IEEE&rft.spage=975&rft.epage=984&rft_id=info:doi/10.1109%2FIPDPSW52791.2021.00155&rft.externalDocID=9460667 |