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2018-12-12 Workshop Programme

ITG FA 5.2 Workshop
Communication Network Performance Modelling and Evaluation


Location:  Hamburg University of Technology, Am Schwarzenberg-Campus, Hamburg


Room:  4.041 (Building E, 4th Floor)


Registration


09:00 - 10:00 ITG 5.2.1 Fachgruppentreffen


10:00 Welcome Coffee

Draft Agenda



Presenter’s name

Topic

Affiliation

10:30

Paul Kühn

Performance Evaluation of Fork-Join Problems by Analytic Task Graph Reductions

U Stuttgart

11:00

Tuan Khai Nguyen

Multi-step Virtual Network Functions Migration: A Time Minimisation Approach

TU Chemnitz

11:30

Christian Moldovan


Optimal Fairness and Quality in Video Streaming With Multiple Users

U Würzburg

12:00

Coffee (15min)

12:15

Frank Loh

Estimating Video Stalls
from Encrypted Traffic

U Würzburg

12:45

Paul Nikolaus

Integrating Fractional Brownian Motion Arrivals into the Statistical
Network Calculus

TU Kaiserslautern

13:15

Lunch

14:30

Christian Maier

Measuring the reliability of Wireless Networks

Salzburg Research Forschungsgesellschaft mbH


15:00

Annika Schwind

Potential Traffic Savings by Leveraging Proximity of Communication Groups in Mobile Messaging

U Würzburg

15:30

Sebastian Lindner

A Multi-Level Game Theoretic Algorithm for Device-to-Device Resource Allocation with Frequency Reuse

TUHH

16:00

Coffee Break

16:30

Sebastian Kühlmorgen

Szenariobasierte Untersuchung von dezentraler Überlaststeuerung und kooperativem Relaying in Fahrzeugkommunikationsnetzen

TU  Dresden

17:00

Sudeep Hedge

Enhanced Resource Scheduling for Platooning in 5G V2X Systems

Nokia Bells Lab Stutgart / TUHH


Abstracts:

Frank Loh

Today's traffic projections speak of almost 58% video traffic across the
Internet. Nearly all video traffic is encrypted, accounting for more
than 50% encrypted traffic worldwide. To analyze video traffic today, or
even estimate its quality in the network, a deep look into the traffic
characteristics has to be done. But then, important quality metrics from
the traffic behavior can be derived. Based on extensive measurements it
is shown how to measure and estimate video stalls for mobile adaptive
streaming. A dataset of video footage from the native YouTube app is
measured with over 18 different videos in 12 network scenarios. A
possible approach to estimate the video playback buffer size in
real-time to break down the video stalls is presented. It is intended as
a tool for network operators to receive further knowledge of the
characteristics of video streaming traffic to quantify the most
important QoE degradation factors of one of the most important
applications today.


Christian Maier

In the future, connected vehicles and automated factories will use wireless communication. To implement these applications, wireless networks must be reliable. Because the cost of communication failures in such applications is high, reliability should not only be estimated in advance, but also measured directly in practice. To date, no method exists that is able to determine, if a wireless network is 99.999% reliable.

To address this need, we propose a black box test that uses only the success/fail status of transmissions to determine the reliability of wireless communication. The test is based on crucial assumptions, whose validity we test as part of the method.

The proposed method is especially suited when access to lower layer information is limited to the information returned by off-the-shelf hardware. The method measures reliability of wireless networks without support and knowledge from the network operator and administrator. In the future, methods such as the proposed one are needed to ensure reliable operation of wireless networks in critical scenarios.


Annika Schwind

Communication groups in mobile messaging applications (MMAs) multiply the data transmissions, because every message has to be delivered to all members of the communication group. Thereby, they put a high load on mobile networks. As the number of recipients is still comparably small, the data-intensive user-generated content cannot be handled efficiently in large content delivery networks. However, small communication groups, such as groups of friends or teams, might often be in close proximity, which can be leveraged to locally deliver messages by applying edge caching or device-to-device (D2D) communication. In this work, a simulation study is conducted to investigate these potential traffic savings in the mobile network. It is based on a realistic communication model of the MMA WhatsApp and utilizes different models for human mobility. The user mobility and MMA

communication are simulated for a single day in a small city to obtain the ratio of messages, which could be potentially transmitted locally when utilizing edge caching and D2D communication.


Paul Nikolaus

"Integrating Fractional Brownian Motion Arrivals into the Statistical
Network Calculus".

Abstract:
Stochastic network calculus (SNC) is a versatile framework to derive
probabilistic performance bounds. Recently, it was proposed in [1] to
replace the typical a priori assumptions on arrival processes with
measurement observations and to incorporate the corresponding
statistical uncertainty into calculation of the bounds. This so-called
statistical network calculus (StatNC) opens the door for many
applications with limited traffic information. However, the important
traffic class of self-similar processes such as fractional Brownian
Motion (fBm) was left open in [1], thus, e.g., depriving the usage of
the StatNC for Internet traffic. In this work, we close this gap by
integrating fBm arrivals into the StatNC. To this end, we analyze the
impact imposed by the uncertainty on the backlog bound and show in
numerical evaluations that the additional inaccuracy is only of moderate
size.

[1] M.A. Beck, S.A. Henningsen, S.B. Birnbach, and J. Schmitt, “Towards
a statistical network calculus - dealing with uncertainty in arrivals,”
in Proc. IEEE International Conference on Computer Communications
(INFOCOM’14), Toronto, Canada, 2014.

Christian Moldovan

With the majority of video distribution services relying on the HTTP adaptive streaming paradigm, a great deal of research is geared towards developing algorithms and solutions for improving user perceived quality while making efficient use of available resources. Our goal is to provide the means for benchmarking such solutions in the context of multiple users accessing Video on Demand content while sharing a bottleneck link. For that purpose, we propose a quadratic problem formulation to compute the theoretical optimum in terms of adaptation strategies and corresponding segment downloads across multiple users under given bandwidth constraints. By aiming to maximize both service quality and fairness, we quantify and compare the impact of different fairness objectives (bandwidth fairness, pattern fairness, and session fairness) on resulting quality and achieved QoE fairness. Based on conducted simulations and parameter studies, our results demonstrate the benefits of optimizing for session fairness as compared to other approaches.


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