3,885 research outputs found
Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles
We address the security of a network of Connected and Automated Vehicles
(CAVs) cooperating to navigate through a conflict area. Adversarial attacks
such as Sybil attacks can cause safety violations resulting in collisions and
traffic jams. In addition, uncooperative (but not necessarily adversarial) CAVs
can also induce similar adversarial effects on the traffic network. We propose
a decentralized resilient control and coordination scheme that mitigates the
effects of adversarial attacks and uncooperative CAVs by utilizing a trust
framework. Our trust-aware scheme can guarantee safe collision free
coordination and mitigate traffic jams. Simulation results validate the
theoretical guarantee of our proposed scheme, and demonstrate that it can
effectively mitigate adversarial effects across different traffic scenarios.Comment: Keywords: Resilient control and coordination, Cybersecurity, Safety
guaranteed coordination, Connected And Autonomous Vehicle
Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges
Participatory sensing is a powerful paradigm which takes advantage of
smartphones to collect and analyze data beyond the scale of what was previously
possible. Given that participatory sensing systems rely completely on the
users' willingness to submit up-to-date and accurate information, it is
paramount to effectively incentivize users' active and reliable participation.
In this paper, we survey existing literature on incentive mechanisms for
participatory sensing systems. In particular, we present a taxonomy of existing
incentive mechanisms for participatory sensing systems, which are subsequently
discussed in depth by comparing and contrasting different approaches. Finally,
we discuss an agenda of open research challenges in incentivizing users in
participatory sensing.Comment: Updated version, 4/25/201
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn
Integer programming based solution approaches for the train dispatching problem
Railroads face the challenge of competing with the trucking industry in a fastpaced environment. In this respect, they are working toward running freight trains on schedule and reducing travel times. The planned train schedules consist of departure and arrival times at main stations on the rail network. A detailed timetable, on the other hand, consists of the departure and arrival times of each train in each track section of its route. The train dispatching problem aims to determine detailed timetables over a rail network in order to minimize deviations from the planned schedule. We provide a new integer programming formulation for this problem based on a spacetime network; we propose heuristic algorithms to solve it and present computational results of these algorithms. Our approach includes some realistic constraints that have not been previously considered as well as all the assumptions and practical issues considered by the earlier works
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Towards a Fault-tolerant, Scheduling Methodology for Safety-critical Certified Information Systems
Today, many critical information systems have safety-critical and non-safety-critical functions executed on the same platform in order to reduce design and implementation costs. The set of safety-critical functionality is subject to certification requirements and the rest of the functionality does not need to be certified, or is certified to a lower level. The resulting mixed-criticality systems bring challenges in designing such systems, especially when the critical tasks are required to complete with a timing constraint. This paper studies a problem of scheduling a mixed-criticality system with fault tolerance. A fault-recovery technique called checkpointing is used where a program can go back to a recent checkpoint for re-execution upon errors occurred. A novel schedulability test is derived to ensure that the safety-critical tasks are completed before their deadlines and the theoretical correctness is shown
High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks
Federated edge learning (FEEL) technology for vehicular networks is
considered as a promising technology to reduce the computation workload while
keep the privacy of users. In the FEEL system, vehicles upload data to the edge
servers, which train the vehicles' data to update local models and then return
the result to vehicles to avoid sharing the original data. However, the cache
queue in the edge is limited and the channel between edge server and each
vehicle is a time varying wireless channel, which makes a challenge to select a
suitable number of vehicles to upload data to keep a stable cache queue in edge
server and maximize the learning accuracy. Moreover, selecting vehicles with
different resource statuses to update data will affect the total amount of data
involved in training, which further affects the model accuracy. In this paper,
we propose a vehicle selection scheme, which maximizes the learning accuracy
while ensuring the stability of the cache queue, where the statuses of all the
vehicles in the coverage of edge server are taken into account. The performance
of this scheme is evaluated through simulation experiments, which indicates
that our proposed scheme can perform better than the known benchmark scheme.Comment: This paper has been submitted to China Communication
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