Joint Optimization of Caching and Transport in Proactive Edge Cloud. Sardellitti, S., Costanzo, F., & Merluzzi, M. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 797-801, Sep., 2018.
Paper doi abstract bibtex Our goal in this paper is to devise a strategy for finding the optimal trade-off between the transport and caching energy costs associated to the delivery of contents in information networks. The proposed strategy is proactive with respect to the users' requests, as contents are pre-fetched depending on the distribution of their (estimated) popularity. In particular, we propose a k-center dominating set strategy to find the optimal clustering and then locate the best places to store/replicate the most popular contents. Then we develop a dynamic energy-efficient, strategy that jointly optimizes caching and delivery costs within each cluster. Although the formulated problem is a binary problem, we will show as it can be solved for moderate size networks by using efficient solvers. The performance gain reached through the proposed proactive strategy are then assessed by numerical results.
@InProceedings{8553288,
author = {S. Sardellitti and F. Costanzo and M. Merluzzi},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {Joint Optimization of Caching and Transport in Proactive Edge Cloud},
year = {2018},
pages = {797-801},
abstract = {Our goal in this paper is to devise a strategy for finding the optimal trade-off between the transport and caching energy costs associated to the delivery of contents in information networks. The proposed strategy is proactive with respect to the users' requests, as contents are pre-fetched depending on the distribution of their (estimated) popularity. In particular, we propose a k-center dominating set strategy to find the optimal clustering and then locate the best places to store/replicate the most popular contents. Then we develop a dynamic energy-efficient, strategy that jointly optimizes caching and delivery costs within each cluster. Although the formulated problem is a binary problem, we will show as it can be solved for moderate size networks by using efficient solvers. The performance gain reached through the proposed proactive strategy are then assessed by numerical results.},
keywords = {cache storage;cloud computing;optimisation;joint optimization;proactive edge cloud;caching energy costs;information networks;k-center dominating;optimal clustering;dynamic energy-efficient;jointly optimizes caching;delivery costs;moderate size networks;proactive strategy;Optimization;Routing;Energy consumption;Europe;Signal processing;Delays;Indexes;Proactive content delivery;in-network caching;energy efficiency;information centric networking},
doi = {10.23919/EUSIPCO.2018.8553288},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437836.pdf},
}
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