Cost-efficient edge caching for NOMA-enabled IoT services
Mobile edge computing (MEC) is a promising paradigm by deploying edge servers (nodes) with computation and storage capacity close to IoT devices. Content Providers can cache data in edge servers and provide services for IoT devices, which effectively reduces the delay for acquiring data. With the in...
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| Published in | China communications Vol. 21; no. 8; pp. 182 - 191 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
China Institute of Communications
01.08.2024
School of Computer Science,Beijing Information Science and Technology University,Beijing 100101,China%Beijing Key Laboratory of Petroleum Data Mining,China University of Petroleum,Beijing 102249,China |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1673-5447 |
| DOI | 10.23919/JCC.fa.2021-0830.202408 |
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| Abstract | Mobile edge computing (MEC) is a promising paradigm by deploying edge servers (nodes) with computation and storage capacity close to IoT devices. Content Providers can cache data in edge servers and provide services for IoT devices, which effectively reduces the delay for acquiring data. With the increasing number of IoT devices requesting for services, the spectrum resources are generally limited. In order to effectively meet the challenge of limited spectrum resources, the Non-Orthogonal Multiple Access (NOMA) is proposed to improve the transmission efficiency. In this paper, we consider the caching scenario in a NOMA-enabled MEC system. All the devices compete for the limited resources and tend to minimize their own cost. We formulate the caching problem, and the goal is to minimize the delay cost for each individual device subject to resource constraints. We reformulate the optimization as a non-cooperative game model. We prove the existence of Nash equilibrium (NE) solution in the game model. Then, we design the Game-based Cost-Efficient Edge Caching Algorithm (GCECA) to solve the problem. The effectiveness of our GCECA algorithm is validated by both parameter analysis and comparison experiments. |
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| AbstractList | Mobile edge computing (MEC) is a promising paradigm by deploying edge servers (nodes) with computation and storage capacity close to IoT devices. Content Providers can cache data in edge servers and provide services for IoT devices, which effectively reduces the delay for acquiring data. With the increasing number of IoT devices requesting for services, the spectrum resources are generally limited. In order to effectively meet the challenge of limited spectrum resources, the Non-Orthogonal Multiple Access (NOMA) is proposed to improve the transmission efficiency. In this paper, we consider the caching scenario in a NOMA-enabled MEC system. All the devices compete for the limited resources and tend to minimize their own cost. We formulate the caching problem, and the goal is to minimize the delay cost for each individual device subject to resource constraints. We reformulate the optimization as a non-cooperative game model. We prove the existence of Nash equilibrium (NE) solution in the game model. Then, we design the Game-based Cost-Efficient Edge Caching Algorithm (GCECA) to solve the problem. The effectiveness of our GCECA algorithm is validated by both parameter analysis and comparison experiments. Mobile edge computing(MEC)is a promising paradigm by deploying edge servers(nodes)with computation and storage capacity close to IoT devices.Content Providers can cache data in edge servers and provide services for IoT devices,which effectively reduces the delay for acquiring data.With the increasing number of IoT devices requesting for services,the spectrum resources are generally lim-ited.In order to effectively meet the challenge of lim-ited spectrum resources,the Non-Orthogonal Multiple Access(NOMA)is proposed to improve the transmis-sion efficiency.In this paper,we consider the caching scenario in a NOMA-enabled MEC system.All the devices compete for the limited resources and tend to minimize their own cost.We formulate the caching problem,and the goal is to minimize the delay cost for each individual device subject to resource constraints.We reformulate the optimization as a non-cooperative game model.We prove the existence of Nash equi-librium(NE)solution in the game model.Then,we design the Game-based Cost-Efficient Edge Caching Algorithm(GCECA)to solve the problem.The effec-tiveness of our GCECA algorithm is validated by both parameter analysis and comparison experiments. |
| Author | Xin, Chen Zhuo, Ma Hua, Xing Jiwei, Huang Ying, Chen |
| AuthorAffiliation | School of Computer Science,Beijing Information Science and Technology University,Beijing 100101,China%Beijing Key Laboratory of Petroleum Data Mining,China University of Petroleum,Beijing 102249,China |
| AuthorAffiliation_xml | – name: School of Computer Science,Beijing Information Science and Technology University,Beijing 100101,China%Beijing Key Laboratory of Petroleum Data Mining,China University of Petroleum,Beijing 102249,China |
| Author_xml | – sequence: 1 givenname: Chen surname: Ying fullname: Ying, Chen organization: School of Computer Science, Beijing Information Science and Technology University, Beijing 100101, China – sequence: 2 givenname: Xing surname: Hua fullname: Hua, Xing organization: School of Computer Science, Beijing Information Science and Technology University, Beijing 100101, China – sequence: 3 givenname: Ma surname: Zhuo fullname: Zhuo, Ma organization: School of Computer Science, Beijing Information Science and Technology University, Beijing 100101, China – sequence: 4 givenname: Chen surname: Xin fullname: Xin, Chen organization: School of Computer Science, Beijing Information Science and Technology University, Beijing 100101, China – sequence: 5 givenname: Huang surname: Jiwei fullname: Jiwei, Huang organization: Beijing Key Laboratory of Petroleum Data Mining, China University of Petroleum, Beijing 102249, China |
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| Snippet | Mobile edge computing (MEC) is a promising paradigm by deploying edge servers (nodes) with computation and storage capacity close to IoT devices. Content... Mobile edge computing(MEC)is a promising paradigm by deploying edge servers(nodes)with computation and storage capacity close to IoT devices.Content Providers... |
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| SubjectTerms | caching Cloud computing cost Costs Delays Downlink Games Internet of Things mobile edge computing NOMA non-orthogonal multiple access |
| Title | Cost-efficient edge caching for NOMA-enabled IoT services |
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