Computation Rate Maximization for Multiuser Mobile Edge Computing Systems With Dynamic Energy Arrivals

This paper considers an energy harvesting (EH) based multiuser mobile edge computing (MEC) system, where each user utilizes the harvested energy from renewable energy sources to execute its computation tasks via computation of-floading and local computing. Towards maximizing the system weighted comp...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2021 IEEE/CIC International Conference on Communications in China (ICCC) s. 312 - 317
Hlavní autoři: Lin, Zhifei, Wang, Feng, Liu, Licheng
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 28.07.2021
Témata:
Benchmark testing
computation offloading
Convex functions
convex optimization
Energy harvesting
energy harvesting (EH)
Mobile edge computing (MEC)
Performance gain
Renewable energy sources
Resource management
Task analysis
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract This paper considers an energy harvesting (EH) based multiuser mobile edge computing (MEC) system, where each user utilizes the harvested energy from renewable energy sources to execute its computation tasks via computation of-floading and local computing. Towards maximizing the system weighted computation rate (i.e., the number of weighted users' computing bits within a finite time horizon) subject to the users' energy causality constraints due to dynamic energy arrivals, the decision for joint computation offloading and local computing over time is optimized over time. Assuming that the profile of channel state information and dynamic task arrivals at the users is known in advance, the weighted computation rate maximization problem becomes a convex optimization problem. Building on the Lagrange duality method, the well-structured optimal solution is analytically obtained. Both the users' local computing and offloading rates are shown to have a monotonically increasing structure. Numerical results show that the proposed design scheme can achieve a significant performance gain over the alternative benchmark schemes.
AbstractList This paper considers an energy harvesting (EH) based multiuser mobile edge computing (MEC) system, where each user utilizes the harvested energy from renewable energy sources to execute its computation tasks via computation of-floading and local computing. Towards maximizing the system weighted computation rate (i.e., the number of weighted users' computing bits within a finite time horizon) subject to the users' energy causality constraints due to dynamic energy arrivals, the decision for joint computation offloading and local computing over time is optimized over time. Assuming that the profile of channel state information and dynamic task arrivals at the users is known in advance, the weighted computation rate maximization problem becomes a convex optimization problem. Building on the Lagrange duality method, the well-structured optimal solution is analytically obtained. Both the users' local computing and offloading rates are shown to have a monotonically increasing structure. Numerical results show that the proposed design scheme can achieve a significant performance gain over the alternative benchmark schemes.
Author Lin, Zhifei
Liu, Licheng
Wang, Feng
Author_xml – sequence: 1
  givenname: Zhifei
  surname: Lin
  fullname: Lin, Zhifei
  email: linfei0922@outlook.com
  organization: School of Information Engineering, Guangdong University of Technology,Guangzhou,China,510006
– sequence: 2
  givenname: Feng
  surname: Wang
  fullname: Wang, Feng
  email: fengwang13@gdut.edu.cn
  organization: School of Information Engineering, Guangdong University of Technology,Guangzhou,China,510006
– sequence: 3
  givenname: Licheng
  surname: Liu
  fullname: Liu, Licheng
  email: celcliu@gdut.edu.cn
  organization: School of Information Engineering, Guangdong University of Technology,Guangzhou,China,510006
BookMark eNotj91KwzAcxSPohZs-gSB5gdZ8NunliFUHG4IOvBxp-28NtOlIU7E-vYPu6nc4cA7nrNC1Hzwg9EhJSinJn7bGGMmUUikjjKa51IRzcYVWNMukEFxLeYsaM_SnKdroBo8_bAS8t7-ud3-L0wwB76cuummEsxpK1wEu6hbwknO-xZ_zGKEf8ZeL3_h59rZ3FS48hHbGmxDcj-3GO3TTnAH3F67R4aU4mLdk9_66NZtd4hjhMcm4aoAyYKAotRpqUQlynsu1lUpTsBkwoara2pIx1iipdVmyjFda5azUfI0elloHAMdTcL0N8_HynP8DqUhUqg
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/ICCC52777.2021.9580334
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEL
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library (IEL) (UW System Shared)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 1665443855
9781665443852
EndPage 317
ExternalDocumentID 9580334
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i203t-637fe12e2e711a8ed4c4016638a5781ea6e247cdaab222f7588bb263c8792b83
IEDL.DBID RIE
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001353334200055&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 18:38:11 EDT 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i203t-637fe12e2e711a8ed4c4016638a5781ea6e247cdaab222f7588bb263c8792b83
PageCount 6
ParticipantIDs ieee_primary_9580334
PublicationCentury 2000
PublicationDate 2021-July-28
PublicationDateYYYYMMDD 2021-07-28
PublicationDate_xml – month: 07
  year: 2021
  text: 2021-July-28
  day: 28
PublicationDecade 2020
PublicationTitle 2021 IEEE/CIC International Conference on Communications in China (ICCC)
PublicationTitleAbbrev ICCC
PublicationYear 2021
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.7794538
Snippet This paper considers an energy harvesting (EH) based multiuser mobile edge computing (MEC) system, where each user utilizes the harvested energy from renewable...
SourceID ieee
SourceType Publisher
StartPage 312
SubjectTerms Benchmark testing
computation offloading
Convex functions
convex optimization
Energy harvesting
energy harvesting (EH)
Mobile edge computing (MEC)
Performance gain
Renewable energy sources
Resource management
Task analysis
Title Computation Rate Maximization for Multiuser Mobile Edge Computing Systems With Dynamic Energy Arrivals
URI https://ieeexplore.ieee.org/document/9580334
WOSCitedRecordID wos001353334200055&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/eLvHCXMwlV3NS8MwFA_b8OBJZRO_ycGj3ZqkTdKj1A0FN4YM3W2k7Yv24CpdJ_75vqZlInjxFkI-4OXj_d57-eURcp1kqKOE4h4EvvYC8DPP2DT0QhkwY60NpYuePz-q2Uwvl9G8Q252XBgAcI_PYFgXXSw_K9Jt7SobRaH2hQi6pKuUbLhaLemX-dHoIY7jkCul0OrjbNg2_pU1xSmNycH_pjskgx_2HZ3v9MoR6cC6T2yTfsHJkT4hQKRT85W_tyxKitCTOi5t7XSg0yLBw07H2SvQph8ORNvPyelLXr3RuyYTPR077h-9Lcsc99xmQBaT8SK-99ocCV7OfVF5UigLjAMHxZjRkAUpWkwII7TBs8jASOCBSjNjEkQCFq0DnSRcilSriCdaHJPeuljDCaFKG52BQAsHUZzFBgzvnzAAYbiRPLKnpF-LaPXR_IKxaqVz9nf1OdmvV6H2gnJ9QXpVuYVLspd-VvmmvHJL9w3rC5zh
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA9zCnpS2cRvc_BotzZJm_QodWPDbQwZuttI2xftwU26TvzzfU3LRPDiLYR8wMvH-7338ssj5DZOUUdxyRwQrnIEuKmjTeI7fiA8bYzxAxs9fx7JyUTN5-G0Qe62XBgAsI_PoFMWbSw_XSWb0lXWDX3lci52yK4vBHMrtlZN-_XcsDuMoshnUkq0-5jXqZv_ypti1Ub_8H8THpH2D_-OTrea5Zg0YNkipkrAYCVJnxAi0rH-yt5rHiVF8Ektm7Z0O9DxKsbjTnvpK9CqHw5E6-_J6UtWvNGHKhc97Vn2H73P8wx33bpNZv3eLBo4dZYEJ2MuL5yASwMeAwbS87SCVCRoMyGQUBpPowc6ACZkkmodIxYwaB-oOGYBT5QMWaz4CWkuV0s4JVQqrVLgaOMgjjPYwMMbyBfANdMBC80ZaZUiWnxU_2Asaumc_119Q_YHs_FoMRpOHi_IQbkipU-UqUvSLPINXJG95LPI1vm1XcZvQPegKA
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%2FCIC+International+Conference+on+Communications+in+China+%28ICCC%29&rft.atitle=Computation+Rate+Maximization+for+Multiuser+Mobile+Edge+Computing+Systems+With+Dynamic+Energy+Arrivals&rft.au=Lin%2C+Zhifei&rft.au=Wang%2C+Feng&rft.au=Liu%2C+Licheng&rft.date=2021-07-28&rft.pub=IEEE&rft.spage=312&rft.epage=317&rft_id=info:doi/10.1109%2FICCC52777.2021.9580334&rft.externalDocID=9580334