Exploiting mobility prediction for mobility & popularity caching and DASH adaptation

Vasilios A. Siris, Xenofon Vasilakos, Dimitrios Dimopoulos

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

7 Citations (Scopus)

Abstract

We present our recent work investigating how mobility prediction can be exploited for improving the performance of mobile users in two directions: proactive caching requested content close to the network attachment points where a mobile has a high probability to connect to and DASH (Dynamic Adaptive Streaming over HTTP) video quality adaptation. For proactive caching we discuss a new model to proactively cache content based on both mobility prediction and content popularity. An important feature of the model is that it dynamically adapts caching decisions to the relative importance of the two factors. For DASH adaptation we discuss a procedure that exploits mobility and throughput prediction to select the quality levels of video segments requested by a DASH player in order to achieve improved QoE, in terms of both high video quality and few video quality switches.

Original languageEnglish
Title of host publicationWoWMoM 2016 - 17th International Symposium on a World of Wireless, Mobile and Multimedia Networks
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781509021857
DOIs
Publication statusPublished - 26 Jul 2016
Event17th International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2016 - Coimbra, Portugal
Duration: 21 Jun 201624 Jun 2016

Publication series

NameWoWMoM 2016 - 17th International Symposium on a World of Wireless, Mobile and Multimedia Networks

Conference

Conference17th International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2016
CountryPortugal
CityCoimbra
Period21/06/1624/06/16

Fingerprint Dive into the research topics of 'Exploiting mobility prediction for mobility & popularity caching and DASH adaptation'. Together they form a unique fingerprint.

Cite this