A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications
Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tra...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on industrial informatics 2018-10, Vol.14 (10), p.4529-4537 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 4537 |
|---|---|
| container_issue | 10 |
| container_start_page | 4529 |
| container_title | IEEE transactions on industrial informatics |
| container_volume | 14 |
| creator | Tseng, Fan-Hsun Tsai, Ming-Shiun Tseng, Chia-Wei Yang, Yao-Tsung Liu, Chien-Chang Chou, Li-Der |
| description | Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tradeoff between service scalability and operating expenses. This paper integrates the hypervisor technique with container virtualization, and constructs an integrated virtualization (IV) fog platform for deploying industrial applications based on the virtual network function. This paper presents a fuzzy-based real-time autoscaling (FRAS) mechanism and implements it in the IV fog platform. The FRAS mechanism provides a dynamic, rapid, lightweight, and low-cost solution to the service autoscaling problem. Experimental results showed that the proposed FRAS mechanism yields a better service scale with lower average delay, error rate, and operating expenses compared to other autoscaling schemes. |
| doi_str_mv | 10.1109/TII.2018.2799230 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TII_2018_2799230</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8272512</ieee_id><sourcerecordid>2117187976</sourcerecordid><originalsourceid>FETCH-LOGICAL-c357t-1eb8244a748376747b08c06c9e68919f38338456353066717f6b2731a27de36e3</originalsourceid><addsrcrecordid>eNo9kE1Lw0AQhhdRsFbvgpcFz6kzu8l-HEPxI1DRQz0v23TTbkmzMZsg_nsTWrzMDMzzzsBDyD3CAhH007ooFgxQLZjUmnG4IDPUKSYAGVyOc5Zhwhnwa3IT4wGAS-B6Rj5zuvK7ff_jpkrzoQ-xtLVvdvTdlXvb-HikVejoS9jRZTi2Qz_tfEOLZjvEvvO2pnnb1r60vQ9NvCVXla2juzv3Ofl6eV4v35LVx2uxzFdJyTPZJ-g2iqWplaniUshUbkCVIErthNKoK644V2kmeMZBCImyEhsmOVomt44Lx-fk8XS37cL34GJvDmHomvGlYYgSldRSjBScqLILMXauMm3nj7b7NQhm8mZGb2byZs7exsjDKeKdc_-4YpJlyPgfJeBnFw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2117187976</pqid></control><display><type>article</type><title>A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications</title><source>IEEE Electronic Library (IEL)</source><creator>Tseng, Fan-Hsun ; Tsai, Ming-Shiun ; Tseng, Chia-Wei ; Yang, Yao-Tsung ; Liu, Chien-Chang ; Chou, Li-Der</creator><creatorcontrib>Tseng, Fan-Hsun ; Tsai, Ming-Shiun ; Tseng, Chia-Wei ; Yang, Yao-Tsung ; Liu, Chien-Chang ; Chou, Li-Der</creatorcontrib><description>Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tradeoff between service scalability and operating expenses. This paper integrates the hypervisor technique with container virtualization, and constructs an integrated virtualization (IV) fog platform for deploying industrial applications based on the virtual network function. This paper presents a fuzzy-based real-time autoscaling (FRAS) mechanism and implements it in the IV fog platform. The FRAS mechanism provides a dynamic, rapid, lightweight, and low-cost solution to the service autoscaling problem. Experimental results showed that the proposed FRAS mechanism yields a better service scale with lower average delay, error rate, and operating expenses compared to other autoscaling schemes.</description><identifier>ISSN: 1551-3203</identifier><identifier>EISSN: 1941-0050</identifier><identifier>DOI: 10.1109/TII.2018.2799230</identifier><identifier>CODEN: ITIICH</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Autoscaling ; Cloud computing ; Computer architecture ; container virtualization ; Containers ; Costs ; fog computing ; fuzzy theory ; Industrial applications ; Libraries ; Lightweight ; Scalability ; Virtual machine monitors ; virtual network function (VNF) ; Virtualization ; Weight reduction</subject><ispartof>IEEE transactions on industrial informatics, 2018-10, Vol.14 (10), p.4529-4537</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c357t-1eb8244a748376747b08c06c9e68919f38338456353066717f6b2731a27de36e3</citedby><cites>FETCH-LOGICAL-c357t-1eb8244a748376747b08c06c9e68919f38338456353066717f6b2731a27de36e3</cites><orcidid>0000-0003-2461-8377</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8272512$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27915,27916,54749</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8272512$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Tseng, Fan-Hsun</creatorcontrib><creatorcontrib>Tsai, Ming-Shiun</creatorcontrib><creatorcontrib>Tseng, Chia-Wei</creatorcontrib><creatorcontrib>Yang, Yao-Tsung</creatorcontrib><creatorcontrib>Liu, Chien-Chang</creatorcontrib><creatorcontrib>Chou, Li-Der</creatorcontrib><title>A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications</title><title>IEEE transactions on industrial informatics</title><addtitle>TII</addtitle><description>Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tradeoff between service scalability and operating expenses. This paper integrates the hypervisor technique with container virtualization, and constructs an integrated virtualization (IV) fog platform for deploying industrial applications based on the virtual network function. This paper presents a fuzzy-based real-time autoscaling (FRAS) mechanism and implements it in the IV fog platform. The FRAS mechanism provides a dynamic, rapid, lightweight, and low-cost solution to the service autoscaling problem. Experimental results showed that the proposed FRAS mechanism yields a better service scale with lower average delay, error rate, and operating expenses compared to other autoscaling schemes.</description><subject>Autoscaling</subject><subject>Cloud computing</subject><subject>Computer architecture</subject><subject>container virtualization</subject><subject>Containers</subject><subject>Costs</subject><subject>fog computing</subject><subject>fuzzy theory</subject><subject>Industrial applications</subject><subject>Libraries</subject><subject>Lightweight</subject><subject>Scalability</subject><subject>Virtual machine monitors</subject><subject>virtual network function (VNF)</subject><subject>Virtualization</subject><subject>Weight reduction</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1Lw0AQhhdRsFbvgpcFz6kzu8l-HEPxI1DRQz0v23TTbkmzMZsg_nsTWrzMDMzzzsBDyD3CAhH007ooFgxQLZjUmnG4IDPUKSYAGVyOc5Zhwhnwa3IT4wGAS-B6Rj5zuvK7ff_jpkrzoQ-xtLVvdvTdlXvb-HikVejoS9jRZTi2Qz_tfEOLZjvEvvO2pnnb1r60vQ9NvCVXla2juzv3Ofl6eV4v35LVx2uxzFdJyTPZJ-g2iqWplaniUshUbkCVIErthNKoK644V2kmeMZBCImyEhsmOVomt44Lx-fk8XS37cL34GJvDmHomvGlYYgSldRSjBScqLILMXauMm3nj7b7NQhm8mZGb2byZs7exsjDKeKdc_-4YpJlyPgfJeBnFw</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Tseng, Fan-Hsun</creator><creator>Tsai, Ming-Shiun</creator><creator>Tseng, Chia-Wei</creator><creator>Yang, Yao-Tsung</creator><creator>Liu, Chien-Chang</creator><creator>Chou, Li-Der</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-2461-8377</orcidid></search><sort><creationdate>20181001</creationdate><title>A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications</title><author>Tseng, Fan-Hsun ; Tsai, Ming-Shiun ; Tseng, Chia-Wei ; Yang, Yao-Tsung ; Liu, Chien-Chang ; Chou, Li-Der</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c357t-1eb8244a748376747b08c06c9e68919f38338456353066717f6b2731a27de36e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Autoscaling</topic><topic>Cloud computing</topic><topic>Computer architecture</topic><topic>container virtualization</topic><topic>Containers</topic><topic>Costs</topic><topic>fog computing</topic><topic>fuzzy theory</topic><topic>Industrial applications</topic><topic>Libraries</topic><topic>Lightweight</topic><topic>Scalability</topic><topic>Virtual machine monitors</topic><topic>virtual network function (VNF)</topic><topic>Virtualization</topic><topic>Weight reduction</topic><toplevel>online_resources</toplevel><creatorcontrib>Tseng, Fan-Hsun</creatorcontrib><creatorcontrib>Tsai, Ming-Shiun</creatorcontrib><creatorcontrib>Tseng, Chia-Wei</creatorcontrib><creatorcontrib>Yang, Yao-Tsung</creatorcontrib><creatorcontrib>Liu, Chien-Chang</creatorcontrib><creatorcontrib>Chou, Li-Der</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on industrial informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tseng, Fan-Hsun</au><au>Tsai, Ming-Shiun</au><au>Tseng, Chia-Wei</au><au>Yang, Yao-Tsung</au><au>Liu, Chien-Chang</au><au>Chou, Li-Der</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications</atitle><jtitle>IEEE transactions on industrial informatics</jtitle><stitle>TII</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>14</volume><issue>10</issue><spage>4529</spage><epage>4537</epage><pages>4529-4537</pages><issn>1551-3203</issn><eissn>1941-0050</eissn><coden>ITIICH</coden><abstract>Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tradeoff between service scalability and operating expenses. This paper integrates the hypervisor technique with container virtualization, and constructs an integrated virtualization (IV) fog platform for deploying industrial applications based on the virtual network function. This paper presents a fuzzy-based real-time autoscaling (FRAS) mechanism and implements it in the IV fog platform. The FRAS mechanism provides a dynamic, rapid, lightweight, and low-cost solution to the service autoscaling problem. Experimental results showed that the proposed FRAS mechanism yields a better service scale with lower average delay, error rate, and operating expenses compared to other autoscaling schemes.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TII.2018.2799230</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-2461-8377</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1551-3203 |
| ispartof | IEEE transactions on industrial informatics, 2018-10, Vol.14 (10), p.4529-4537 |
| issn | 1551-3203 1941-0050 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TII_2018_2799230 |
| source | IEEE Electronic Library (IEL) |
| subjects | Autoscaling Cloud computing Computer architecture container virtualization Containers Costs fog computing fuzzy theory Industrial applications Libraries Lightweight Scalability Virtual machine monitors virtual network function (VNF) Virtualization Weight reduction |
| title | A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T06%3A46%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Lightweight%20Autoscaling%20Mechanism%20for%20Fog%20Computing%20in%20Industrial%20Applications&rft.jtitle=IEEE%20transactions%20on%20industrial%20informatics&rft.au=Tseng,%20Fan-Hsun&rft.date=2018-10-01&rft.volume=14&rft.issue=10&rft.spage=4529&rft.epage=4537&rft.pages=4529-4537&rft.issn=1551-3203&rft.eissn=1941-0050&rft.coden=ITIICH&rft_id=info:doi/10.1109/TII.2018.2799230&rft_dat=%3Cproquest_RIE%3E2117187976%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2117187976&rft_id=info:pmid/&rft_ieee_id=8272512&rfr_iscdi=true |