982 research outputs found
Optimizing the delivery of multimedia over mobile networks
MenciĂłn Internacional en el tĂtulo de doctorThe consumption of multimedia content is moving from a residential environment to mobile
phones. Mobile data traffic, driven mostly by video demand, is increasing rapidly and wireless
spectrum is becoming a more and more scarce resource. This makes it highly important to operate
mobile networks efficiently. To tackle this, recent developments in anticipatory networking
schemes make it possible to to predict the future capacity of mobile devices and optimize the
allocation of the limited wireless resources. Further, optimizing Quality of Experienceâsmooth,
quick, and high quality playbackâis more difficult in the mobile setting, due to the highly dynamic
nature of wireless links. A key requirement for achieving, both anticipatory networking
schemes and QoE optimization, is estimating the available bandwidth of mobile devices. Ideally,
this should be done quickly and with low overhead.
In summary, we propose a series of improvements to the delivery of multimedia over mobile
networks. We do so, be identifying inefficiencies in the interconnection of mobile operators with
the servers hosting content, propose an algorithm to opportunistically create frequent capacity estimations
suitable for use in resource optimization solutions and finally propose another algorithm
able to estimate the bandwidth class of a device based on minimal traffic in order to identify the
ideal streaming quality its connection may support before commencing playback.
The main body of this thesis proposes two lightweight algorithms designed to provide bandwidth
estimations under the high constraints of the mobile environment, such as and most notably
the usually very limited traffic quota. To do so, we begin with providing a thorough overview
of the communication path between a content server and a mobile device. We continue with
analysing how accurate smartphone measurements can be and also go in depth identifying the
various artifacts adding noise to the fidelity of on device measurements. Then, we first propose
a novel lightweight measurement technique that can be used as a basis for advanced resource
optimization algorithms to be run on mobile phones. Our main idea leverages an original packet
dispersion based technique to estimate per user capacity. This allows passive measurements by
just sampling the existing mobile traffic. Our technique is able to efficiently filter outliers introduced
by mobile network schedulers and phone hardware. In order to asses and verify our
measurement technique, we apply it to a diverse dataset generated by both extensive simulations
and a week-long measurement campaign spanning two cities in two countries, different radio
technologies, and covering all times of the day. The results demonstrate that our technique is effective even if it is provided only with a small fraction of the exchanged packets of a flow. The
only requirement for the input data is that it should consist of a few consecutive packets that are
gathered periodically. This makes the measurement algorithm a good candidate for inclusion in
OS libraries to allow for advanced resource optimization and application-level traffic scheduling,
based on current and predicted future user capacity.
We proceed with another algorithm that takes advantage of the traffic generated by short-lived
TCP connections, which form the majority of the mobile connections, to passively estimate the
currently available bandwidth class. Our algorithm is able to extract useful information even if the
TCP connection never exits the slow start phase. To the best of our knowledge, no other solution
can operate with such constrained input. Our estimation method is able to achieve good precision
despite artifacts introduced by the slow start behavior of TCP, mobile scheduler and phone hardware.
We evaluate our solution against traces collected in 4 European countries. Furthermore, the
small footprint of our algorithm allows its deployment on resource limited devices.
Finally, in an attempt to face the rapid traffic increase, mobile application developers outsource
their cloud infrastructure deployment and content delivery to cloud computing services
and content delivery networks. Studying how these services, which we collectively denote Cloud
Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding
some of the performance limitations of todayâs mobile apps. To that end, we perform
the first empirical study of the complex dynamics between applications, MNOs and CSPs. First,
we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign
to identify the most prevalent CSPs supporting todayâs mobile Internet. Then, we investigate how
well these services interconnect with major European MNOs at a topological level, and measure
their performance over European MNO networks through a month-long measurement campaign
on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs
are used by 85% of apps, and observe significant differences in their performance across different
MNOs due to the nature of their services, peering relationships with MNOs, and deployment
strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming,
and presence of middleboxes, but not influenced by the choice of DNS resolver. We also
observe that the choice of operatorâs Point of Presence (PoP) may inflate by at least 20% the
delay towards popular websites.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en IngenierĂa TelemĂĄticaPresidente: Ahmed Elmokashfi.- Secretario: RubĂŠn Cuevas RumĂn.- Vocal: Paolo Din
SecMon: End-to-End Quality and Security Monitoring System
The Voice over Internet Protocol (VoIP) is becoming a more available and
popular way of communicating for Internet users. This also applies to
Peer-to-Peer (P2P) systems and merging these two have already proven to be
successful (e.g. Skype). Even the existing standards of VoIP provide an
assurance of security and Quality of Service (QoS), however, these features are
usually optional and supported by limited number of implementations. As a
result, the lack of mandatory and widely applicable QoS and security guaranties
makes the contemporary VoIP systems vulnerable to attacks and network
disturbances. In this paper we are facing these issues and propose the SecMon
system, which simultaneously provides a lightweight security mechanism and
improves quality parameters of the call. SecMon is intended specially for VoIP
service over P2P networks and its main advantage is that it provides
authentication, data integrity services, adaptive QoS and (D)DoS attack
detection. Moreover, the SecMon approach represents a low-bandwidth consumption
solution that is transparent to the users and possesses a self-organizing
capability. The above-mentioned features are accomplished mainly by utilizing
two information hiding techniques: digital audio watermarking and network
steganography. These techniques are used to create covert channels that serve
as transport channels for lightweight QoS measurement's results. Furthermore,
these metrics are aggregated in a reputation system that enables best route
path selection in the P2P network. The reputation system helps also to mitigate
(D)DoS attacks, maximize performance and increase transmission efficiency in
the network.Comment: Paper was presented at 7th international conference IBIZA 2008: On
Computer Science - Research And Applications, Poland, Kazimierz Dolny
31.01-2.02 2008; 14 pages, 5 figure
Systems and Methods for Measuring and Improving End-User Application Performance on Mobile Devices
In today's rapidly growing smartphone society, the time users are spending on their smartphones is continuing to grow and mobile applications are becoming the primary medium for providing services and content to users. With such fast paced growth in smart-phone usage, cellular carriers and internet service providers continuously upgrade their infrastructure to the latest technologies and expand their capacities to improve the performance and reliability of their network and to satisfy exploding user demand for mobile data. On the other side of the spectrum, content providers and e-commerce companies adopt the latest protocols and techniques to provide smooth and feature-rich user experiences on their applications.
To ensure a good quality of experience, monitoring how applications perform on users' devices is necessary. Often, network and content providers lack such visibility into the end-user application performance. In this dissertation, we demonstrate that having visibility into the end-user perceived performance, through system design for efficient and coordinated active and passive measurements of end-user application and network performance, is crucial for detecting, diagnosing, and addressing performance problems on mobile devices. My dissertation consists of three projects to support this statement. First, to provide such continuous monitoring on smartphones with constrained resources that operate in such a highly dynamic mobile environment, we devise efficient, adaptive, and coordinated systems, as a platform, for active and passive measurements of end-user performance. Second, using this platform and other passive data collection techniques, we conduct an in-depth user trial of mobile multipath to understand how Multipath TCP (MPTCP) performs in practice. Our measurement study reveals several limitations of MPTCP. Based on the insights gained from our measurement study, we propose two different schemes to address the identified limitations of MPTCP. Last, we show how to provide visibility into the end- user application performance for internet providers and in particular home WiFi routers by passively monitoring users' traffic and utilizing per-app models mapping various network quality of service (QoS) metrics to the application performance.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146014/1/ashnik_1.pd
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Performance evaluation of information and communications technology infrastructure for smart distribution network applications
This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Current electrical networks require secure, scalable and cost-effective Information and
Communications Technology (ICT) solutions to facilitate the novel functionalities
required by Smart Grids. Countries around the globe are investigating alternative energy sources to mitigate the current energy crisis and environmental issues experienced by many countries due to global warming, rapid growth of population, inefficient energy management, dwindling fossil fuel resources, etc. Therefore, alternative or renewable energy sources, such as wind, solar, hydro, combined heat and power, etc., are required to mitigate such a crisis and such sources will also need to be integrated in to the power grid
in a distributed manner. Such distributed energy sources are mainly connected to the
distribution networks and introduce huge challenges to the distribution network operator (DNO). Many of these challenges cannot be dealt with effectively using existing network operation mechanisms therefore the research and development of novel ICT solutions to support smart distribution network operation is required.
This research investigated suitable ICT solutions to enable the Smart Grid to tackle these challenges and proposes ICT infrastructure models that can be used for simulation studies in order to investigate cost-effective, scalable and secure solutions for the DNOs. Initially, a Quality of Service (QoS) monitoring test-bed was proposed to evaluate the performance of bandwidth intensive applications, such as smart meter data transmission. Simulation studies for different communication technologies, cellular and Power Line
Communication (PLC), were also carried out and the simulation models were verified
using experimental test results. Finally, the modelling and analysis of smart metering
infrastructure was carried out using simulation and extensive studies were performed to evaluate the data transmission rate performance for different configurations of smart meters and concentrators
The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena
The Internet is the most complex system ever created in human history.
Therefore, its dynamics and traffic unsurprisingly take on a rich variety of
complex dynamics, self-organization, and other phenomena that have been
researched for years. This paper is a review of the complex dynamics of
Internet traffic. Departing from normal treatises, we will take a view from
both the network engineering and physics perspectives showing the strengths and
weaknesses as well as insights of both. In addition, many less covered
phenomena such as traffic oscillations, large-scale effects of worm traffic,
and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex
System
Cooperation Strategies for Enhanced Connectivity at Home
WHILE AT HOME , USERS MAY EXPERIENCE A POOR I NTERNET SERVICE while being connected to their 802.11 Access Points (APs). The AP is just one component
of the Internet Gateway (GW) that generally includes a backhaul connection (ADSL, fiber,etc..) and a router providing a LAN. The root cause of performance degradation may be poor/congested wireless channel between the user and the GW or congested/bandwidth limited backhaul connection.
The latter is a serious issue for DSL users that are located far from the central office because the greater the distance the lesser the achievable physical datarate. Furthermore, the GW is one of the few devices in the home that is left always on, resulting in energy waste and electromagnetic pollution increase. This thesis proposes two strategies to enhance Internet connectivity at home by (i) creating a wireless resource sharing scheme through the federation and the coordination of neighboring GWs in order to achieve energy efficiency while avoiding congestion, (ii) exploiting different king of connectivities, i.e., the wired plus the cellular (3G/4G) connections, through the aggregation of the available bandwidth across multiple access technologies.
In order to achieve the aforementioned strategies we study and develop:
⢠A viable interference estimation technique for 802.11 BSSes that can be implemented on commodity hardware at the MAC layer, without requiring active measurements, changes in the 802.11 standard, cooperation from the wireless stations (WSs). We extend previous theoretical results on the saturation throughput in order to quantify the impact in term of throughput loss of any kind of interferer. We im- plement and extensively evaluate our estimation technique with a real testbed and with different kind of interferer, achieving always good accuracy.
⢠Two available bandwidth estimation algorithms for 802.11 BSSes that rely only on passive measurements and that account for different kind of interferers on the ISM band. This algorithms can be implemented on commodity hardware, as they require only software modifications. The first algorithm applies to intra-GW while the second one applies to inter-GW available bandwidth estimation. Indeed, we use the first algorithm to compute the metric for assessing the Wi-Fi load of a GW and the second one to compute the metric to decide whether accept incoming WSs from neighboring GWs or not. Note that in the latter case it is assumed that one or more WSs with known traffic profile are requested to relocate from one GW to another
one. We evaluate both algorithms with simulation as well as with a real test-bed for different traffic patterns, achieving high precision.
⢠A fully distributed and decentralized inter-access point protocol for federated GWs that allows to dynamically manage the associations of the wireless stations (WSs) in the federated network in order to achieve energy efficiency and offloading con- gested GWs, i.e, we keep a minimum number of GWs ON while avoiding to create congestion and real-time throughput loss. We evaluate this protocol in a federated scenario, using both simulation and a real test-bed, achieving up to 65% of energy saving in the simulated setting. We compare the energy saving achieved by our protocol against a centralized optimal scheme, obtaining close to optimal results.
⢠An application level solution that accelerates slow ADSL connections with the parallel use of cellular (3G/4G) connections. We study the feasibility and the potential performance of this scheme at scale using both extensive throughput measurement of the cellular network and trace driven analysis. We validate our solution by implementing a real test bed and evaluating it âin the wild, at several residential locations of a major European city. We test two applications: Video-on-Demand (VoD) and picture upload, obtaining remarkable throughput increase for both applications at all locations. Our implementation features a multipath scheduler which we compare to other scheduling policies as well as to transport level solution like MTCP, obtaining always better results
Performance Evaluation And Anomaly detection in Mobile BroadBand Across Europe
With the rapidly growing market for smartphones and userâs confidence for immediate
access to high-quality multimedia content, the delivery of video over wireless networks has
become a big challenge. It makes it challenging to accommodate end-users with flawless
quality of service. The growth of the smartphone market goes hand in hand with the
development of the Internet, in which current transport protocols are being re-evaluated to
deal with traffic growth. QUIC and WebRTC are new and evolving standards. The latter
is a unique and evolving standard explicitly developed to meet this demand and enable
a high-quality experience for mobile users of real-time communication services. QUIC
has been designed to reduce Web latency, integrate security features, and allow a highquality
experience for mobile users. Thus, the need to evaluate the performance of these
rising protocols in a non-systematic environment is essential to understand the behavior
of the network and provide the end user with a better multimedia delivery service. Since
most of the work in the research community is conducted in a controlled environment, we
leverage the MONROE platform to investigate the performance of QUIC and WebRTC
in real cellular networks using static and mobile nodes. During this Thesis, we conduct
measurements ofWebRTC and QUIC while making their data-sets public to the interested
experimenter. Building such data-sets is very welcomed with the research community,
opening doors to applying data science to network data-sets. The development part of the
experiments involves building Docker containers that act as QUIC and WebRTC clients.
These containers are publicly available to be used candidly or within the MONROE
platform. These key contributions span from Chapter 4 to Chapter 5 presented in Part
II of the Thesis.
We exploit data collection from MONROE to apply data science over network
data-sets, which will help identify networking problems shifting the Thesis focus from
performance evaluation to a data science problem.
Indeed, the second part of the Thesis focuses on interpretable data science. Identifying
network problems leveraging Machine Learning (ML) has gained much visibility in the
past few years, resulting in dramatically improved cellular network services. However,
critical tasks like troubleshooting cellular networks are still performed manually by experts
who monitor the network around the clock. In this context, this Thesis contributes by proposing the use of simple interpretable
ML algorithms, moving away from the current trend of high-accuracy ML algorithms
(e.g., deep learning) that do not allow interpretation (and hence understanding) of their
outcome. We prefer having lower accuracy since we consider it interesting (anomalous)
the scenarios misclassified by the ML algorithms, and we do not want to miss them by
overfitting. To this aim, we present CIAN (from Causality Inference of Anomalies in
Networks), a practical and interpretable ML methodology, which we implement in the
form of a software tool named TTrees (from Troubleshooting Trees) and compare it to
a supervised counterpart, named STress (from Supervised Trees). Both methodologies
require small volumes of data and are quick at training. Our experiments using real
data from operational commercial mobile networks e.g., sampled with MONROE probes,
show that STrees and CIAN can automatically identify and accurately classify network
anomaliesâe.g., cases for which a low network performance is not justified by operational
conditionsâtraining with just a few hundreds of data samples, hence enabling precise
troubleshooting actions. Most importantly, our experiments show that a fully automated
unsupervised approach is viable and efficient. In Part III of the Thesis which includes
Chapter 6 and 7.
In conclusion, in this Thesis, we go through a data-driven networking roller coaster,
from performance evaluating upcoming network protocols in real mobile networks to
building methodologies that help identify and classify the root cause of networking
problems, emphasizing the fact that these methodologies are easy to implement and can
be deployed in production environments.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Matteo Sereno.- Secretario: Antonio de la Oliva Delgado.- Vocal: Raquel Barco Moren
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