Real-Time Data-Intensive Telematics Functionalities at the Extreme Edge of the Network: Experience with the PrEstoCloud Project

Taherizadeh, Salman; Novak, Blaž; Komatar, Marija; Grobelnik, Marko

doi:10.1109/compsac.2018.10288

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…In order to demonstrate our proposed capillary distributed computing architecture, we rely on an advanced smart application used for car automation [ 13 ]. To this end, a telematics Microservice is deployed on a Motorhome Artificial Intelligence Communication Hardware (MACH) system as the Edge node installed in the car.…”

Section: Empirical Evaluationmentioning

confidence: 99%

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A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

Taherizadeh

Stankovski

Grobelnik

2018

Sensors

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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.

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Section: Empirical Evaluationmentioning

confidence: 99%

“…An additional goal of this study is to demonstrate the feasibility of the new architecture on a smart telematics application [ 13 ]. The application involves the use of a Motorhome Artificial Intelligence Communication Hardware (MACH) [ 14 ] system, which is deployed in a vehicle.…”

Section: Introductionmentioning

confidence: 99%

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

Taherizadeh

Stankovski

Grobelnik

2018

Sensors

Self Cite

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“…It bridges the gap between real-time scheduling theory and Xen, and provides a platform for integrating a broad range of realtime and embedded systems. The performance guarantee at the software system level relies on the optimisation between application and infrastructure, e.g., CloudStorm [17] for service applications and PrEstoCloud [18] for real-time Big Data using an extension of the Fog computing paradigm to the extreme Edge of the network, real-time container scheduling [19]. However, the engineering of quality critical applications across heteronomous infrastructure for DApps is still very challenging, due to diverse programming interfaces, and the lack of effective programming methods.…”

Section: Introductionmentioning

confidence: 99%

A Trustworthy Blockchain-based Decentralised Resource Management System in the Cloud

Shi

Rong

Jaatun

2020

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)

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Quality Critical Decentralised Applications (QC-DApp) have high requirements for system performance and service quality, involve heterogeneous infrastructures (Clouds, Fogs, Edges and IoT), and rely on the trustworthy collaborations among participants of data sources and infrastructure providers to deliver their business value. The development of the QCDApp has to tackle the low-performance challenge of the current blockchain technologies due to the low collaboration efficiency among distributed peers for consensus. On the other hand, the resilience of the Cloud has enabled significant advances in software-defined storage, networking, infrastructure, and every technology; however, those rich programmabilities of infrastructure (in particular, the advances of new hardware accelerators in the infrastructures) can still not be effectively utilised for QCDApp due to lack of suitable architecture and programming model.

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The Impact of Technological Innovations on the Competitiveness of the Telematic Companies

Dadelytė

Mačiulytė-Šniukienė

2020

Science - Future of Lithuania

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Innovation is an important driver of economic progress, benefiting consumers, business and the economy as whole. However, innovation companies face high risks because innovation requires a lot of resources, and it is difficult to predict a payback period in advance. This is common for all types of innovation, but especially to technological innovation. One of the least researched technological innovations is telematics, innovative transport monitoring and control technology solutions. Those are widely applied in logistics, car-sharing platforms and the public transport sector. These innovations help to achieve the goals of the companies that buy and install them, but question what impact they have on the competitiveness of the companies that create these innovations remains a matter of debate. To fill this gap, the purpose of this article is to determine the impact of technological innovation on the competitiveness of telematics companies. In pursuit of this goal, the concepts of technological innovation and competitiveness are revealed. The definition of telematics innovation and its significance for the competitiveness of enterprises was also formed. The empirical part discusses the telematics market, provides the analysis of the main competitiveness indicators of 8 telematics companies and their changes, as well as the analysis of the research and development (R&D) costs and the impact of innovations on competitiveness. Applied research methods: a critical analysis of scientific literature, generalization, systematization of data, computation, and comparison of relative indicator, data dispersion indicator, and dynamics indicator, correlation, and regression analysis. The research reveals that creation and development innovation are related to competitiveness of telematics companies. However, excessive investment into innovation no longer generates positive return.

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Real-Time Data-Intensive Telematics Functionalities at the Extreme Edge of the Network: Experience with the PrEstoCloud Project

Cited by 3 publications

References 16 publications

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

A Trustworthy Blockchain-based Decentralised Resource Management System in the Cloud

The Impact of Technological Innovations on the Competitiveness of the Telematic Companies

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