Augmenting home routers for socially-aware traffic management

Abstract

Mobile users' Quality-of-Experience (QoE) is degrading as network usage increases while Internet Service Providers (ISP) face increased inter-domain traffic. This paper presents a network traffic management mechanism, named RB-HORST, addressing these inefficiencies. RB-HORST exploits home routers by using them as caches and forming an overlay network between them to transfer content. To shift traffic from peak hours, RB-HORST employs predictions based on social network properties and based on similarity in the overlay network. To further improve user QoE, home routers allow trusted mobile devices to offload their mobile connection to the local WiFi. Simulation results show that an overlay is imperative for the success of the proposed caching mechanism. Especially ISPs with a large number of customers can benefit if only every thousandth user shares its router, reducing inter-domain traffic by half and superseding an ISP operated cache. The presented implementation proves that the concept is technically feasible and can be deployed and run on constrained devices.

Quality of experience and access network traffic management of HTTP adaptive video streaming

“…Afterwards, the focus is on Wi-Fi o oading as a SATM mechanism, which is not only widely considered by ISPs to reduce the load on stressed mobile access networks, but is also well suited in the home environment due to the prevalence of residential Wi-Fi networks. This thesis presents a hotspot location model for public Wi-Fi o oading [10], a SATM system for private Wi-Fi o oading in home environments [42,56], and a performance evaluation on the QoE end energy e ciency of public and private Wi-Fi o oading of HAS ows [29,44,47].…”

“…Section 4.2 presents a simple model to describe the locations of public Wi-Fi infrastructure in cities based on [10]. Moreover, it describes a collaborative SATM platform for HAS on residential Wi-Fi routers based on [42,56], which supports private Wi-Fi o oading, as well as the distribution and caching of niche content. A performance evaluation of the gain of Wi-Fi o oading for HAS is conducted in Section 4.3 based on [29,44,47], and the applicability of the simple hotspot location model is investigated.…”

“…However, private Wi-Fi networks should not be publicly shared, but only to trusted friends. Therefore, Section 4.2.2 presents a framework for Home Router Sharing based on Trust (HORST) following [42,56]. The framework enables private Wi-Fi o oading, and additionally supports content delivery, caching, and prefetching mechanisms for HAS.…”

“…In contrast, the actual architecture and implementation of the prototype are not part of this work, and thus, only some implementation details are mentioned here to better understand the speci cation of the mechanisms. The entire design and implementation of the prototype is described in detail in [42] and its functionality was demonstrated in [65].…”

“…The social information is collected from the Facebook app via the Facebook Graph Application Programming Interface (API) and the video content provider, which is the Vimeo 22 video sharing portal. The exact speci cations of the prediction algorithms implemented in the prototype can be found in [42]. Both algorithms output rankings of relevant video contents.…”