8,820 research outputs found
Energy and Information Management of Electric Vehicular Network: A Survey
The connected vehicle paradigm empowers vehicles with the capability to
communicate with neighboring vehicles and infrastructure, shifting the role of
vehicles from a transportation tool to an intelligent service platform.
Meanwhile, the transportation electrification pushes forward the electric
vehicle (EV) commercialization to reduce the greenhouse gas emission by
petroleum combustion. The unstoppable trends of connected vehicle and EVs
transform the traditional vehicular system to an electric vehicular network
(EVN), a clean, mobile, and safe system. However, due to the mobility and
heterogeneity of the EVN, improper management of the network could result in
charging overload and data congestion. Thus, energy and information management
of the EVN should be carefully studied. In this paper, we provide a
comprehensive survey on the deployment and management of EVN considering all
three aspects of energy flow, data communication, and computation. We first
introduce the management framework of EVN. Then, research works on the EV
aggregator (AG) deployment are reviewed to provide energy and information
infrastructure for the EVN. Based on the deployed AGs, we present the research
work review on EV scheduling that includes both charging and vehicle-to-grid
(V2G) scheduling. Moreover, related works on information communication and
computing are surveyed under each scenario. Finally, we discuss open research
issues in the EVN
Fogbanks: Future Dynamic Vehicular Fog Banks for Processing, Sensing and Storage in 6G
Fixed edge processing has become a key feature of 5G networks, while playing
a key role in reducing latency, improving energy efficiency and introducing
flexible compute resource utilization on-demand with added cost savings.
Autonomous vehicles are expected to possess significantly more on-board
processing capabilities and with improved connectivity. Vehicles continue to be
used for a fraction of the day, and as such there is a potential to increase
processing capacity by utilizing these resources while vehicles are in
short-term and long-term car parks, in roads and at road intersections. Such
car parks and road segments can be transformed, through 6G networks, into
vehicular fog clusters, or Fogbanks, that can provide processing, storage and
sensing capabilities, making use of underutilized vehicular resources. We
introduce the Fogbanks concept, outline current research efforts underway in
vehicular clouds, and suggest promising directions for 6G in a world where
autonomous driving will become commonplace. Moreover, we study the processing
allocation problem in cloud-based Fogbank architecture. We solve this problem
using Mixed Integer Programming (MILP) to minimize the total power consumption
of the proposed architecture, taking into account two allocation strategies,
single allocation of tasks and distributed allocation. Finally, we describe
additional future directions needed to establish reliability, security,
virtualisation, energy efficiency, business models and standardization
Opportunistic Routing for the Vehicular Energy Network
Vehicular energy network (VEN) is a vehicular network which can transport
energy over a large geographical area by means of electric vehicles (EVs). In
the near future, an abundance of EVs, plentiful generation of the renewables,
and mature wireless energy transfer and vehicular communication technologies
will expedite the realization of VEN. To transmit energy from a source to a
destination, we need to establish energy paths, which are composed of segments
of vehicular routes, while satisfying various design objectives. In this paper,
we develop a method to construct all energy paths for a particular energy
source-destination pair, followed by some analytical results of the method. We
describe how to utilize the energy paths to develop optimization models for
different design goals and propose two solutions. We also develop a heuristic
for the power loss minimization problem. We compare the performance of the
three solution methods with artificial and real-world traffic networks and
provide a comprehensive comparison in terms of solution quality, computation
time, solvable problem size, and applicability. This paper lays the foundations
of VEN routing.Comment: 13 page
MOTIVE: Micropayments for trusted vehicular services
Increasingly, connected cars are becoming a decentralized data platform. With
greater autonomy, they have growing needs for computation and perceiving the
world around them through sensors. While todays generation of vehicles carry
all the necessary sensor data and computation on board, we envision a future
where vehicles can cooperate to increase their perception of the world beyond
their immediate view, resulting in greater safety, coordination and more
comfortable experience for their human occupants. In order for vehicles to
obtain data, compute and other services from other vehicles or road side
infrastructure, it is important to be able to make micro payments for those
services and for the services to run seamlessly despite the challenges posed by
mobility and ephemeral interactions with a dynamic set of neighboring devices.
We present MOTIVE, a trusted and decentralized framework that allows vehicles
to make peer to peer micropayments for data, compute and other services
obtained from other vehicles or road side infrastructure within radio range.
The framework utilizes distributed ledger technologies including smart
contracts to enable autonomous operation and trusted interactions between
vehicles and nearby entities
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
An Open Source Modeling Framework for Interdependent Energy-Transportation- Communication Infrastructure in Smart and Connected Communities
Infrastructure in future smart and connected communities is envisioned as an
aggregate of public services, including the energy, transportation and
communication systems, all intertwined with each other. The intrinsic
interdependency among these systems may exert underlying influence on both
design and operation of the heterogeneous infrastructures. However, few prior
studies have tapped into the interdependency among the three systems in order
to quantify their potential impacts during standard operation. In response to
this, this paper proposes an open source, flexible, integrated modeling
framework suitable for designing coupled energy, transportation, and
communication systems and for assessing the impact of their interdependencies.
First, a novel multi-level, multi-layer, multi-agent approach is proposed to
enable flexible modeling of the interconnected energy, transportation, and
communication systems. Then, for the framework's proof-of-concept, preliminary
component and system-level models for different systems are designed and
implemented using Modelica, an equation-based object-oriented modeling
language. Finally, three case studies of gradually increasing complexity are
presented (energy, energy + transportation, energy + transportation +
communication) to evaluate the interdependencies among the three systems.
Quantitative analyses show that the deviation of the average velocity on the
road can be 10.5\% and the deviation of the power draw from the grid can be 7\%
with or without considering the transportation and communication system at the
peak commute time, indicating the presence of notable interdependencies. The
proposed modeling framework also has the potential to be further extended for
various modeling purposes and use cases, such as dynamic modeling and
optimization, resilience analysis, and integrated decision making in future
connected communities
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
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
PBF: A New Privacy-Aware Billing Framework for Online Electric Vehicles with Bidirectional Auditability
Recently an online electric vehicle (OLEV) concept has been introduced, where
vehicles are propelled through the wirelessly transmitted electrical power from
the infrastructure installed under the road while moving. The absence of
secure-and-fair billing is one main hurdle to widely adopt this promising
technology. This paper introduces a secure and privacy-aware fair billing
framework for OLEV on the move through the charging plates installed under the
road. We first propose two extreme lightweight mutual authentication
mechanisms, a direct authentication and a hash chain-based authentication
between vehicles and the charging plates that can be used for different
vehicular speeds on the road. Second we propose a secure and privacy-aware
wireless power transfer on move for the vehicles with bidirectional
auditability guarantee by leveraging game-theoretic approach. Each charging
plate transfers a fixed amount of energy to the vehicle and bills the vehicle
in a privacy-aware way accordingly. Our protocol guarantees secure,
privacy-aware, and fair billing mechanism for the OLEVs while receiving
electric power from the road. Moreover our proposed framework can play a vital
role in eliminating the security and privacy challenges in the deployment of
power transfer technology to the OLEVs.Comment: 13 pages, 7 figure
Criteria for Solar Car Optimized Route Estimation
This paper gives a thorough overview of Solar Car Optimized Route Estimation
(SCORE), novel route optimization scheme for solar vehicles based on solar
irradiance and target distance. In order to conduct the optimization, both data
collection and the optimization algorithm itself have to be performed using
appropriate hardware. Here we give an insight to both stages, hardware and
software used and present some results of the SCORE system together with
certain improvements of its fusion and optimization criteria. Results and the
limited applicability of SCORE are discussed together with an overview of
future research plans and comparison with state-of-the-art solar vehicle
optimization solutions
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