Coding for fast content download

By Gauri Joshi, Yanpei Liu, Emina Soljanin. 2012

100 citations recorded by the source corpus.

We study the fundamental trade-off between storage and content download time. We show that the download time can be significantly reduced by dividing the content into chunks, encoding it to add redundancy and then distributing it across multiple disks. We determine the download time for two content access models - the fountain and fork-join models that involve simultaneous content access, and individual access from enqueued user requests respectively. For the fountain model we explicitly characterize the download time, while in the fork-join model we derive the upper and lower bounds. Our results show that coding reduces download time, through the diversity of distributing the data across more disks, even for the total storage used.

Subfields: Computer Networks and Communications

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Citations in the corpus

Minimizing latency for secure distributed computing (2017, background): “studied in [12] the tradeoff between storage cost and content download time.”
Efficient task replication for fast response times in parallel computation (2014, background): “Finally, some other work also investigate using replication or redundancy to reduce latency in other contexts such as data transfer [12,13,17,18].”
On the Delay-Storage Trade-Off in Content Download from Coded Distributed Storage Systems (2013, background): “These results were presented in part in [5].”
Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing (2015, methodology): “We note that using replication or redundancy to reduce latency has also attracted attention in other contexts such as cloud storage and networking applications [12, 13,17,19].”
When do redundant requests reduce latency ? (2013, background): “The two related theoretical results that we know of are [15] and [9].”
Queues with Redundancy: Latency-Cost Analysis (2015, background): “The effect of redundancy in queueing systems was first analyzed only recently in [2, 3, 6], assuming exponential service time.”
Analyzing the download time of availability codes (2015, methodology): “Our work is inspired by a series of recent studies [3], [4], [5], [6], [7], which have analyzed codes (mainly, MDS”