Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks
Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS...
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Veröffentlicht in: | IEEE transactions on wireless communications 2017-02, Vol.16 (2), p.717-729 |
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description | Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS to total number of user requests. With finite battery capacity, Markov decision process-based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based policy and the energy-efficient threshold-based policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high. |
doi_str_mv | 10.1109/TWC.2016.2628789 |
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A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS to total number of user requests. With finite battery capacity, Markov decision process-based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based policy and the energy-efficient threshold-based policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high.</description><identifier>ISSN: 1536-1276</identifier><identifier>EISSN: 1558-2248</identifier><identifier>DOI: 10.1109/TWC.2016.2628789</identifier><identifier>CODEN: ITWCAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Base stations ; Batteries ; Cellular networks ; Content caching and push ; dynamic programming ; Energy consumption ; Energy harvesting ; heterogeneous networks ; Renewable energy ; Renewable energy sources ; small cell ; Wireless communication</subject><ispartof>IEEE transactions on wireless communications, 2017-02, Vol.16 (2), p.717-729</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-7ac459fad16845db6b9eede6dff1595c5c06a265f5a9fdba9c04ee9efe42969c3</citedby><cites>FETCH-LOGICAL-c291t-7ac459fad16845db6b9eede6dff1595c5c06a265f5a9fdba9c04ee9efe42969c3</cites><orcidid>0000-0002-9670-6336</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7744665$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7744665$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Gong, Jie</creatorcontrib><creatorcontrib>Zhou, Sheng</creatorcontrib><creatorcontrib>Zhou, Zhenyu</creatorcontrib><creatorcontrib>Niu, Zhisheng</creatorcontrib><title>Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><description>Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS to total number of user requests. With finite battery capacity, Markov decision process-based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based policy and the energy-efficient threshold-based policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high.</description><subject>Base stations</subject><subject>Batteries</subject><subject>Cellular networks</subject><subject>Content caching and push</subject><subject>dynamic programming</subject><subject>Energy consumption</subject><subject>Energy harvesting</subject><subject>heterogeneous networks</subject><subject>Renewable energy</subject><subject>Renewable energy sources</subject><subject>small cell</subject><subject>Wireless communication</subject><issn>1536-1276</issn><issn>1558-2248</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLAzEQRhdRsFbvgpeA561JuslujrKoFYotWPEY0-ykpm6TmqSV-uvd0uJp5vC-b4aXZdcEDwjB4m72Xg8oJnxAOa3KSpxkPcJYlVNaVKf7fchzQkt-nl3EuMSYlJyxXvYx9a3VOzRZJ7uyvypZ75DxAdXeJXAJTTfxE22tQg8OwmKHRipsISbrFuh1pdoW1dC2EVmHRpAg-AU48JuIXiD9-PAVL7Mzo9oIV8fZz94eH2b1KB9Pnp7r-3GuqSApL5UumDCqIbwqWDPncwHQAG-MIUwwzTTminJmmBKmmSuhcQEgwEBBBRd62M9uD73r4L833Ydy6TfBdSclqbpOyiqCOwofKB18jAGMXAe7UmEnCZZ7j7LzKPce5dFjF7k5RCwA_ONlWRScs-Efi-Nwrw</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Gong, Jie</creator><creator>Zhou, Sheng</creator><creator>Zhou, Zhenyu</creator><creator>Niu, Zhisheng</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/0000-0002-9670-6336</orcidid></search><sort><creationdate>20170201</creationdate><title>Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks</title><author>Gong, Jie ; Zhou, Sheng ; Zhou, Zhenyu ; Niu, Zhisheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-7ac459fad16845db6b9eede6dff1595c5c06a265f5a9fdba9c04ee9efe42969c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Base stations</topic><topic>Batteries</topic><topic>Cellular networks</topic><topic>Content caching and push</topic><topic>dynamic programming</topic><topic>Energy consumption</topic><topic>Energy harvesting</topic><topic>heterogeneous networks</topic><topic>Renewable energy</topic><topic>Renewable energy sources</topic><topic>small cell</topic><topic>Wireless communication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gong, Jie</creatorcontrib><creatorcontrib>Zhou, Sheng</creatorcontrib><creatorcontrib>Zhou, Zhenyu</creatorcontrib><creatorcontrib>Niu, Zhisheng</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005–Present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE/IET Electronic Library (IEL) - Journals and E-Books</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 wireless communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gong, Jie</au><au>Zhou, Sheng</au><au>Zhou, Zhenyu</au><au>Niu, Zhisheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks</atitle><jtitle>IEEE transactions on wireless communications</jtitle><stitle>TWC</stitle><date>2017-02-01</date><risdate>2017</risdate><volume>16</volume><issue>2</issue><spage>717</spage><epage>729</epage><pages>717-729</pages><issn>1536-1276</issn><eissn>1558-2248</eissn><coden>ITWCAX</coden><abstract>Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS to total number of user requests. With finite battery capacity, Markov decision process-based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based policy and the energy-efficient threshold-based policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TWC.2016.2628789</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-9670-6336</orcidid></addata></record> |
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subjects | Base stations Batteries Cellular networks Content caching and push dynamic programming Energy consumption Energy harvesting heterogeneous networks Renewable energy Renewable energy sources small cell Wireless communication |
title | Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks |
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