Neutral Net Neutrality

Yiakoumis, Yiannis; McKeown, Nick

doi:10.1145/2934872.2934896

Cited by 14 publications

(6 citation statements)

References 14 publications

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“…In that sense, it is also interesting to note that some user studies (e.g. by Yiakoumis et al [28]) have shown that endusers actually want specific services to have a differential treatment in the network.…”

Section: Building the Generic App-net Modelmentioning

confidence: 98%

Quantitative comparison of application–network interaction: a case study of adaptive video streaming

2017

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Managing quality of experience (QoE) is now widely accepted as a critical objective for multimedia applications and the supporting communication systems. In general, QoE management encompasses: (1) monitoring of the key influence factors and QoE indicators, and (2) deciding on the appropriate control actions as specified by the management goal. Many multimedia applications, e.g., video streaming and audio conferencing, are able to adjust their operational parameters so as to react to variations in the network performance. However, such an adaptation feature is mostly based on a local client view of the network conditions, which may lead to an unfair allocation of network resources among heterogeneous clients and, thus, an unfair QoE distribution. In order to tackle this issue, there is the call for a cooperation between the applications and the underlying network, which includes applicationnetwork interaction (App-Net) in terms of: (1) exchanging information on the monitored QoE indicators, and (2) coordinating the QoE control actions. Various App-Net mechanisms focusing on specific use cases and applications have been proposed to date. This paper gives an overview of App-Net mechanisms and proposes a generic App-Net model that provides the means to realize a coordinated QoE-centric management. Based on the App-Net model, we develop an evaluation methodology to compare three App-Net mechanisms for managing QoE of HTTP adaptive streaming (HAS) against a baseline HAS service. The aim of this quantitative comparison is to explore the trade-offs between QoE gains and the complexity of App-Net implementation, with respect to the number of monitoring and control messages, achieved video quality, and QoE fairness among heterogeneous clients. Our ultimate goal is to set up reproducible experiments that facilitate a holistic evaluation of different App-Net mechanisms.

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Section: Building the Generic App-net Modelmentioning

confidence: 98%

Quantitative comparison of application–network interaction: a case study of adaptive video streaming

2017

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“…The increasing softwarization of the network infrastructure, enabled by the advancements in computing power and virtualization techniques, has facilitated the support of new applications and services inside the network. Among different opportunities, network vendors and researchers have looked at solutions that explore how to better integrate inputs from the application logic to optimize network functionality [49,53,54,18]. While this is a useful direction, more general solutions capable of extending beyond the limits of single networks are still lacking.…”

Section: Advanced Mec Techniquesmentioning

confidence: 99%

NOVN: A named-object based virtual network architecture to support advanced mobile edge computing services

Bronzino

Maheshwari

Seskar

et al. 2020

Pervasive and Mobile Computing

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Achieving advanced Mobile Edge Computing (MEC) services such as dynamic resource assignment and slicing, maintaining Quality of Service (QoS), and enabling heterogeneous virtual functions are some of the technical challenges associated with edge-cloud enhanced 5G architectures now under consideration. This paper proposes a named-object based virtual network (NOVN) architecture to support low-latency applications in the MEC. Software router implementation running on the ORBIT testbed validates the named-object approach, showing low VN processing and control overhead, and making it possible to achieve low latency. A latency performance improvement of 30% is achieved as compared to the baseline implementation without NOVN. The results also validate feasibility of using the advanced MEC services for an example latency constrained edge cloud scenario.

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“…Neither were they affected by important regulatory decisions during the 10-years period as can be seen in Figure 1. Some projects [4] introduce technical ways in which consumers could set their fast lane preferences in order to alleviate the net neutrality repeal, but this may, as well, prove essentially unfair users would hardly be willing to include or even get to notice new-born services or start-up CAPs. Eventually, there have been some cases, as in [5], where economists have gone even further and have supported such fast lanes, comparing them to the traditional concept of fast postal delivery for users who pay more.…”

Section: Introductionmentioning

confidence: 99%