Vasilakos, Xenofon and Al-Khalidi, Mohammed and Siris, Vasilios A and Reed, Martin J and Thomos, Nikolaos and Polyzos, George C (2017) Mobility-based Proactive Multicast for Seamless Mobility Support in Cellular Network Environments. In: Workshop on Mobile Edge Communications - MECOMM '17, 2017-08-21 - 2017-08-21, Los Angeles.
Vasilakos, Xenofon and Al-Khalidi, Mohammed and Siris, Vasilios A and Reed, Martin J and Thomos, Nikolaos and Polyzos, George C (2017) Mobility-based Proactive Multicast for Seamless Mobility Support in Cellular Network Environments. In: Workshop on Mobile Edge Communications - MECOMM '17, 2017-08-21 - 2017-08-21, Los Angeles.
Vasilakos, Xenofon and Al-Khalidi, Mohammed and Siris, Vasilios A and Reed, Martin J and Thomos, Nikolaos and Polyzos, George C (2017) Mobility-based Proactive Multicast for Seamless Mobility Support in Cellular Network Environments. In: Workshop on Mobile Edge Communications - MECOMM '17, 2017-08-21 - 2017-08-21, Los Angeles.
Abstract
Information-Centric Networking (ICN) is receiver driven, asynchronous and location-independent, hence it natively supports client-mobility. However, post-handover delay is a problem for delay-sensitive mobile applications, as they need to (re-)submit their subscriptions and wait for them to get resolved and (probably re-) transmitted before receiving the demanded data. To avoid this problem and optimize performance, this paper proposes a Mobility-based Proactive Multicast (MPM) scheme. Unlike reactive or blind multicast solutions proposed in the past, MPM takes autonomous decisions locally at various network access points (cells) prior to the movement of mobile clients, using a semi-Markov mobility prediction model that predicts next-cell transitions, along with anticipating the duration between the transitions for an arbitrary user in a cellular network. Since cellular backhaul links are typically a bottleneck, MPM trades-off effectively part of the capacity of the (congested) backhaul link for a decreased delay experienced by users after handovers thanks to a congestion pricing scheme used for backhaul capacity allocation. Our preliminary performance evaluation results show that MPM captures well the temporal locality of mobile requests due to the semi-Markov mobility prediction model, hence it achieves a better performance compared to both a (i) blind/naïve multicast and a (ii) content popularity-based proactive multicast.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | Published proceedings: Proceedings of the Workshop on Mobile Edge Communications - MECOMM '17 |
Uncontrolled Keywords: | proactive multicast; markov; mobility prediction |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Feb 2020 14:36 |
Last Modified: | 30 Oct 2024 15:54 |
URI: | http://repository.essex.ac.uk/id/eprint/20879 |
Available files
Filename: p25-Vasilakos.pdf