7,112 research outputs found
Characterization of ISP Traffic: Trends, User Habits, and Access Technology Impact
In the recent years, the research community has increased its focus on network monitoring which is seen as a key tool to understand the Internet and the Internet users. Several studies have presented a deep characterization of a particular application, or a particular network, considering the point of view of either the ISP, or the Internet user. In this paper, we take a different perspective. We focus on three European countries where we have been collecting traffic for more than a year and a half through 5 vantage points with different access technologies. This humongous amount of information allows us not only to provide precise, multiple, and quantitative measurements of "What the user do with the Internet" in each country but also to identify common/uncommon patterns and habits across different countries and nations. Considering different time scales, we start presenting the trend of application popularity; then we focus our attention to a one-month long period, and further drill into a typical daily characterization of users activity. Results depict an evolving scenario due to the consolidation of new services as Video Streaming and File Hosting and to the adoption of new P2P technologies. Despite the heterogeneity of the users, some common tendencies emerge that can be leveraged by the ISPs to improve their servic
Relieving the Wireless Infrastructure: When Opportunistic Networks Meet Guaranteed Delays
Major wireless operators are nowadays facing network capacity issues in
striving to meet the growing demands of mobile users. At the same time,
3G-enabled devices increasingly benefit from ad hoc radio connectivity (e.g.,
Wi-Fi). In this context of hybrid connectivity, we propose Push-and-track, a
content dissemination framework that harnesses ad hoc communication
opportunities to minimize the load on the wireless infrastructure while
guaranteeing tight delivery delays. It achieves this through a control loop
that collects user-sent acknowledgements to determine if new copies need to be
reinjected into the network through the 3G interface. Push-and-Track includes
multiple strategies to determine how many copies of the content should be
injected, when, and to whom. The short delay-tolerance of common content, such
as news or road traffic updates, make them suitable for such a system. Based on
a realistic large-scale vehicular dataset from the city of Bologna composed of
more than 10,000 vehicles, we demonstrate that Push-and-Track consistently
meets its delivery objectives while reducing the use of the 3G network by over
90%.Comment: Accepted at IEEE WoWMoM 2011 conferenc
A survey on Human Mobility and its applications
Human Mobility has attracted attentions from different fields of studies such
as epidemic modeling, traffic engineering, traffic prediction and urban
planning. In this survey we review major characteristics of human mobility
studies including from trajectory-based studies to studies using graph and
network theory. In trajectory-based studies statistical measures such as jump
length distribution and radius of gyration are analyzed in order to investigate
how people move in their daily life, and if it is possible to model this
individual movements and make prediction based on them. Using graph in mobility
studies, helps to investigate the dynamic behavior of the system, such as
diffusion and flow in the network and makes it easier to estimate how much one
part of the network influences another by using metrics like centrality
measures. We aim to study population flow in transportation networks using
mobility data to derive models and patterns, and to develop new applications in
predicting phenomena such as congestion. Human Mobility studies with the new
generation of mobility data provided by cellular phone networks, arise new
challenges such as data storing, data representation, data analysis and
computation complexity. A comparative review of different data types used in
current tools and applications of Human Mobility studies leads us to new
approaches for dealing with mentioned challenges
Network centrality: an introduction
Centrality is a key property of complex networks that influences the behavior
of dynamical processes, like synchronization and epidemic spreading, and can
bring important information about the organization of complex systems, like our
brain and society. There are many metrics to quantify the node centrality in
networks. Here, we review the main centrality measures and discuss their main
features and limitations. The influence of network centrality on epidemic
spreading and synchronization is also pointed out in this chapter. Moreover, we
present the application of centrality measures to understand the function of
complex systems, including biological and cortical networks. Finally, we
discuss some perspectives and challenges to generalize centrality measures for
multilayer and temporal networks.Comment: Book Chapter in "From nonlinear dynamics to complex systems: A
Mathematical modeling approach" by Springe
Survivability in Time-varying Networks
Time-varying graphs are a useful model for networks with dynamic connectivity
such as vehicular networks, yet, despite their great modeling power, many
important features of time-varying graphs are still poorly understood. In this
paper, we study the survivability properties of time-varying networks against
unpredictable interruptions. We first show that the traditional definition of
survivability is not effective in time-varying networks, and propose a new
survivability framework. To evaluate the survivability of time-varying networks
under the new framework, we propose two metrics that are analogous to MaxFlow
and MinCut in static networks. We show that some fundamental
survivability-related results such as Menger's Theorem only conditionally hold
in time-varying networks. Then we analyze the complexity of computing the
proposed metrics and develop several approximation algorithms. Finally, we
conduct trace-driven simulations to demonstrate the application of our
survivability framework to the robust design of a real-world bus communication
network
New approaches for characterizing inter-contact times in opportunistic networks
Characterizing the contacts between nodes is of utmost importance when evaluating mobile opportunistic
networks. The most common characterization of inter-contact times is based on the study of the aggregate
distribution of contacts between individual pairs of nodes, assuming an homogenous network,
where contact patterns between nodes are similar. The problem with this aggregate distribution is that
it is not always representative of the individual pair distributions, especially in the short term and when
the number of nodes in the network is high. Thus, deriving results from this characterization can lead to
inaccurate performance evaluation results.
In this paper, we propose new approaches to characterize the inter-contact times distribution having a
higher representativeness and, thus, increasing the accuracy of the derived performance results. Furthermore,
these new characterizations require only a moderate number of contacts in order to be representative,
thereby allowing to perform a temporal modelization of traffic traces. This a key issue for increasing
accuracy, since real-traces can have a high variability in terms of contact patterns along time. The experiments
show that the new characterizations, compared with the established one, are more precise, even
using short time contact traces.
© 2016 Elsevier B.V. All rights reserved.Hernández Orallo, E.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2016). New approaches for characterizing inter-contact times in opportunistic networks. Ad Hoc Networks. 52:160-172. doi:10.1016/j.adhoc.2016.04.003S1601725
Web User-session Inference by Means of Clustering Techniques
This paper focuses on the definition and identification
of “Web user-sessions”, aggregations of several TCP
connections generated by the same source host. The identification
of a user-session is non trivial. Traditional approaches rely on
threshold based mechanisms. However, these techniques are very
sensitive to the value chosen for the threshold, which may be
difficult to set correctly. By applying clustering techniques, we
define a novel methodology to identify Web user-sessions without
requiring an a priori definition of threshold values. We define
a clustering based approach, we discuss pros and cons of this
approach, and we apply it to real traffic traces. The proposed
methodology is applied to artificially generated traces to evaluate
its benefits against traditional threshold based approaches. We
also analyze the characteristics of user-sessions extracted by the
clustering methodology from real traces and study their statistical
properties. Web user-sessions tend to be Poisson, but correlation
may arise during periods of network/hosts anomalous behavior
The Dark Side(-Channel) of Mobile Devices: A Survey on Network Traffic Analysis
In recent years, mobile devices (e.g., smartphones and tablets) have met an
increasing commercial success and have become a fundamental element of the
everyday life for billions of people all around the world. Mobile devices are
used not only for traditional communication activities (e.g., voice calls and
messages) but also for more advanced tasks made possible by an enormous amount
of multi-purpose applications (e.g., finance, gaming, and shopping). As a
result, those devices generate a significant network traffic (a consistent part
of the overall Internet traffic). For this reason, the research community has
been investigating security and privacy issues that are related to the network
traffic generated by mobile devices, which could be analyzed to obtain
information useful for a variety of goals (ranging from device security and
network optimization, to fine-grained user profiling).
In this paper, we review the works that contributed to the state of the art
of network traffic analysis targeting mobile devices. In particular, we present
a systematic classification of the works in the literature according to three
criteria: (i) the goal of the analysis; (ii) the point where the network
traffic is captured; and (iii) the targeted mobile platforms. In this survey,
we consider points of capturing such as Wi-Fi Access Points, software
simulation, and inside real mobile devices or emulators. For the surveyed
works, we review and compare analysis techniques, validation methods, and
achieved results. We also discuss possible countermeasures, challenges and
possible directions for future research on mobile traffic analysis and other
emerging domains (e.g., Internet of Things). We believe our survey will be a
reference work for researchers and practitioners in this research field.Comment: 55 page
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