Abstract

International audience; Mobile devices have usually limited capabilities in terms of computation power, battery lifetime, storage size and available bandwidth. Thus, to address these limitations and to continue supporting the ever-increasing application requirements, service providers use powerful servers in order to offer services through the cloud. However, due to latency and QoS limitations, cloud computing still does not solve all the problems of newly emerging mobile applications demands. Thus, a more recent development is to push the storage and processing capabilities to the edge of access network closer to end users, which introduce the new concept of fog computing. Fog computing is a decentralized computation framework which essentially extends cloud computing resources and services to the edge of access network [2].

Abstract

International audience; High volumes of pedestrians, cyclists and other vulnerable road users (VRUs) have much higher casualty rates per mile; not surprising given their lack of protection from an accident. In order to alleviate the problem, sensing capabilities of smartphones can be used to detect, warn and safeguard these road users. In this research we propose an infrastructure-less fog-based architecture named PV-Alert (Pedestrian-Vehicle Alert) where fog nodes process delay sensitive data obtained from smartphones for alerting pedestrians and drivers before sending the data to the cloud for further analysis. Fog computing is considered in developing the architecture since it is an emerging paradigm that has paramount of advantages for low-latency applications which demand mobility support, geo-distribution and location awareness. We have also defined an algorithm for accident prediction and alerting traffic accidents involving vehicles and pedestrians. PV-Alert can be deployed quickly since it is based only on users' smartphones and doesn't require special infrastructure. Simulation results show that the proposed architecture is able to render alerts in real time whichever the wireless communication technology used to connect smartphones with fog nodes (Wi-Fi or LTE). Moreover, analytical and performance evaluations depict that the new architecture outperforms other related architectures in terms of reliability, scalability and latency.

Abstract

The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS. Document type: Article