Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks
Multiaccess edge computing and caching (MEC) is regarded as one of the key technologies of fifth-generation (5G) radio access networks. By bringing computing and storage resources closer to the end users, MEC could help to reduce network congestion and improve user experience. However, deploying man...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8777166/ |
| _version_ | 1818855722168877056 |
|---|---|
| author | Ming Yan Chien Aun Chan Wenwen Li Ling Lei Andre F. Gygax Chih-Lin I |
| author_facet | Ming Yan Chien Aun Chan Wenwen Li Ling Lei Andre F. Gygax Chih-Lin I |
| author_sort | Ming Yan |
| collection | DOAJ |
| description | Multiaccess edge computing and caching (MEC) is regarded as one of the key technologies of fifth-generation (5G) radio access networks. By bringing computing and storage resources closer to the end users, MEC could help to reduce network congestion and improve user experience. However, deploying many distributed MEC servers at the edge of wireless networks is challenging not only in terms of managing resource allocation and distribution but also in regard to reducing network energy consumption. Here, we focus on the latter by assessing the network energy consumption of different cache updating and replacement algorithms. First, we introduce our proposed proactive caching (PC) algorithm for mobile edge caching with Zipf request patterns, which could potentially improve the cache hit rates compared to other caching algorithms such as least recently used, least frequently used, and popularity-based caching. Then, we present the energy assessment models for mobile edge caching by breaking down the total network energy consumption into transmission and storage energy consumption. Finally, we perform a comprehensive simulation to assess the energy consumption of the PC algorithm under different key factors and compare with that of conventional algorithms. The simulation results show that improving cache hit rates by using the PC algorithm comes at the expense of additional energy consumption for network transmission. |
| first_indexed | 2024-12-19T08:13:07Z |
| format | Article |
| id | doaj.art-82e8193152e245a6bc70b7aae8bc659a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:13:07Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-82e8193152e245a6bc70b7aae8bc659a2022-12-21T20:29:35ZengIEEEIEEE Access2169-35362019-01-01710439410440410.1109/ACCESS.2019.29314498777166Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless NetworksMing Yan0https://orcid.org/0000-0001-8979-8490Chien Aun Chan1Wenwen Li2Ling Lei3Andre F. Gygax4Chih-Lin I5School of Information and Telecommunications Engineering, Communication University of China, Beijing, ChinaDepartment of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC, AustraliaGreen Communications Research Center, China Mobile Research Institute, Beijing, ChinaSchool of Information and Telecommunications Engineering, Communication University of China, Beijing, ChinaDepartment of Finance, Faculty of Business and Economics, The University of Melbourne, Parkville, VIC, AustraliaGreen Communications Research Center, China Mobile Research Institute, Beijing, ChinaMultiaccess edge computing and caching (MEC) is regarded as one of the key technologies of fifth-generation (5G) radio access networks. By bringing computing and storage resources closer to the end users, MEC could help to reduce network congestion and improve user experience. However, deploying many distributed MEC servers at the edge of wireless networks is challenging not only in terms of managing resource allocation and distribution but also in regard to reducing network energy consumption. Here, we focus on the latter by assessing the network energy consumption of different cache updating and replacement algorithms. First, we introduce our proposed proactive caching (PC) algorithm for mobile edge caching with Zipf request patterns, which could potentially improve the cache hit rates compared to other caching algorithms such as least recently used, least frequently used, and popularity-based caching. Then, we present the energy assessment models for mobile edge caching by breaking down the total network energy consumption into transmission and storage energy consumption. Finally, we perform a comprehensive simulation to assess the energy consumption of the PC algorithm under different key factors and compare with that of conventional algorithms. The simulation results show that improving cache hit rates by using the PC algorithm comes at the expense of additional energy consumption for network transmission.https://ieeexplore.ieee.org/document/8777166/Wireless edge cachingenergy consumption5Gmultiaccess edge computingproactive caching |
| spellingShingle | Ming Yan Chien Aun Chan Wenwen Li Ling Lei Andre F. Gygax Chih-Lin I Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks IEEE Access Wireless edge caching energy consumption 5G multiaccess edge computing proactive caching |
| title | Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks |
| title_full | Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks |
| title_fullStr | Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks |
| title_full_unstemmed | Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks |
| title_short | Assessing the Energy Consumption of Proactive Mobile Edge Caching in Wireless Networks |
| title_sort | assessing the energy consumption of proactive mobile edge caching in wireless networks |
| topic | Wireless edge caching energy consumption 5G multiaccess edge computing proactive caching |
| url | https://ieeexplore.ieee.org/document/8777166/ |
| work_keys_str_mv | AT mingyan assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks AT chienaunchan assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks AT wenwenli assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks AT linglei assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks AT andrefgygax assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks AT chihlini assessingtheenergyconsumptionofproactivemobileedgecachinginwirelessnetworks |