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

Multiagent Intelligent System of Convergent Sensor Data Processing for the Smart&Safe Road

The results of monitoring and analyzing traffic accidents, fixed by an intelligent monitoring system with photoradar complexes, are considered. The system works with a network of distributed photoradar vehicle detectors for road accidents, video surveillance cameras, vehicle information and communication systems, built-in car navigation equipment and mobile communication equipment. A multiagent approach developed to address the tasks of sensor data collecting and processing. The system functionality is implemented by several agents that perform data collecting, cleaning, clustering, comparing time series, retrieving data for visualization, preparing charts and reports, performing spatial and intellectual analysis, etc. Convergent approach is the convergence of cloud, fog and mobile data processing technologies. The diagnostic system is necessary for remote maintenance of photoradar equipment. The structure of the neural network is adapted to the diagnosing problems and forecasting. The tasks of intellectual analysis and forecasting traffic accidents are solved. The hybrid fuzzy neural network is synthesized. Because of the comparison of time series of traffic accidents and time series of meteorological factors, the presence of factors to become determinants for an abnormal change in the traffic situation in controlled areas is established

SkyCDS: A resilient content delivery service based on diversified cloud storage

Cloud-based storage is a popular outsourcing solution for organizations to deliver contents to end-users. However, there is a need for contingency plans to ensure service provision when the provider either suffers outages or is going out of business. This paper presents SkyCDS: a resilient content delivery service based on a publish/subscribe overlay over diversified cloud storage. SkyCDS splits the content delivery into metadata and content storage flow layers. The metadata flow layer is based on publish-subscribe patterns for insourcing the metadata control back to content owner. The storage layer is based on dispersal information over multiple cloud locations with which organizations outsource content storage in a controlled manner. In SkyCDS, the content dispersion is performed on the publisher side and the content retrieving process on the end-user side (the subscriber), which reduces the load on the organization side only to metadata management. SkyCDS also lowers the overhead of the content dispersion and retrieving processes by taking advantage of multi-core technology. A new allocation strategy based on cloud storage diversification and failure masking mechanisms minimize side effects of temporary, permanent cloud-based service outages and vendor lock-in. We developed a SkyCDS prototype that was evaluated by using synthetic workloads and a study case with real traces. Publish/subscribe queuing patterns were evaluated by using a simulation tool based on characterized metrics taken from experimental evaluation. The evaluation revealed the feasibility of SkyCDS in terms of performance, reliability and storage space profitability. It also shows a novel way to compare the storage/delivery options through risk assessment. (C) 2015 Elsevier B.V. All rights reserved.The work presented in this paper has been partially supported by EU under the COST programme Action IC1305, Network for Sustainable Ultrascale Computing (NESUS)

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

NUMA Time Warp

It is well known that Time Warp may suffer from large usage of memory, which may hamper the efficiency of the memory hierarchy. To cope with this issue, several approaches have been devised, mostly based on the reduction of the amount of used virtual memory, e.g., by the avoidance of checkpointing and the exploitation of reverse computing. In this article we present an orthogonal solution aimed at optimizing the latency for memory access operations when running Time Warp systems on Non-Uniform Memory Access (NUMA) multi-processor/multi-core computing systems. More in detail, we provide an innovative Linux-based architecture allowing per simulation-object management of memory segments made up by disjoint sets of pages, and supporting both static and dynamic binding of the memory pages reserved for an individual object to the different NUMA nodes, depending on what worker thread is in charge of running that simulation object along a given wall-clock-time window. Our proposal not only manages the virtual pages used for the live state image of the simulation object, rather, it also copes with memory pages destined to keep the simulation object's event buffers and any recoverability data. Further, the architecture allows memory access optimization for data (messages) exchanged across the different simulation objects running on the NUMA machine. Our proposal is fully transparent to the application code, thus operating in a seamless manner. Also, a free software release of our NUMA memory manager for Time Warp has been made available within the open source ROOT-Sim simulation platform. Experimental data for an assessment of our innovative proposal are also provided in this article