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Caching Online Video: Analysis and Proposed Algorithm

Published:12 August 2017Publication History
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Abstract

Online video presents new challenges to traditional caching with over a thousand-fold increase in number of assets, rapidly changing popularity of assets and much higher throughput requirements.

We propose a new hierarchical filtering algorithm for caching online video HiFi. Our algorithm is designed to optimize hit rate, replacement rate and cache throughput. It has an associated implementation complexity comparable to that of LRU.

Our results show that, under typical operator conditions, HiFi can increase edge cache byte hit rate by 5%--24% over an LRU policy, but more importantly can increase the RAM or memory byte hit rate by 80% to 200% and reduce the replacement rate by more than 100 times! These two factors combined can dramatically increase throughput for most caches. If SSDs are used for storage, the much lower replacement rate may also allow substitution of lower-cost MLC-based SSDs instead of SLC-based SSDs.

We extend previous multi-tier analytical models for LRU caches to caches with filtering. We analytically show how HiFi can approach the performance of an optimal caching policy and how to tune HiFi to reach as close to optimal performance as the traffic conditions allow. We develop a realistic simulation environment for online video using statistics from operator traces. We show that HiFi performs within a few percentage points from the optimal solution which was simulated by Belady's MIN algorithm under typical operator conditions

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      • Published in

        cover image ACM Transactions on Multimedia Computing, Communications, and Applications
        ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 13, Issue 4
        November 2017
        362 pages
        ISSN:1551-6857
        EISSN:1551-6865
        DOI:10.1145/3129737
        Issue’s Table of Contents

        Copyright © 2017 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 12 August 2017
        • Revised: 1 March 2017
        • Accepted: 1 March 2017
        • Received: 1 June 2016
        Published in tomm Volume 13, Issue 4

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