国際会議 IEEE SERVICES/CLOUD 2020 参加報告 / A Report of IEEE SERVICES/CLOUD 2020

クラウドコンピューティングを中心とした国際会議IEEE CLOUD 2020に参加してきたので、その報告をまとめています。
https://conferences.computer.org/cloud/2020/program/

Transcript

1. ࠃࡍձٞ IEEE SERVICES/CLOUD 2020
   ࢀՃใࠂ
   ௶಺ ༎थ@͘͞ΒΠϯλʔωοτ
   2020/10/28
   

   View Slide

2. 2
   1. IEEE SERVICES/CLOUD 2020ͷ֓ཁ
   2. Best Paper Awardड৆࿦จͷ঺հ
   3. ௌߨͨ͠ݚڀൃදͷ঺հ
   4. ΦϯϥΠϯձ৔ͷ༷ࢠͱޮՌతͳௌߨͷͨΊͷ޻෉
   5. ૯ׅͱདྷ೥ͷ։࠵༧ࠂ
   ໨࣍
   

   View Slide

3. 1.
   IEEE SERVICES/CLOUD 2020ͷ֓ཁ
   

   View Slide

4. 4
   IEEE SERVICES 2020
   ɾ2020೥10݄18-24 ๺ژ → ΦϯϥΠϯ։࠵
   ɾݩདྷ͸7݄։࠵͕ͩͬͨCOVID-19ͷӨڹʹΑΓԆظ͞ΕͨͷͪʹΦϯ
   ϥΠϯ։࠵ͱͳͬͨ
   ɾIEEE Computer Society Technical Committee on Services Computing
   (TC-SVC) ओ࠵
   ɾαʔϏείϯϐϡʔςΟϯάʹؔ࿈͢Δෳ਺ͷࠃࡍձٞͷڞ࠵Πϕϯτ
   ɾ2004೥͔Β։࠵͞Ε͍ͯΔ
   

   View Slide

5. 5
   IEEE SERVICES 2020಺ͷ֤ࠃࡍձٞ
   ෼໺ ࠾୒཰ Core Rank
   IEEE
   CLOUD
   Ϋϥ΢υίϯϐϡʔςΟϯά
   IaaSɺPaaSͳͲ
   53/256 = 20.7% (regular)
   13 papers (short) B
   IEEE
   ICWS
   WebϕʔεͷαʔϏεͷϥΠϑαΠ
   Ϋϧݚڀͱ؅ཧ
   58/321 = 19% (regular)
   20 papers (short)
   A
   IEEE
   SCC
   αʔϏείϯϐϡʔςΟϯά 41/200 = 20.5% (regular)
   11 papers (workshop)
   14 papers (WIP)
   A
   IEEE
   SMDS
   σʔλۦಈܕΞϓϦέʔγϣϯ
   σʔλ෼ੳɺσʔλ඼࣭
   No data
   -
   IEEE
   EDGE
   ΤοδίϯϐϡʔςΟϯά 23/61 = 37.7% (regular)
   -
   CLOUD
   Λத৺ʹௌߨ
   

   View Slide

6. 6
   Keynotes
   (1) On Odor Reproduction, and How to Test For It by David Harel, a
   Vice President of the Israel Academy of Sciences and Humanities
   (2) Cloud Native Database Systems for Enterprise Applications by Feifei
   Li, a Vice President of Alibaba Group
   (3) On the Future of Smart Transportation with AI by Ozan Tonguz, a
   professor at Carnegie Mellon University
   (4) Digital Health and Beyond: What Computing Can Do to Transform
   Health by Wendy Nilsen, a Program Director in the Computer and
   Information Science and Engineering Directorate at NSF
   (5) IT Services after COVID-19 by Dr. Dong Xie, a CTO of IBM Greater
   China Group and Director of IBM China Research Lab
   (6) Participatory Systems in the Digital Era: A Services Computing
   Perspective by Valérie Issarny, Director of Research at INRIA.
   

   View Slide

7. 7
   ΦϯϥΠϯ։࠵
   ɾࢀՃొ࿥අ༻͸ɺIEEEձһͰ͋Ε͹ૣظొ࿥Ͱ $75ɻ
   ɾUnderlineͱ͍͏ΦϯϥΠϯձٞγεςϜΛར༻ɻ
   ɾ๺ژ࣌ؒͰ։࠵ɻͨͩ͠ɺனա͔͗Β༦ํ·Ͱٳܜ͕ೖΓɺਂ໷ଳʹ
   ΋ηογϣϯ༧ఆ͕૊·Ε͍ͯͨɻ
   ɾࣄલ഑෍FAQʹΑΔͱηογϣϯͷ࿥ըΛޙ೔ެ։༧ఆͷ͜ͱɻ
   

   View Slide

8. 8
   IEEE CLOUD 2020ͷ෼໺
   Cloud as a Service
   • IaaS, PaaS, and SaaS
   • Function as a Service
   • Network as a Service
   • Storage as a Service
   • Everything as a Service
   Cloud Infrastructure
   • Cloud Computing System & Architectures
   • Edge Computing System & Architectures
   • Cloud-centric Network Architectures
   • Storage & Data Architectures
   • Hybrid-clouds & Multi-clouds Integration
   Cloud Applications
   • Large Scale Cloud Applications
   • Terminal-Edge-Cloud Applications
   • 5G/6G Enhanced Edge/Cloud Applications
   • Social & Mobile Cloud Applications
   • Innovative Cloud Applications
   Cloud Management and Operations
   • Distributed & Parallel Query Processing
   • Resource, Energy & Data Management
   • Cloud Metering & Monitoring
   • Containers & Serverless Computing
   • SDN, NFV, & Data Center Network
   • Cloud Service Adaptation & Automation
   • Cloud Federation & Service Composition
   Cloud Trustworthiness
   • Access Control, Authorization, & Authentication
   • Assurance, Audit, Certification, Compliance
   • Fault Tolerance, High Availability, & Reliability
   • Cryptographic Algorithms and Protocols
   • Cloud Security and Privacy
   • Trusted Cloud Environments
   https://conferences.computer.org/cloud/2020/cfp/ ΑΓҾ༻
   ӡ༻؅ཧ
   ηΩϡϦςΟ
   ΞϓϦέʔγϣϯ
   ΠϯϑϥͷΞʔΩςΫνϟ
   αʔϏεͱͯ͠ͷΫϥ΢υ
   

   View Slide

9. 9
   IEEE CLOUD 2020ͷηογϣϯฤ੒
   ɾService Prediction & Optimization
   ɾEdge Applications x 2
   ɾEdge Caching & Computation
   Offloading
   ɾEdge-Cloud Collaboration
   ɾCloud & Edge Management
   ɾCloud Applications x 4
   ɾCloud Management x 2
   ɾCloud Management & Governance
   ɾSDN and NFV
   ɾNetwork and Storage Optimization
   ɾDeep Learning & Federated Learning
   ɾCloud Modeling x 2
   ɾCloud Performance & Maintenance
   ɾCloud Security
   ɾCloud Task Scheduling
   ɾCloud Performance Evaluation
   ɾServerless Computers and Containers
   ɾMicroservices & Containers
   ɾOrchestration & Data Analysis
   ΤοδίϯϐϡʔςΟϯάɺਂ૚ֶशɺαʔ
   όϨε&ίϯςφͳͲ͕ϗοτͳτϐοΫ
   

   View Slide

10. 10
    ɾ๺ژ։࠵ͳͷͰɺதࠃͷେֶʹॴଐ͢ΔํʑʹΑΔൃද͕໨ཱͬͨ
    ɾͦͷଞɺUSAɺϤʔϩούݍɺΠϯυɺΦʔετϥϦΞͳͲ
    ɾ೔ຊࠃ಺ͷ૊৫ʹॴଐ͢ΔஶऀʹΑΔൃද͸3݅
    ɾIBM Research - Tokyo x 1ɺ۝भ޻ۀେֶ x 2
    ɾ֤ࠃͷIBM ResearchॴଐʹΑΔൃද͕໨ཱͬͨ
    ɾΫϥ΢υࣄۀऀॴଐͷൃද͸3݅ͱগͳΊ (Alibaba Cloud,IBM Cloud)
    ൃද͞ΕΔݚڀͷஶऀͷॴଐ
    

    View Slide

11. 11
    ɾର৅γεςϜ: Ϋϥ΢υ্ͷϚΠΫϩαʔϏεɺ൓Ԡతʹεέʔϧ͢
    ΔαʔόϨείϯϐϡʔςΟϯάɺଟ਺ͷΤοδͱΫϥ΢υͷ࿈ܞͱ
    ͍ͬͨಈత͔ͭ෼ࢄͨ͠ෳࡶͳγεςϜߏ੒
    ɾ໰୊ҙࣝ: γεςϜ؅ཧऀʹΑΔϧʔϧϕʔεͷઃܭͷݶք
    ɾΞϓϩʔν: ଴ͪߦྻཧ࿦΍਺ཧ࠷దԽ໰୊ͳͲͷݹయతͳ਺ཧϞσ
    ϧͷద༻ʹՃ͑ͯɺػցֶशͱਂ૚ֶशΛద༻͢Δ
    ɾ৽ͨʹML/DLΛద༻͢Δͱ͍͏ΑΓɺ͢ͰʹͦΕΒΛద༻ͨ͠ઌߦ
    ݚڀͷ՝୊Λղ͘ͱ͍͏ஈ֊ʹೖ͍ͬͯΔ
    ɾ൒਺Ҏ্͕͜ͷखͷൃදͩͬͨΑ͏ʹײͨ͡ʢஶऀ؍ଌʣ
    Ұ෦ͷݚڀൃදʹڞ௨͢Δ໰୊ઃఆ΍ݚڀख๏
    

    View Slide

12. 2.
    Best Paper Awardड৆࿦จͷ঺հ
    

    View Slide

13. 13
    IEEE CLOUD 2020 Best Paper Award
    Skedulix: Hybrid Cloud Scheduling for Cost-Efficient
    Execution of Serverless Applications
    Anirban Das (Rensselaer Polytechnic Institute), Andrew Leaf (Rensselaer Polytechnic
    Institute), Carlos A. Varela (Rensselaer Polytechnic Institute), Stacy Patterson (Rensselaer
    Polytechnic Institute)
    

    View Slide

14. 14
    ɾैདྷͷΞϓϦέʔγϣϯ͸ɺωοτϫʔΫI/OΛ଴ͪड͚Δৗறϓϩ
    ηεͰ͋ΔʮωοτϫʔΫαʔόʯʢWebαʔόͳͲʣͷܗଶΛͱΔ
    ɾαʔόͰ͸ͳ͘ɺೖྗΛड৴ͨ͠ͱ͖͚ͩɺॲཧ಺༰Λ಺แ͢Δ
    Functionʢؔ਺ʣ͕ίϯςφϓϩηεͱͯ͠ىಈͯ͠ɺδϣϒΛ࣮ߦ
    ͢ΔΞϓϦέʔγϣϯϞσϧɻ
    ɾΫϥ΢υࣄۀऀ͕Functionͱ͍͏ܗଶ·ͰΞϓϦέʔγϣϯ࣮ߦج൫
    Λந৅Խ͍ͯ͠Δͱ΋ݴ͑Δɻ
    αʔόʔϨείϯϐϡʔςΟϯάʢFunction asSʣ
    

    View Slide

15. 15
    ɾϓϥΠϕʔτΫϥ΢υͰ΋OSSʹΑΓFaaSج൫ΛߏஙՄೳ
    ɾ͔͠͠ɺϓϥΠϕʔτΫϥ΢υ͸Ϧιʔε͕ݶΒΕ͍ͯΔͨΊɺϋΠ
    ϒϦουΫϥ΢υΛ࠾༻͢Δ͜ͱ͕͋Δɻ
    ϓϥΠϕʔτΫϥ΢υͰ΋εέʔϧ͍ͤͨ͞
    Private Cloud Public Cloud
    Incoming jobs Additional jobs
    Function
    ɾϓϥΠϕʔτΫϥ΢υͷ
    ϓϥΠόγʔɺੑೳɺίε
    τ໘Ͱͷར఺ΛڗडՄೳ
    ɾϐʔΫ࣌ͷෛՙ૿େʹඋ
    ͑ͨϋʔυ΢ΣΞͷҡ͕࣋
    ෆཁ
    ௿ίετ ߴεέʔϥϏϦςΟ
    

    View Slide

16. 16
    ఏҊख๏ Skedulix ͷ֓ཁ
    ɾ໨త͸ϋΠϒϦουϓϥοτϑΥʔϜ্Ͱػೳ࣮ߦΛεέδϡʔϦϯ
    ά͠ɺύϒϦοΫΫϥ΢υͷར༻ίετΛ࠷খݶʹ཈͑ͭͭɺϢʔβ
    ͕ࢦఆ࣮ͨ͠ߦ࣌ؒͷظݶΛຬͨ͢͜ͱ
    ɾ͜ͷεέδϡʔϦϯάͱׂΓ౰ͯ໰୊ͷܗࣜԽ͸ɺ ࠞ߹੔਺ઢܗ໰
    ୊ͱ࣮ͯ͠ݱ͞ΕɺNPࠔ೉Ͱ͋Δ͜ͱ͕ূ໌͞Ε͍ͯΔʢ෇࿥ʣ
    ɾSkedulix͸ɺؔ਺࣮ߦ࣌ؒͱωοτϫʔΫ஗Ԇͷ༧ଌϞσϧΛ༻͍
    ͯɺίετ࠷খԽͷͨΊʹ֤ػೳͷॱংͱ഑ஔΛಈతʹܾఆ͢Δᩦཉ
    ͳΞϓϩʔνΛ࠾༻͢Δ
    ɾϓϥΠϕʔτΫϥ΢υͷΈͱൺֱ͠ɺ40.5%ͷίετ௿ݮͱ࠷େ
    1.92ഒͷߴ଎ԽΛୡ੒ͨ͠
    

    View Slide

17. 17
    ΞϓϦέʔγϣϯΛDAGͱͯ͠ϞσϧԽ
    ɾෳ਺ͷFunctionͷ࿈ͳΓʹΑΓΞϓϦέʔγϣϯ͕ߏ੒͞ΕΔ
    ɾDAGͷ֤ϊʔυ͸Function࣮ߦΛࣔ͢εςʔδ
    ɾϓϥΠϕʔτΫϥ΢υͰ͸֤εςʔδͷϨϓϦΧ਺͸ݻఆ
    ɾύϒϦοΫΫϥ΢υ͸ແ੍ݶͷ༰ྔͰ͋Γɺੑೳ௿Լ͸͠ͳ͍ͱ͍͏
    ԾఆΛஔ͘
    

    View Slide

18. εέδϡʔϥ
    0. ճؼϞσϧʹΑΓ
    δϣϒͷ࣮ߦ࣌ؒΛ༧
    ଌ͢ΔϞσϧΛߏங
    1. όονδϣϒͷ
    ΩϡʔΠϯά
    2. εέδϡʔϦϯάΞ
    ϧΰϦζϜͷ࣮ߦ
    δϣϒͷ֤εςʔδ͝
    ͱʹධՁ
    18
    εέδϡʔϥͷ֓ཁ
    

    View Slide

19. 19
    ॴײ
    ɾαʔόʔϨεͷϋΠϒϦουΫϥ΢υʹ͓͚ΔεέδϡʔϦϯά໰୊
    ͱ͍͏৽͍͠໰୊ઃఆͰ͋Δ͜ͱ
    ɾ໰୊Λࠞ߹ઢܗܭը໰୊ʹམͱ͠ࠐΊͯɺͳ͓͔ͭNPࠔ೉Ͱ͋Δ͜
    ͱΛཧ࿦తʹ͍ࣔͯ͠Δ͜ͱ
    ɾαʔόϨεͱ͍͏ந৅ԽʹΑΓ໰୊ΛఆࣜԽ͠΍͘͢ͳ͍ͬͯΔ͜ͱ
    ɾFunctionδϣϒΛ࣮ߦͯ͠༧Ί܇࿅͢Δͱ͍ͬͨख͕ؒ͋Δ
    ɾAWS͔ΒͷΞ΢τό΢ϯυτϥϑΟοΫίετ͕ߟྀ͞Ε͍ͯͳ͍ʁ
    ྑ͍෦෼
    ݒ೦఺
    

    View Slide

20. 3.
    ௌߨͨ͠ݚڀൃදͷ঺հ
    

    View Slide

21. 21
    Deep Unsupervised Workload Sequence Anomaly Detection
    with Fusion of Spatial and Temporal Features in the Cloud
    Mengqing Wang, Zhihua Zhang, and others, IEEE CLOUD 2020.
    ࣗ෼ͷݚڀʹؔ࿈͢Δൃද
    Root-Cause Metric Location for Microservice Systems
    via Log Anomaly Detection
    Lingzhi Wang, Nengwen Zhao, and others, IEEE ICWS 2020.
    RAD: Detecting Performance Anomalies
    in Cloud-Based Web Services
    Joydeep Mukherjee, Alexandru Baluta, and others, IEEE CLOUD 2020.
    ҟৗݕ஌
    ҟৗݕ஌
    ҟৗݕ஌ͱ
    ݪҼಛఆ
    

    View Slide

22. 22
    ɾखಈͰᮢ஋Λઃఆ͸ෛՙγʔέϯεͷछྨ͕ଟ
    ͍ͱ೉͍ͨ͠ΊɺҟৗΛڭࢣͳ͠Ͱࣗಈݕग़
    ɾෳ਺ͷෛՙγʔέϯεͷมԽύλʔϯʹదͨ͠ڭ
    ࢣͳ͠ͷҟৗγʔέϯεݕग़ϞσϧΛͲͷΑ͏ʹ
    ߏங͢Δ͔͕՝୊
    ɾσΟʔϓχϡʔϥϧωοτϫʔΫΛ༻͍ͯɺγʔ
    έϯεͷຊ࣭తͳಛ௃Λัଊ͠ɺҟৗγʔέϯε
    ͷແؔ܎ͳಛ௃Λ෼཭͢Δ
    ɾۭؒతಛ௃->CNNɺ࣌ؒతಛ௃->BiLSTM
    Deep Unsupervised Workload Sequence Anomaly Detection with
    Fusion of Spatial and Temporal Features in the Cloud
    

    View Slide

23. 23
    ɾෳࡶԽͨ͠γεςϜͷҟৗͱͦ
    ͷݪҼΛࣗಈతʹݕग़͍ͨ͠
    ɾ֎෦γεςϜͱͷڝ߹ͳͲɺγ
    εςϜԼҐ૚ͷϝτϦοΫ͚ͩͰ
    ͸ҟৗͷݕग़͕ࠔ೉
    ɾ্Ґ૚ͷܭଌ͸खؒ΍Φʔό
    ϔου͕͔͔Δ
    RAD: Detecting Performance Anomalies in Cloud-Based Web Services
    ɾVM͔ΒURLͱγεςϜϝτϦοΫΛܧଓతʹ؂ࢹ͠ɺΩϡʔΠϯά
    ωοτϫʔΫϞσϧΛߏங͢Δ
    ɾϞσϧͰ༧ଌͨ͠Ԡ౴࣌ؒΛɺҟৗ͕ͳ͍৔߹ͷϞσϧͰ༧ଌ͞Εͨ
    ϕʔεϥΠϯͱͳΔԠ౴࣌ؒͱൺֱͯ͠ҟৗݕ஌Λߦ͏
    

    View Slide

24. 24
    ɾϚΠΫϩαʔϏεͰ
    ͸ɺαʔϏεؒͷো֐
    ఻ൖʹΑΓɺͲͷαʔ
    Ϗε͕ݪҼ͔ಛఆ͢Δ
    ͜ͱ͸ࠔ೉
    ɾؔ࿈ݚڀ͸͢΂ͯϝτ
    ϦοΫؒͷ૬ؔؔ܎΍
    ϝτϦοΫͱނোͷ૬
    ؔؔ܎ΛΈ͍ͯΔ͕ɺ
    ϩά΋ॏཁ
    Root-Cause Metric Location for Microservice Systems via Log Anomaly
    Detection
    ɾDeeplog[8]ʹΑΓࢉग़ͨ͠ϩάͷҟৗείΞͱ
    ϝτϦοΫΛ੔߹ͤͯ͞ɺ૬ޓ৘ใྔʹج͍ͮͨ
    ૬ؔ෼ੳΛߦ͏
    ɾ਺ඦͷࢦඪͷத͔Βฏۉ্ͯ͠Ґ15Ґ·Ͱʹࠜ
    ຊݪҼΛಛఆͰ͖ͨ
    

    View Slide

25. 4.
    ΦϯϥΠϯձ৔ͷ༷ࢠͱ
    ޮՌతͳௌߨͷͨΊͷ޻෉
    

    View Slide

26. 26
    ΦϯϥΠϯձ৔ͷ༷ࢠ
    ɾௌऺͷਓ਺͸ɺKeynoteͰ΋20ਓલޙɻฏۉ10ਓऑɺਓؾ͕ͳ͚Ε
    ͹1,2ਓͳͲɻඇৗʹগͳ͍ਓ਺Ͱ͋Δͱײͨ͡ɻʢஶऀ؍ଌʣ
    ɾ࠲௕͕ෆࡏͷηογϣϯ͕͋ͬͨɻ࠲௕ͱൃදऀͷ3ਓ͏ͪ2ਓ͕͍
    ͳ͍͜ͱ΋͋ͬͨɻ
    ɾUnderlineͷ഑৴ػೳͷ࢖͍উखʹ೉͋ΓɻԻ੠ͱΧϝϥͷڞ༗ͷ
    On/Offঢ়ଶΛ೺ѲͰ͖ͣɺมߋ͢Δʹ͸Ұ୴ୀग़͢Δඞཁ͕͋ͬͨɻ
    ɾ࠲௕Ҏ֎ͷௌऺʹΑΔ࣭໰͸ɺUnderlineͷQ&Aཝʹॻ͖ࠐ·ΕΔ͜
    ͱ͕ଟ͔ͬͨɻ
    ɾ࿥ը഑৴࣌ʹ͏·͘Ի੠ͱը໘Λ഑৴Ͱ͖ͳ͍ɺԻׂ͕Ε͍ͯΔɺԻ
    ͕খ͍͞ɺԻ·ͨ͸εϥΠυ഑৴్͕தͰ్੾ΕΔͳͲͷτϥϒϧ
    

    View Slide

27. 27
    ௌߨͷͨΊͷ޻෉: ༧ߘͷϦʔσΟϯά
    ɾௌߨ༧ఆηογϣϯͷཁ໿ͱΠϯτϩμΫγϣϯͷষͷจষΛɺ຋
    ༁αʔϏεDeepLʹ͔͚Δ
    ɾ຋༁݁ՌΛϊʔτΞϓϦʢNotionʣʹه࿥͢Δ
    ɾಉ࣌ʹௌߨ͍ͯͨ͠ಉ྅ʹڞ༗͢Δ
    Πϯϓοτྔ͕ଟ͍ͷͰɺ೴ͷෛ
    ୲͕ߴ͍ͨΊɺ೔ຊޠͰ༧शͨ͠
    ݁Ռతʹ͔ͬ͠Γ༧शΛͯ͠ൃද
    Λௌ͚ͨ
    

    View Slide

28. 28
    ௌߨͷͨΊͷ޻෉: ൃදͷϦεχϯά
    ɾԻ੠ॻ͖ى͜͠αʔϏεOtterʹΑΓϦΞϧλΠϜʹॻ͖ى͜͠
    ɾखݩ୺຤ͷԻ੠ग़ྗΛೖྗͱͯ͠ϧʔϓόοΫͤ͞Δඞཁ͕͋Δ
    ɾmacOSͷ৔߹ͷઃఆํ๏͸
    https://www.notion.so/yuuk1/Listening-Talks-a95698a888634120a3e285c3085ab4f2
    

    View Slide

29. 5.
    ૯ׅͱདྷ೥ͷ։࠵༧ࠂ
    

    View Slide

30. 30
    ૯ׅ
    ɾIEEE CLOUD 2020Λத৺ʹɺ֓ཁɺड৆࿦จɺௌߨͨ͠ݚڀൃදɺ
    ͓ΑͼɺΦϯϥΠϯௌߨͷ՝୊ͱ޻෉Λ঺հͨ͠ɻ
    ɾΫϥ΢υίϯϐϡʔςΟϯάʹ·ͭΘΔ՝୊ΛػցֶशΛ͸͡Ίͱ͠
    ͨ਺ཧతΞϓϩʔνͰղ͘ݚڀ͕ଟ਺ൃද͞Εͨ͜ͱ͔ΒɺݱࡏऔΓ
    ૊ΜͰ͍Δݚڀͷൃදͷ৔ͱͯ͠ద੾Ͱ͋Δͱײͨ͡ɻ
    ɾ͜ͷΑ͏ͳݚڀ͕ଟ਺ൃද͞Ε͍ͯΔʹ΋ؔΘΒͣɺະͩݱ৔Ͱ͸
    ϧʔϧϕʔεͷӡ༻͕ͳ͞Ε͍ͯΔ͜ͱ͔Βɺ࣮؀ڥ΁ͷద༻Մೳੑ
    ʹॏࢹͯ͠ݚڀ͍ͯ͘͠ɻ
    

    View Slide

31. 31
    Early paper submission: March 1, 2021
    Notification to early papers: April 15, 2021
    Normal paper submission due: May 5, 2021
    Final notification to authors: June 17, 2021
    Camera-ready paper due: July 1, 2021
    དྷ೥ͷ։࠵༧ࠂ: IEEE SERVICES 2021
    CHICAGO, ILLINOIS, USA September 5-10
    ։࠵༧ఆͷࠃࡍձٞ͸ɺCLOUD/ICWS/SCC/SMDS ͷ4ͭ
    https://youtu.be/hwkGNGn4mt8 ΑΓҾ༻
    

    View Slide