An Index Coding Approach to Caching With Uncoded Cache Placement
Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user's local cache memory, even without knowledge of user's later demands. Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strate...
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description | Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user's local cache memory, even without knowledge of user's later demands. Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users' demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the "acyclic index coding converse bound." This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al has however shown that coded cache placement can at most half the network load compared to the results presented in this paper. |
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Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users' demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the "acyclic index coding converse bound." This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al has however shown that coded cache placement can at most half the network load compared to the results presented in this paper.</description><identifier>ISSN: 0018-9448</identifier><identifier>EISSN: 1557-9654</identifier><identifier>DOI: 10.1109/TIT.2020.2967753</identifier><identifier>CODEN: IETTAW</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Cache memory ; Caching ; Coded caching ; Coding ; Constraint modelling ; distributed source coding ; Encoding ; Engineering Sciences ; index coding ; Indexes ; Integrated circuit modeling ; Load modeling ; Peak hour traffic ; Placement ; Traffic congestion ; uncoded cache placement</subject><ispartof>IEEE transactions on information theory, 2020-03, Vol.66 (3), p.1318-1332</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users' demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the "acyclic index coding converse bound." This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al has however shown that coded cache placement can at most half the network load compared to the results presented in this paper.</description><subject>Cache memory</subject><subject>Caching</subject><subject>Coded caching</subject><subject>Coding</subject><subject>Constraint modelling</subject><subject>distributed source coding</subject><subject>Encoding</subject><subject>Engineering Sciences</subject><subject>index coding</subject><subject>Indexes</subject><subject>Integrated circuit modeling</subject><subject>Load modeling</subject><subject>Peak hour traffic</subject><subject>Placement</subject><subject>Traffic congestion</subject><subject>uncoded cache placement</subject><issn>0018-9448</issn><issn>1557-9654</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1Lw0AQxRdRsFbvgpcFTx5S9zu7N0NQWyjoocXjss3O2pQ2qUkq-t-7MaWnYR6_95h5CN1SMqGUmMfFbDFhhJEJMypNJT9DIyplmhglxTkaEUJ1YoTQl-iqbTdxFZKyEXrKKjyrPPzgvPZl9Ymz_b6pXbHGXY3zOHvto-zWeFkVtQf_LwJ-37oCdlB11-giuG0LN8c5RsuX50U-TeZvr7M8mycFV2mXUF9olzpQKQ9SwUoJKQInKxecD14qbbgr-IoHLwyAJJxTD4YKQ5QGzxQfo4chd-22dt-UO9f82tqVdprNba8RZiRV0nzTyN4PbHzl6wBtZzf1oanieZZxqQ2NuT1FBqpo6rZtIJxiKbF9pzZ2avtO7bHTaLkbLCUAnHBtFFfM8D8zyG_-</recordid><startdate>20200301</startdate><enddate>20200301</enddate><creator>Wan, Kai</creator><creator>Tuninetti, Daniela</creator><creator>Piantanida, Pablo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><general>Institute of Electrical and Electronics Engineers</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><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0003-1880-4798</orcidid><orcidid>https://orcid.org/0000-0003-4671-3287</orcidid><orcidid>https://orcid.org/0000-0002-8717-2117</orcidid></search><sort><creationdate>20200301</creationdate><title>An Index Coding Approach to Caching With Uncoded Cache Placement</title><author>Wan, Kai ; Tuninetti, Daniela ; Piantanida, Pablo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-1dc8a7ae673f56eb6454f30bafadfd56893ac3b3fd49ee50331de9149068ed263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Cache memory</topic><topic>Caching</topic><topic>Coded caching</topic><topic>Coding</topic><topic>Constraint modelling</topic><topic>distributed source coding</topic><topic>Encoding</topic><topic>Engineering Sciences</topic><topic>index coding</topic><topic>Indexes</topic><topic>Integrated circuit modeling</topic><topic>Load modeling</topic><topic>Peak hour traffic</topic><topic>Placement</topic><topic>Traffic congestion</topic><topic>uncoded cache placement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wan, Kai</creatorcontrib><creatorcontrib>Tuninetti, Daniela</creatorcontrib><creatorcontrib>Piantanida, Pablo</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><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>IEEE transactions on information theory</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wan, Kai</au><au>Tuninetti, Daniela</au><au>Piantanida, Pablo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Index Coding Approach to Caching With Uncoded Cache Placement</atitle><jtitle>IEEE transactions on information theory</jtitle><stitle>TIT</stitle><date>2020-03-01</date><risdate>2020</risdate><volume>66</volume><issue>3</issue><spage>1318</spage><epage>1332</epage><pages>1318-1332</pages><issn>0018-9448</issn><eissn>1557-9654</eissn><coden>IETTAW</coden><abstract>Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user's local cache memory, even without knowledge of user's later demands. 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This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. 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subjects | Cache memory Caching Coded caching Coding Constraint modelling distributed source coding Encoding Engineering Sciences index coding Indexes Integrated circuit modeling Load modeling Peak hour traffic Placement Traffic congestion uncoded cache placement |
title | An Index Coding Approach to Caching With Uncoded Cache Placement |
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