Distributed Service Function Chaining
A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF in...
Gespeichert in:
Veröffentlicht in: | IEEE journal on selected areas in communications 2017-11, Vol.35 (11), p.2479-2489 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2489 |
---|---|
container_issue | 11 |
container_start_page | 2479 |
container_title | IEEE journal on selected areas in communications |
container_volume | 35 |
creator | Ghaznavi, Milad Shahriar, Nashid Kamali, Shahin Ahmed, Reaz Boutaba, Raouf |
description | A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF instances, and routing traffic through them. In the current optimization-models of a chain deployment, the instances of the same function are assumed to be identical, while typical service providers offer VNFs with heterogeneous throughput and resource configurations. The VNF instances of the same function are installed in a single physical machine, which limits a chain to the throughput of a few instances that can be installed in one physical machine. Furthermore, the selection, placement, and routing problems are solved in isolation. We present distributed service function chaining that coordinates these operations, places VNF-instances of the same function distributedly, and selects appropriate instances from typical VNF offerings. Such a deployment uses network resources more efficiently and decouples a chain's throughput from that of physical machines. We formulate this deployment as a mixed integer programming (MIP) model, prove its NP-Hardness, and develop a local search heuristic called Kariz. Extensive experiments demonstrate that Kariz achieves a competitive acceptance-ratio of 76%-100% with an extra cost of less than 24% compared with the MIP model. |
doi_str_mv | 10.1109/JSAC.2017.2760178 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_8058439</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8058439</ieee_id><sourcerecordid>1974434910</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-a4f32eaf184fb5ef0a26bcbdf4259f23606fac0f823fc3841f4dda36d5ef72163</originalsourceid><addsrcrecordid>eNo9kE1LxDAURYMoWEd_gLgpiMuO7yVpmi6H6vjBgIvRdUjTRDNoOyat4L-3pYOruzn3XjiEXCIsEaG8fd6uqiUFLJa0EGPII5JgnssMAOQxSaBgLJMFilNyFuMOADmXNCE3dz72wddDb5t0a8OPNzZdD63pfdem1Yf2rW_fz8mJ05_RXhxyQd7W96_VY7Z5eXiqVpvM0JL1meaOUasdSu7q3DrQVNSmbhyneekoEyCcNuAkZc4wydHxptFMNCNbUBRsQa7n3X3ovgcbe7XrhtCOlwrLgnPGS4SRwpkyoYsxWKf2wX_p8KsQ1GRDTTbUZEMdbIydq7njrbX_vIRcclayP_i3WlE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1974434910</pqid></control><display><type>article</type><title>Distributed Service Function Chaining</title><source>IEEE Electronic Library (IEL)</source><creator>Ghaznavi, Milad ; Shahriar, Nashid ; Kamali, Shahin ; Ahmed, Reaz ; Boutaba, Raouf</creator><creatorcontrib>Ghaznavi, Milad ; Shahriar, Nashid ; Kamali, Shahin ; Ahmed, Reaz ; Boutaba, Raouf</creatorcontrib><description>A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF instances, and routing traffic through them. In the current optimization-models of a chain deployment, the instances of the same function are assumed to be identical, while typical service providers offer VNFs with heterogeneous throughput and resource configurations. The VNF instances of the same function are installed in a single physical machine, which limits a chain to the throughput of a few instances that can be installed in one physical machine. Furthermore, the selection, placement, and routing problems are solved in isolation. We present distributed service function chaining that coordinates these operations, places VNF-instances of the same function distributedly, and selects appropriate instances from typical VNF offerings. Such a deployment uses network resources more efficiently and decouples a chain's throughput from that of physical machines. We formulate this deployment as a mixed integer programming (MIP) model, prove its NP-Hardness, and develop a local search heuristic called Kariz. Extensive experiments demonstrate that Kariz achieves a competitive acceptance-ratio of 76%-100% with an extra cost of less than 24% compared with the MIP model.</description><identifier>ISSN: 0733-8716</identifier><identifier>EISSN: 1558-0008</identifier><identifier>DOI: 10.1109/JSAC.2017.2760178</identifier><identifier>CODEN: ISACEM</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Bandwidth ; Chaining ; Chains ; Firewalls ; Integer programming ; Linear programming ; Load modeling ; Mixed integer ; Network function virtualization ; Optimization ; placement ; routing ; Routing (machining) ; Service function chaining ; Throughput ; Traffic models ; virtual network function ; Virtualization</subject><ispartof>IEEE journal on selected areas in communications, 2017-11, Vol.35 (11), p.2479-2489</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-a4f32eaf184fb5ef0a26bcbdf4259f23606fac0f823fc3841f4dda36d5ef72163</citedby><cites>FETCH-LOGICAL-c293t-a4f32eaf184fb5ef0a26bcbdf4259f23606fac0f823fc3841f4dda36d5ef72163</cites><orcidid>0000-0003-1341-7203 ; 0000-0002-1101-6716</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8058439$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8058439$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ghaznavi, Milad</creatorcontrib><creatorcontrib>Shahriar, Nashid</creatorcontrib><creatorcontrib>Kamali, Shahin</creatorcontrib><creatorcontrib>Ahmed, Reaz</creatorcontrib><creatorcontrib>Boutaba, Raouf</creatorcontrib><title>Distributed Service Function Chaining</title><title>IEEE journal on selected areas in communications</title><addtitle>J-SAC</addtitle><description>A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF instances, and routing traffic through them. In the current optimization-models of a chain deployment, the instances of the same function are assumed to be identical, while typical service providers offer VNFs with heterogeneous throughput and resource configurations. The VNF instances of the same function are installed in a single physical machine, which limits a chain to the throughput of a few instances that can be installed in one physical machine. Furthermore, the selection, placement, and routing problems are solved in isolation. We present distributed service function chaining that coordinates these operations, places VNF-instances of the same function distributedly, and selects appropriate instances from typical VNF offerings. Such a deployment uses network resources more efficiently and decouples a chain's throughput from that of physical machines. We formulate this deployment as a mixed integer programming (MIP) model, prove its NP-Hardness, and develop a local search heuristic called Kariz. Extensive experiments demonstrate that Kariz achieves a competitive acceptance-ratio of 76%-100% with an extra cost of less than 24% compared with the MIP model.</description><subject>Bandwidth</subject><subject>Chaining</subject><subject>Chains</subject><subject>Firewalls</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>Load modeling</subject><subject>Mixed integer</subject><subject>Network function virtualization</subject><subject>Optimization</subject><subject>placement</subject><subject>routing</subject><subject>Routing (machining)</subject><subject>Service function chaining</subject><subject>Throughput</subject><subject>Traffic models</subject><subject>virtual network function</subject><subject>Virtualization</subject><issn>0733-8716</issn><issn>1558-0008</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LxDAURYMoWEd_gLgpiMuO7yVpmi6H6vjBgIvRdUjTRDNoOyat4L-3pYOruzn3XjiEXCIsEaG8fd6uqiUFLJa0EGPII5JgnssMAOQxSaBgLJMFilNyFuMOADmXNCE3dz72wddDb5t0a8OPNzZdD63pfdem1Yf2rW_fz8mJ05_RXhxyQd7W96_VY7Z5eXiqVpvM0JL1meaOUasdSu7q3DrQVNSmbhyneekoEyCcNuAkZc4wydHxptFMNCNbUBRsQa7n3X3ovgcbe7XrhtCOlwrLgnPGS4SRwpkyoYsxWKf2wX_p8KsQ1GRDTTbUZEMdbIydq7njrbX_vIRcclayP_i3WlE</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Ghaznavi, Milad</creator><creator>Shahriar, Nashid</creator><creator>Kamali, Shahin</creator><creator>Ahmed, Reaz</creator><creator>Boutaba, Raouf</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>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-1341-7203</orcidid><orcidid>https://orcid.org/0000-0002-1101-6716</orcidid></search><sort><creationdate>20171101</creationdate><title>Distributed Service Function Chaining</title><author>Ghaznavi, Milad ; Shahriar, Nashid ; Kamali, Shahin ; Ahmed, Reaz ; Boutaba, Raouf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-a4f32eaf184fb5ef0a26bcbdf4259f23606fac0f823fc3841f4dda36d5ef72163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Bandwidth</topic><topic>Chaining</topic><topic>Chains</topic><topic>Firewalls</topic><topic>Integer programming</topic><topic>Linear programming</topic><topic>Load modeling</topic><topic>Mixed integer</topic><topic>Network function virtualization</topic><topic>Optimization</topic><topic>placement</topic><topic>routing</topic><topic>Routing (machining)</topic><topic>Service function chaining</topic><topic>Throughput</topic><topic>Traffic models</topic><topic>virtual network function</topic><topic>Virtualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ghaznavi, Milad</creatorcontrib><creatorcontrib>Shahriar, Nashid</creatorcontrib><creatorcontrib>Kamali, Shahin</creatorcontrib><creatorcontrib>Ahmed, Reaz</creatorcontrib><creatorcontrib>Boutaba, Raouf</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>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE journal on selected areas in communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ghaznavi, Milad</au><au>Shahriar, Nashid</au><au>Kamali, Shahin</au><au>Ahmed, Reaz</au><au>Boutaba, Raouf</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distributed Service Function Chaining</atitle><jtitle>IEEE journal on selected areas in communications</jtitle><stitle>J-SAC</stitle><date>2017-11-01</date><risdate>2017</risdate><volume>35</volume><issue>11</issue><spage>2479</spage><epage>2489</epage><pages>2479-2489</pages><issn>0733-8716</issn><eissn>1558-0008</eissn><coden>ISACEM</coden><abstract>A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF instances, and routing traffic through them. In the current optimization-models of a chain deployment, the instances of the same function are assumed to be identical, while typical service providers offer VNFs with heterogeneous throughput and resource configurations. The VNF instances of the same function are installed in a single physical machine, which limits a chain to the throughput of a few instances that can be installed in one physical machine. Furthermore, the selection, placement, and routing problems are solved in isolation. We present distributed service function chaining that coordinates these operations, places VNF-instances of the same function distributedly, and selects appropriate instances from typical VNF offerings. Such a deployment uses network resources more efficiently and decouples a chain's throughput from that of physical machines. We formulate this deployment as a mixed integer programming (MIP) model, prove its NP-Hardness, and develop a local search heuristic called Kariz. Extensive experiments demonstrate that Kariz achieves a competitive acceptance-ratio of 76%-100% with an extra cost of less than 24% compared with the MIP model.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSAC.2017.2760178</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-1341-7203</orcidid><orcidid>https://orcid.org/0000-0002-1101-6716</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 0733-8716 |
ispartof | IEEE journal on selected areas in communications, 2017-11, Vol.35 (11), p.2479-2489 |
issn | 0733-8716 1558-0008 |
language | eng |
recordid | cdi_ieee_primary_8058439 |
source | IEEE Electronic Library (IEL) |
subjects | Bandwidth Chaining Chains Firewalls Integer programming Linear programming Load modeling Mixed integer Network function virtualization Optimization placement routing Routing (machining) Service function chaining Throughput Traffic models virtual network function Virtualization |
title | Distributed Service Function Chaining |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T13%3A13%3A27IST&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=Distributed%20Service%20Function%20Chaining&rft.jtitle=IEEE%20journal%20on%20selected%20areas%20in%20communications&rft.au=Ghaznavi,%20Milad&rft.date=2017-11-01&rft.volume=35&rft.issue=11&rft.spage=2479&rft.epage=2489&rft.pages=2479-2489&rft.issn=0733-8716&rft.eissn=1558-0008&rft.coden=ISACEM&rft_id=info:doi/10.1109/JSAC.2017.2760178&rft_dat=%3Cproquest_RIE%3E1974434910%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=1974434910&rft_id=info:pmid/&rft_ieee_id=8058439&rfr_iscdi=true |