7,915 research outputs found
Applications of Data Mining Techniques for Vehicular Ad hoc Networks
Due to the recent advances in vehicular ad hoc networks (VANETs), smart
applications have been incorporating the data generated from these networks to
provide quality of life services. In this paper, we have proposed taxonomy of
data mining techniques that have been applied in this domain in addition to a
classification of these techniques. Our contribution is to highlight the
research methodologies in the literature and allow for comparing among them
using different characteristics. The proposed taxonomy covers elementary data
mining techniques such as: preprocessing, outlier detection, clustering, and
classification of data. In addition, it covers centralized, distributed,
offline, and online techniques from the literature
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey
With the Internet of Things (IoT) becoming part of our daily life and our
environment, we expect rapid growth in the number of connected devices. IoT is
expected to connect billions of devices and humans to bring promising
advantages for us. With this growth, fog computing, along with its related edge
computing paradigms, such as multi-access edge computing (MEC) and cloudlet,
are seen as promising solutions for handling the large volume of
security-critical and time-sensitive data that is being produced by the IoT. In
this paper, we first provide a tutorial on fog computing and its related
computing paradigms, including their similarities and differences. Next, we
provide a taxonomy of research topics in fog computing, and through a
comprehensive survey, we summarize and categorize the efforts on fog computing
and its related computing paradigms. Finally, we provide challenges and future
directions for research in fog computing.Comment: 48 pages, 7 tables, 11 figures, 450 references. The data (categories
and features/objectives of the papers) of this survey are now available
publicly. Accepted by Elsevier Journal of Systems Architectur
Intelligent Processing in Vehicular Ad hoc Networks: a Survey
The intelligent Processing technique is more and more attractive to
researchers due to its ability to deal with key problems in Vehicular Ad hoc
networks. However, several problems in applying intelligent processing
technologies in VANETs remain open. The existing applications are
comprehensively reviewed and discussed, and classified into different
categories in this paper. Their strategies, advantages/disadvantages, and
performances are elaborated. By generalizing different tactics in various
applications related to different scenarios of VANETs and evaluating their
performances, several promising directions for future research have been
suggested.Comment: 11pages, 5 figure
Fog Computing in IoT Aided Smart Grid Transition- Requirements, Prospects, Status Quos and Challenges
Due to unfolded developments in both the IT sectors viz. Intelligent
Transportation and Information Technology contemporary Smart Grid (SG) systems
are leveraged with smart devices and entities. Such infrastructures when
bestowed with the Internet of Things (IoT) and sensor network make a universe
of objects active and online. The traditional cloud deployment succumbs to meet
the analytics and computational exigencies decentralized, dynamic cum
resource-time critical SG ecosystems. This paper synoptically inspects to what
extent the cloud computing utilities can satisfy the mission-critical
requirements of SG ecosystems and which subdomains and services call for fog
based computing archetypes. The objective of this work is to comprehend the
applicability of fog computing algorithms to interplay with the core centered
cloud computing support, thus enabling to come up with a new breed of real-time
and latency free SG services. The work also highlights the opportunities
brought by fog based SG deployments. Correspondingly, we also highlight the
challenges and research thrusts elucidated towards the viability of fog
computing for successful SG Transition.Comment: 13 Pages, 1 table, 1 Figur
Large Scale Estimation in Cyberphysical Systems using Streaming Data: a Case Study with Smartphone Traces
Controlling and analyzing cyberphysical and robotics systems is increasingly
becoming a Big Data challenge. Pushing this data to, and processing in the
cloud is more efficient than on-board processing. However, current cloud-based
solutions are not suitable for the latency requirements of these applications.
We present a new concept, Discretized Streams or D-Streams, that enables
massively scalable computations on streaming data with latencies as short as a
second.
We experiment with an implementation of D-Streams on top of the Spark
computing framework. We demonstrate the usefulness of this concept with a novel
algorithm to estimate vehicular traffic in urban networks. Our online EM
algorithm can estimate traffic on a very large city network (the San Francisco
Bay Area) by processing tens of thousands of observations per second, with a
latency of a few seconds
A Survey and Taxonomy of Urban Traffic Management: Towards Vehicular Networks
Urban Traffic Management (UTM) topics have been tackled since long time,
mainly by civil engineers and by city planners. The introduction of new
communication technologies - such as cellular systems, satellite positioning
systems and inter-vehicle communications - has significantly changed the way
researchers deal with UTM issues. In this survey, we provide a review and a
classification of how UTM has been addressed in the literature. We start from
the recent achievements of "classical" approaches to urban traffic estimation
and optimization, including methods based on the analysis of data collected by
fixed sensors (e.g., cameras and radars), as well as methods based on
information provided by mobile phones, such as Floating Car Data (FCD).
Afterwards, we discuss urban traffic optimization, presenting the most recent
works on traffic signal control and vehicle routing control. Then, after
recalling the main concepts of Vehicular Ad-Hoc Networks (VANETs), we classify
the different VANET-based approaches to UTM, according to three categories
("pure" VANETs, hybrid vehicular-sensor networks and hybrid vehicular-cellular
networks), while illustrating the major research issues for each of them. The
main objective of this survey is to provide a comprehensive view on UTM to
researchers with focus on VANETs, in order to pave the way for the design and
development of novel techniques for mitigating urban traffic problems, based on
inter-vehicle communications
Machine Learning for Wireless Communications in the Internet of Things: A Comprehensive Survey
The Internet of Things (IoT) is expected to require more effective and
efficient wireless communications than ever before. For this reason, techniques
such as spectrum sharing, dynamic spectrum access, extraction of signal
intelligence and optimized routing will soon become essential components of the
IoT wireless communication paradigm. Given that the majority of the IoT will be
composed of tiny, mobile, and energy-constrained devices, traditional
techniques based on a priori network optimization may not be suitable, since
(i) an accurate model of the environment may not be readily available in
practical scenarios; (ii) the computational requirements of traditional
optimization techniques may prove unbearable for IoT devices. To address the
above challenges, much research has been devoted to exploring the use of
machine learning to address problems in the IoT wireless communications domain.
This work provides a comprehensive survey of the state of the art in the
application of machine learning techniques to address key problems in IoT
wireless communications with an emphasis on its ad hoc networking aspect.
First, we present extensive background notions of machine learning techniques.
Then, by adopting a bottom-up approach, we examine existing work on machine
learning for the IoT at the physical, data-link and network layer of the
protocol stack. Thereafter, we discuss directions taken by the community
towards hardware implementation to ensure the feasibility of these techniques.
Additionally, before concluding, we also provide a brief discussion of the
application of machine learning in IoT beyond wireless communication. Finally,
each of these discussions is accompanied by a detailed analysis of the related
open problems and challenges.Comment: Ad Hoc Networks Journa
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Modern cyber physical systems (CPSs) has widely being used in our daily lives
because of development of information and communication technologies (ICT).With
the provision of CPSs, the security and privacy threats associated to these
systems are also increasing. Passive attacks are being used by intruders to get
access to private information of CPSs. In order to make CPSs data more secure,
certain privacy preservation strategies such as encryption, and k-anonymity
have been presented in the past. However, with the advances in CPSs
architecture, these techniques also needs certain modifications. Meanwhile,
differential privacy emerged as an efficient technique to protect CPSs data
privacy. In this paper, we present a comprehensive survey of differential
privacy techniques for CPSs. In particular, we survey the application and
implementation of differential privacy in four major applications of CPSs named
as energy systems, transportation systems, healthcare and medical systems, and
industrial Internet of things (IIoT). Furthermore, we present open issues,
challenges, and future research direction for differential privacy techniques
for CPSs. This survey can serve as basis for the development of modern
differential privacy techniques to address various problems and data privacy
scenarios of CPSs.Comment: 46 pages, 12 figure
A Survey on QoE-oriented Wireless Resources Scheduling
Future wireless systems are expected to provide a wide range of services to
more and more users. Advanced scheduling strategies thus arise not only to
perform efficient radio resource management, but also to provide fairness among
the users. On the other hand, the users' perceived quality, i.e., Quality of
Experience (QoE), is becoming one of the main drivers within the schedulers
design. In this context, this paper starts by providing a comprehension of what
is QoE and an overview of the evolution of wireless scheduling techniques.
Afterwards, a survey on the most recent QoE-based scheduling strategies for
wireless systems is presented, highlighting the application/service of the
different approaches reported in the literature, as well as the parameters that
were taken into account for QoE optimization. Therefore, this paper aims at
helping readers interested in learning the basic concepts of QoE-oriented
wireless resources scheduling, as well as getting in touch with its current
research frontier.Comment: Revised version: updated according to the most recent related
literature; added references; corrected typo
A Survey on the Security of Pervasive Online Social Networks (POSNs)
Pervasive Online Social Networks (POSNs) are the extensions of Online Social
Networks (OSNs) which facilitate connectivity irrespective of the domain and
properties of users. POSNs have been accumulated with the convergence of a
plethora of social networking platforms with a motivation of bridging their
gap. Over the last decade, OSNs have visually perceived an altogether
tremendous amount of advancement in terms of the number of users as well as
technology enablers. A single OSN is the property of an organization, which
ascertains smooth functioning of its accommodations for providing a quality
experience to their users. However, with POSNs, multiple OSNs have coalesced
through communities, circles, or only properties, which make
service-provisioning tedious and arduous to sustain. Especially, challenges
become rigorous when the focus is on the security perspective of cross-platform
OSNs, which are an integral part of POSNs. Thus, it is of utmost paramountcy to
highlight such a requirement and understand the current situation while
discussing the available state-of-the-art. With the modernization of OSNs and
convergence towards POSNs, it is compulsory to understand the impact and reach
of current solutions for enhancing the security of users as well as associated
services. This survey understands this requisite and fixates on different sets
of studies presented over the last few years and surveys them for their
applicability to POSNs...Comment: 39 Pages, 10 Figure
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