Cost-Efficient Traffic Allocation in Content Delivery Networks: a Linear Programming Approach

Due to the surge in mobile apps, online videos, and cloud gaming, central servers struggle with high traffic demands. Content delivery networks (CDNs) mitigate this by distributing content from edge caches, easing backbone network strain. Yet, current allocation algorithms, constrained by practical complexities and billing, often fail to optimally schedule traffic, causing server overload and increased costs. Our solution, CEQC-CDN, addresses these issues by considering DNS load balancing, regional hijacking, quality constraints, and server capacity limits. By incorporating these factors as linear constraints through binary decomposition and variable introduction, CEQC-CDN achieves global optimal traffic scheduling. Employing a greedy policy for monthly optimization, tests demonstrate an 8.57% reduction in CDN traffic costs versus conventional greedy algorithms.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/hpcc64274.2024.00126
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
0.00

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article

Cost-Efficient Traffic Allocation in Content Delivery Networks: a Linear Programming Approach

Yihong Ling, Xiaoxiao Wu, Tong Jian, Yifei Zou et al.
Caching and Content Delivery
article

Cost-Efficient Traffic Allocation in Content Delivery Networks: a Linear Programming Approach

Yihong Ling, Xiaoxiao Wu, Tong Jian, Yifei Zou, Dongxiao Yu, Ruomei Liu, Haofei Yin, Guangzheng Lin, Rongxiang Huo
article en

Abstract

Due to the surge in mobile apps, online videos, and cloud gaming, central servers struggle with high traffic demands. Content delivery networks (CDNs) mitigate this by distributing content from edge caches, easing backbone network strain. Yet, current allocation algorithms, constrained by practical complexities and billing, often fail to optimally schedule traffic, causing server overload and increased costs. Our solution, CEQC-CDN, addresses these issues by considering DNS load balancing, regional hijacking, quality constraints, and server capacity limits. By incorporating these factors as linear constraints through binary decomposition and variable introduction, CEQC-CDN achieves global optimal traffic scheduling. Employing a greedy policy for monthly optimization, tests demonstrate an 8.57% reduction in CDN traffic costs versus conventional greedy algorithms.

Bayi Children's Hospital (CN), Cloud Computing Center (CN), Shandong University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 64%
Caching and Content Delivery
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Cost-Efficient Traffic Allocation in Content Delivery Networks: a Linear Programming Approach — Yihong Ling, Xiaoxiao Wu, et al. · (2024) | TGRS Research Map | TGRS