NIDCMMAug 14, 2017

uStash: a Novel Mobile Content Delivery System for Improving User QoE in Public Transport

arXiv:1708.04078v14 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of poor user experience and high costs for mobile content access in public transport, though it is an incremental improvement over existing collaborative methods.

The authors tackled the problem of inefficient and costly mobile content delivery for users on public transport by proposing uStash, a system that reduces monthly cellular data costs by about 50% and expected access delays by 60% compared to standard cellular downloads.

Mobile data traffic is growing exponentially and it is even more challenging to distribute content efficiently while users are "on the move" such as in public transport.The use of mobile devices for accessing content (e.g. videos) while commuting are both expensive and unreliable, although it is becoming common practice worldwide. Leveraging on the spatial and temporal correlation of content popularity and users' diverse network connectivity, we propose a novel content distribution system, \textit{uStash}, which guarantees better QoE with regards to access delays and cost of usage. The proposed collaborative download and content stashing schemes provide the uStash provider the flexibility to control the cost of content access via cellular networks. We model the uStash system in a probabilistic framework and thereby analytically derive the optimal portions for collaborative downloading. Then, we validate the proposed models using real-life trace driven simulations. In particular, we use dataset from 22 inter-city buses running on 6 different routes and from a mobile VoD service provider to show that uStash reduces the cost of monthly cellular data by approximately 50\% and the expected delay for content access by 60\% compared to content downloaded via users' cellular network connections.

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