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MobileTrust: Secure Knowledge Integration in VANETs
Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy
Comparative Analysis of P2P Architectures for Energy Trading and Sharing
Rising awareness and emergence of smart technologies have inspired new thinking in energy system management. Whilst integration of distributed energy resources in micro-grids (MGs) has become the technique of choice for consumers to generate their energy, it also provides a unique opportunity to explore energy trading and sharing amongst them. This paper investigates peer-to-peer (P2P) communication architectures for prosumers’ energy trading and sharing. The performances of common P2P protocols are evaluated under the stringent communication requirements of energy networks defined in IEEE 1547.3-2007. Simulation results show that the structured P2P protocol exhibits a reliability of 99.997% in peer discovery and message delivery whilst the unstructured P2P protocol yields 98%, both of which are consistent with the requirements of MG applications. These two architectures exhibit high scalability with a latency of 0.5 s at a relatively low bandwidth consumption, thus, showing promising potential in their adoption for prosumer to prosumer communication
Topology-aware GPU scheduling for learning workloads in cloud environments
Recent advances in hardware, such as systems with multiple GPUs and their availability in the cloud, are enabling deep learning in various domains including health care, autonomous vehicles, and Internet of Things. Multi-GPU systems exhibit complex connectivity among GPUs and between GPUs and CPUs. Workload schedulers must consider hardware topology and workload communication requirements in order to allocate CPU and GPU resources for optimal execution time and improved utilization in shared cloud environments.
This paper presents a new topology-aware workload placement strategy to schedule deep learning jobs on multi-GPU systems. The placement strategy is evaluated with a prototype on a Power8 machine with Tesla P100 cards, showing speedups of up to ≈1.30x compared to state-of-the-art strategies; the proposed algorithm achieves this result by allocating GPUs that satisfy workload requirements while preventing interference. Additionally, a large-scale simulation shows that the proposed strategy provides higher resource utilization and performance in cloud systems.This project is supported by the IBM/BSC Technology Center for Supercomputing
collaboration agreement. It has also received funding from the European Research Council (ERC) under the European Union’s Horizon
2020 research and innovation programme (grant agreement No 639595). It is
also partially supported by the Ministry of Economy of Spain under contract
TIN2015-65316-P and Generalitat de Catalunya under contract 2014SGR1051,
by the ICREA Academia program, and by the BSC-CNS Severo Ochoa program
(SEV-2015-0493). We thank our IBM Research colleagues Alaa Youssef
and Asser Tantawi for the valuable discussions. We also thank SC17 committee
member Blair Bethwaite of Monash University for his constructive feedback on the earlier drafts of this paper.Peer ReviewedPostprint (published version
Robotics software frameworks for multi-agent robotic systems development
Robotics is an area of research in which the paradigm of Multi-Agent Systems (MAS) can prove to be highly
useful. Multi-Agent Systems come in the form of cooperative robots in a team, sensor networks based on
mobile robots, and robots in Intelligent Environments, to name but a few. However, the development
of Multi-Agent Robotic Systems (MARS) still presents major challenges. Over the past decade, a high
number of Robotics Software Frameworks (RSFs) have appeared which propose some solutions to the
most recurrent problems in robotics. Some of these frameworks, such as ROS, YARP, OROCOS, ORCA,
Open-RTM, and Open-RDK, possess certain characteristics and provide the basic infrastructure necessary
for the development of MARS. The contribution of this work is the identification of such characteristics
as well as the analysis of these frameworks in comparison with the general-purpose Multi-Agent System
Frameworks (MASFs), such as JADE and Mobile-C.Ministerio de Ciencia e Innovación TEC2009-10639-C04-02Junta de Andalucía P06-TIC-2298Junta de Andalucía P08-TIC-0386
Performance analysis of cloud-based cve communication architecture in comparison with the traditional client server, p2p and hybrid models
Gital et al. (2014) proposed a cloud based
communication architecture for improving efficiency of
collaborative virtual environment (CVE) systems in
terms of Scalability and Consistency requirements. This
paper evaluates the performance of the proposed CVE
architecture. The metrics use for the evaluation is
response time. We compare the cloud-based architecture
to the traditional client server and peer-2–peer (P2P)
architecture. The comparison was implemented in the
CVE systems. The comparative simulation analysis of
the results suggested that the CVE architecture based on
cloud computing can significantly improve the
performance of the CVE system
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