Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks
This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. De...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2022-11 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Zhang, Wei Wang, Shafei Pan, Ye Li, Qiang Lin, Jingran Wu, Xiaoxiao |
description | This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. Depending on the computation burden at the fog nodes, the tasks may be computed by the fog nodes or further offloaded to the cloud via capacity-limited fronthaul links. To compute all UEs' tasks as fast as possible, joint optimization of UE-Fog association, radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs. This min-max problem is formulated as a mixed integer nonlinear program (MINP). We first show that the MINP can be reformulated as a continuous optimization problem, and then employ the majorization minimization (MM) approach to find a solution. The MM approach that we develop is unconventional in that -- each MM subproblem can be solved inexactly with the same provable convergence guarantee as the conventional exact MM, thereby reducing the complexity of each MM iteration. In addition, we also consider a cooperative offloading model, where the fog nodes compress-and-forward their received signals to the cloud. Under this model, a similar min-max latency optimization problem is formulated and tackled again by the inexact MM approach. Simulation results show that the proposed algorithms outperform some heuristic offloading strategies, and that the cooperative offloading can better exploit the transmission diversity to attain better latency performance than the non-cooperative one. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2262538394</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2262538394</sourcerecordid><originalsourceid>FETCH-proquest_journals_22625383943</originalsourceid><addsrcrecordid>eNqNis0KgkAYAJcgSMp3WOgs2LdqdgxJOmRBRFcR25U13c_2h6inT6gH6DQMMxPiAWOrII0AZsQ3pg3DEJI1xDHzyPVQWa7qFy2kkr18V1aiogI1LVxnpTNc0wz7wdlvOQnRYXWTqqFS0Ryb4Dwa0m1dc2Pokdsn6rtZkKmoOsP9H-dkme8u2T4YND4cN7Zs0Wk1phIggZilbBOx_64PPPhBdg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2262538394</pqid></control><display><type>article</type><title>Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks</title><source>Free E- Journals</source><creator>Zhang, Wei ; Wang, Shafei ; Pan, Ye ; Li, Qiang ; Lin, Jingran ; Wu, Xiaoxiao</creator><creatorcontrib>Zhang, Wei ; Wang, Shafei ; Pan, Ye ; Li, Qiang ; Lin, Jingran ; Wu, Xiaoxiao</creatorcontrib><description>This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. Depending on the computation burden at the fog nodes, the tasks may be computed by the fog nodes or further offloaded to the cloud via capacity-limited fronthaul links. To compute all UEs' tasks as fast as possible, joint optimization of UE-Fog association, radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs. This min-max problem is formulated as a mixed integer nonlinear program (MINP). We first show that the MINP can be reformulated as a continuous optimization problem, and then employ the majorization minimization (MM) approach to find a solution. The MM approach that we develop is unconventional in that -- each MM subproblem can be solved inexactly with the same provable convergence guarantee as the conventional exact MM, thereby reducing the complexity of each MM iteration. In addition, we also consider a cooperative offloading model, where the fog nodes compress-and-forward their received signals to the cloud. Under this model, a similar min-max latency optimization problem is formulated and tackled again by the inexact MM approach. Simulation results show that the proposed algorithms outperform some heuristic offloading strategies, and that the cooperative offloading can better exploit the transmission diversity to attain better latency performance than the non-cooperative one.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Computation offloading ; Computer simulation ; Mixed integer ; Nodes ; Optimization ; Radio</subject><ispartof>arXiv.org, 2022-11</ispartof><rights>2022. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,784</link.rule.ids></links><search><creatorcontrib>Zhang, Wei</creatorcontrib><creatorcontrib>Wang, Shafei</creatorcontrib><creatorcontrib>Pan, Ye</creatorcontrib><creatorcontrib>Li, Qiang</creatorcontrib><creatorcontrib>Lin, Jingran</creatorcontrib><creatorcontrib>Wu, Xiaoxiao</creatorcontrib><title>Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks</title><title>arXiv.org</title><description>This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. Depending on the computation burden at the fog nodes, the tasks may be computed by the fog nodes or further offloaded to the cloud via capacity-limited fronthaul links. To compute all UEs' tasks as fast as possible, joint optimization of UE-Fog association, radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs. This min-max problem is formulated as a mixed integer nonlinear program (MINP). We first show that the MINP can be reformulated as a continuous optimization problem, and then employ the majorization minimization (MM) approach to find a solution. The MM approach that we develop is unconventional in that -- each MM subproblem can be solved inexactly with the same provable convergence guarantee as the conventional exact MM, thereby reducing the complexity of each MM iteration. In addition, we also consider a cooperative offloading model, where the fog nodes compress-and-forward their received signals to the cloud. Under this model, a similar min-max latency optimization problem is formulated and tackled again by the inexact MM approach. Simulation results show that the proposed algorithms outperform some heuristic offloading strategies, and that the cooperative offloading can better exploit the transmission diversity to attain better latency performance than the non-cooperative one.</description><subject>Algorithms</subject><subject>Computation offloading</subject><subject>Computer simulation</subject><subject>Mixed integer</subject><subject>Nodes</subject><subject>Optimization</subject><subject>Radio</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNis0KgkAYAJcgSMp3WOgs2LdqdgxJOmRBRFcR25U13c_2h6inT6gH6DQMMxPiAWOrII0AZsQ3pg3DEJI1xDHzyPVQWa7qFy2kkr18V1aiogI1LVxnpTNc0wz7wdlvOQnRYXWTqqFS0Ryb4Dwa0m1dc2Pokdsn6rtZkKmoOsP9H-dkme8u2T4YND4cN7Zs0Wk1phIggZilbBOx_64PPPhBdg</recordid><startdate>20221127</startdate><enddate>20221127</enddate><creator>Zhang, Wei</creator><creator>Wang, Shafei</creator><creator>Pan, Ye</creator><creator>Li, Qiang</creator><creator>Lin, Jingran</creator><creator>Wu, Xiaoxiao</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20221127</creationdate><title>Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks</title><author>Zhang, Wei ; Wang, Shafei ; Pan, Ye ; Li, Qiang ; Lin, Jingran ; Wu, Xiaoxiao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_22625383943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Computation offloading</topic><topic>Computer simulation</topic><topic>Mixed integer</topic><topic>Nodes</topic><topic>Optimization</topic><topic>Radio</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Wei</creatorcontrib><creatorcontrib>Wang, Shafei</creatorcontrib><creatorcontrib>Pan, Ye</creatorcontrib><creatorcontrib>Li, Qiang</creatorcontrib><creatorcontrib>Lin, Jingran</creatorcontrib><creatorcontrib>Wu, Xiaoxiao</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Wei</au><au>Wang, Shafei</au><au>Pan, Ye</au><au>Li, Qiang</au><au>Lin, Jingran</au><au>Wu, Xiaoxiao</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks</atitle><jtitle>arXiv.org</jtitle><date>2022-11-27</date><risdate>2022</risdate><eissn>2331-8422</eissn><abstract>This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. Depending on the computation burden at the fog nodes, the tasks may be computed by the fog nodes or further offloaded to the cloud via capacity-limited fronthaul links. To compute all UEs' tasks as fast as possible, joint optimization of UE-Fog association, radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs. This min-max problem is formulated as a mixed integer nonlinear program (MINP). We first show that the MINP can be reformulated as a continuous optimization problem, and then employ the majorization minimization (MM) approach to find a solution. The MM approach that we develop is unconventional in that -- each MM subproblem can be solved inexactly with the same provable convergence guarantee as the conventional exact MM, thereby reducing the complexity of each MM iteration. In addition, we also consider a cooperative offloading model, where the fog nodes compress-and-forward their received signals to the cloud. Under this model, a similar min-max latency optimization problem is formulated and tackled again by the inexact MM approach. Simulation results show that the proposed algorithms outperform some heuristic offloading strategies, and that the cooperative offloading can better exploit the transmission diversity to attain better latency performance than the non-cooperative one.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2022-11 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2262538394 |
source | Free E- Journals |
subjects | Algorithms Computation offloading Computer simulation Mixed integer Nodes Optimization Radio |
title | Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T21%3A54%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Latency%20Minimization%20for%20Multiuser%20Computation%20Offloading%20in%20Fog-Radio%20Access%20Networks&rft.jtitle=arXiv.org&rft.au=Zhang,%20Wei&rft.date=2022-11-27&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2262538394%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2262538394&rft_id=info:pmid/&rfr_iscdi=true |