ThinGs In a Fog: System Illustration with Connected Vehicles

Rayamajhi, Anjan; Rahman, Mizanur; Kaur, Manveen; Liu, Jianwei; Chowdhury, Mashrur; Hu, Hongxin; McClendon, Jerome; Wang, Kuang-Ching; Gosain, Anjana; Martin, Jim

doi:10.1109/vtcspring.2017.8108558

Cited by 10 publications

(11 citation statements)

References 8 publications

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“…In an edge-centric CPS, the physical proximity of devices to the data source reduces the wireless communication latency, and a layered architecture increases the scalability ( 19 ). The edge-centric CPS, as shown in Figure 2 for a CV system, consists of three edge layers: (i) mobile edge (e.g., on-board sensors and computing device inside a vehicle); (ii) fixed edge (e.g., roadside transportation data infrastructure); and (iii) system edge (e.g., backend server at TMC) ( 5 ). This hierarchical cyber-physical system architecture can address complexity and scale issues of CV systems.…”

Section: Connected Vehicle Application Development Platform (Cvdep)mentioning

confidence: 99%

“…Considering a large-scale deployment of CV CPS, the concept of edge computing is introduced as the underlying computing approach ( 5 ). Edge computing has the potential benefits of enabling reduced communication latency and increased scalability.…”

mentioning

confidence: 99%

“…Such benefits are a result of bringing resources, such as storage, and computational resources, closer to the edge ( 6, 7 ). In an edge-centric CPS, the resources for communication, computation, control, and storage are placed at different edge layers (e.g., a mobile edge as a vehicle, a fixed edge as a roadside infrastructure, and a system edge as a backend server or TMC) in a CV environment ( 5 ). Therefore, a CV application can be divided into sub-applications where sub-applications run in different edge layers depending on the requirements of the application.…”

mentioning

confidence: 99%

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Development and Performance Evaluation of a Connected Vehicle Application Development Platform

Islam

Rahman

Khan

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Connected vehicle (CV) application developers need a development platform to build, test, and debug real-world CV applications, such as safety, mobility, and environmental applications, in edge-centric cyber-physical system (CPS). The objective of this paper is to develop and evaluate a scalable and secure CV application development platform (CVDeP) that enables application developers to build, test, and debug CV applications in real-time while meeting the functional requirements of any CV applications. The efficacy of the CVDeP was evaluated using two types of CV applications (one safety and one mobility application) and they were validated through field experiments at the South Carolina Connected Vehicle Testbed (SC-CVT). The analyses show that the CVDeP satisfies the functional requirements in relation to latency and throughput of the selected CV applications while maintaining the scalability and security of the platform and applications.

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Section: Connected Vehicle Application Development Platform (Cvdep)mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Development and Performance Evaluation of a Connected Vehicle Application Development Platform

Islam

Rahman

Khan

et al. 2020

Transportation Research Record: Journal of the Transportation R

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“…Layered Architecture. The key motivations for choosing the layered architecture of the testbed are to reduce data delivery delay and data loss rate, and increase throughput between diffferent edges of the CU-CVT testbed (19). DSRC provides a low-latency, high-throughput communication link from a Mobile Edge to a Fixed Edge and many applications, such as queue prediction, traffic data collection, and video monitoring, which may need computation at the Fixed Edge rather than sending the data to a System Edge.…”

Section: System Design and Prototypingmentioning

confidence: 99%

“…As there is no specific standard for device configuration and it is the early phase of equipment production, one needs to write one's own code to make it compatible with the platform. Another approach involves developing a generalized CVT distributed application services package, such as ThinGs in a Fog (TGIF) (19), to provide services, such as geo-location, messaging, HetNet and WAVE services, for application developers.…”

Section: System Deploymentmentioning

confidence: 99%

Lessons Learned from the Real-World Deployment of a Connected Vehicle Testbed

Chowdhury

Rahman

Rayamajhi

et al. 2018

Transportation Research Record: Journal of the Transportation R

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The connected vehicle (CV) system promises unprecedented safety, mobility, environmental, economic, and social benefits, which can be unlocked using the enormous amount of data shared between vehicles and infrastructure (e.g., traffic signals, centers). Real-world CV deployments, including pilot deployments, help solve technical issues and observe potential benefits, both of which support the broader adoption of the CV system. This study focused on the Clemson University Connected Vehicle Testbed (CU-CVT) with the goal of sharing the lessons learned from the CU-CVT deployment. The motivation of this study was to enhance early CV deployments with the objective of depicting the lessons learned from the CU-CVT testbed, which includes unique features to support multiple CV applications running simultaneously. The lessons learned in the CU-CVT testbed are described at three different levels: (i) the development of system architecture and prototyping in a controlled environment, (ii) the deployment of the CU-CVT testbed, and (iii) the validation of the CV application experiments in the CU-CVT. Field experiments with CV applications validated the functionalities needed for running multiple diverse CV applications simultaneously using heterogeneous wireless networking, and meeting real-time and non-real-time application requirements. The unique deployment experiences, related to heterogeneous wireless networks, real-time data aggregation, data dissemination and processing using a broker system, and data archiving with big data management tools, gained from the CU-CVT testbed, could be used to advance CV research and guide public and private agencies for the deployment of CVs in the real world.

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