Optimal Scheduling of Content Caching Subject to Deadline
Content caching at the edge of network is a promising technique to alleviate the burden of backhaul networks. In this paper, we consider content caching along time in a base station with limited cache capacity. As the popularity of contents may vary over time, the contents of cache need to be update...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Open Journal of the Communications Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9025174/ |
| _version_ | 1818411419541962752 |
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| author | Ghafour Ahani Di Yuan |
| author_facet | Ghafour Ahani Di Yuan |
| author_sort | Ghafour Ahani |
| collection | DOAJ |
| description | Content caching at the edge of network is a promising technique to alleviate the burden of backhaul networks. In this paper, we consider content caching along time in a base station with limited cache capacity. As the popularity of contents may vary over time, the contents of cache need to be updated accordingly. In addition, a requested content may have a delivery deadline within which the content needs to be obtained. Motivated by these, we address optimal scheduling of content caching in a time-slotted system under delivery deadline and cache capacity constraints. The objective is to minimize a cost function that captures the load of backhaul links. For our optimization problem, we prove its NP-hardness via a reduction from the Partition problem. For problem solving, via a mathematical reformulation, we develop a solution approach based on repeatedly applying a column generation algorithm and a problem-tailored rounding algorithm. In addition, two greedy algorithms are developed based on existing algorithms from the literature. Finally, we present extensive simulations that verify the effectiveness of our solution approach in obtaining near-to-optimal solutions in comparison to the greedy algorithms. The solutions obtained from our solution approach are within 1.6% from global optimality. |
| first_indexed | 2024-12-14T10:31:07Z |
| format | Article |
| id | doaj.art-ae8fbc8ee3374b668808201e7d345d8d |
| institution | Directory Open Access Journal |
| issn | 2644-125X |
| language | English |
| last_indexed | 2024-12-14T10:31:07Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj.art-ae8fbc8ee3374b668808201e7d345d8d2022-12-21T23:06:08ZengIEEEIEEE Open Journal of the Communications Society2644-125X2020-01-01129330710.1109/OJCOMS.2020.29785859025174Optimal Scheduling of Content Caching Subject to DeadlineGhafour Ahani0https://orcid.org/0000-0003-1869-6192Di Yuan1https://orcid.org/0000-0001-8119-5206Department of Information Technology, Uppsala University, Uppsala, SwedenDepartment of Information Technology, Uppsala University, Uppsala, SwedenContent caching at the edge of network is a promising technique to alleviate the burden of backhaul networks. In this paper, we consider content caching along time in a base station with limited cache capacity. As the popularity of contents may vary over time, the contents of cache need to be updated accordingly. In addition, a requested content may have a delivery deadline within which the content needs to be obtained. Motivated by these, we address optimal scheduling of content caching in a time-slotted system under delivery deadline and cache capacity constraints. The objective is to minimize a cost function that captures the load of backhaul links. For our optimization problem, we prove its NP-hardness via a reduction from the Partition problem. For problem solving, via a mathematical reformulation, we develop a solution approach based on repeatedly applying a column generation algorithm and a problem-tailored rounding algorithm. In addition, two greedy algorithms are developed based on existing algorithms from the literature. Finally, we present extensive simulations that verify the effectiveness of our solution approach in obtaining near-to-optimal solutions in comparison to the greedy algorithms. The solutions obtained from our solution approach are within 1.6% from global optimality.https://ieeexplore.ieee.org/document/9025174/Base stationcontent cachingdeadlineschedulingtime-varying popularity |
| spellingShingle | Ghafour Ahani Di Yuan Optimal Scheduling of Content Caching Subject to Deadline IEEE Open Journal of the Communications Society Base station content caching deadline scheduling time-varying popularity |
| title | Optimal Scheduling of Content Caching Subject to Deadline |
| title_full | Optimal Scheduling of Content Caching Subject to Deadline |
| title_fullStr | Optimal Scheduling of Content Caching Subject to Deadline |
| title_full_unstemmed | Optimal Scheduling of Content Caching Subject to Deadline |
| title_short | Optimal Scheduling of Content Caching Subject to Deadline |
| title_sort | optimal scheduling of content caching subject to deadline |
| topic | Base station content caching deadline scheduling time-varying popularity |
| url | https://ieeexplore.ieee.org/document/9025174/ |
| work_keys_str_mv | AT ghafourahani optimalschedulingofcontentcachingsubjecttodeadline AT diyuan optimalschedulingofcontentcachingsubjecttodeadline |