University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Enabling Context-aware HTTP with Mobile Edge Hint

Qian, Peng, Wang, Ning, Foster, G and Tafazolli, Rahim (2017) Enabling Context-aware HTTP with Mobile Edge Hint In: IEEE CCNC 2017, 2017-01-08 - 2017-01-11, Las Vegas, USA.

[img]
Preview
Text
CCNC_2017_Oct-24.pdf - Accepted version Manuscript
Available under License : See the attached licence file.

Download (1MB) | Preview
[img]
Preview
PDF (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

Due to dynamic wireless network conditions and heterogeneous mobile web content complexities, web-based content services in mobile network environments always suffer from long loading time. The new HTTP/2.0 protocol only adopts one single TCP connection, but recent research reveals that in real mobile environments, web downloading using single connection will experience long idle time and low bandwidth utilization, in particular with dynamic network conditions and web page characteristics. In this paper, by leveraging the Mobile Edge Computing (MEC) technique, we present the framework of Mobile Edge Hint (MEH), in order to enhance mobile web downloading performances. Specifically, the mobile edge collects and caches the meta-data of frequently visited web pages and also keeps monitoring the network conditions. Upon receiving requests on these popular webpages, the MEC server is able to hint back to the HTTP/2.0 clients on the optimized number of TCP connections that should be established for downloading the content. From the test results on real LTE testbed equipped with MEH, we observed up to 34.5% time reduction and in the median case the improvement is 20.5% compared to the plain over-the-top (OTT) HTTP/2.0 protocol.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Communcation Systems
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
NameEmailORCID
Qian, Pengp.qian@surrey.ac.ukUNSPECIFIED
Wang, NingN.Wang@surrey.ac.ukUNSPECIFIED
Foster, GUNSPECIFIEDUNSPECIFIED
Tafazolli, RahimR.Tafazolli@surrey.ac.ukUNSPECIFIED
Date : 2017
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Contributors :
ContributionNameEmailORCID
UNSPECIFIEDIEEE, UNSPECIFIEDUNSPECIFIED
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 25 Oct 2016 14:33
Last Modified : 18 Jul 2017 14:34
URI: http://epubs.surrey.ac.uk/id/eprint/812601

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800