The large volume of data generated by Internet of Things (IoT) devices at the network edge poses significant challenges. Indeed, centralized cloud platforms struggle to manage this data flow due to issues such as latency, high bandwidth usage, and scalability problems. To address these challenges, the edge-cloud continuum has emerged as a powerful computing model that combines the strengths of edge and cloud computing, enabling data to be processed closer to its source while leveraging cloud resources for resource-intensive tasks. However, the wide adoption of edge-cloud environments is hindered by the lack of shared standards across different platforms and vendors, resulting in highly platform-specific applications. Although major cloud service providers are developing bridging and cloud services, the absence of common standards hinders communication and integration between platforms. This paper introduces a new modeling framework designed to enable developers to define applications for execution across the edge-cloud continuum in an abstract manner, independent of the deployment platform. The framework assists in identifying suitable deployment configurations and optimal service selection, ensuring that quality of service (QoS) requirements are met and supporting the development of flexible and scalable applications for seamless integration across the continuum. To demonstrate the effectiveness of this approach and how the framework facilitates the development of applications within the edge-cloud continuum, we present a use case in the domain of smart cities.

Developing Cross-Platform and Fast-Responsive Applications on the Edge-Cloud Continuum

Andrea Vinci
2024

Abstract

The large volume of data generated by Internet of Things (IoT) devices at the network edge poses significant challenges. Indeed, centralized cloud platforms struggle to manage this data flow due to issues such as latency, high bandwidth usage, and scalability problems. To address these challenges, the edge-cloud continuum has emerged as a powerful computing model that combines the strengths of edge and cloud computing, enabling data to be processed closer to its source while leveraging cloud resources for resource-intensive tasks. However, the wide adoption of edge-cloud environments is hindered by the lack of shared standards across different platforms and vendors, resulting in highly platform-specific applications. Although major cloud service providers are developing bridging and cloud services, the absence of common standards hinders communication and integration between platforms. This paper introduces a new modeling framework designed to enable developers to define applications for execution across the edge-cloud continuum in an abstract manner, independent of the deployment platform. The framework assists in identifying suitable deployment configurations and optimal service selection, ensuring that quality of service (QoS) requirements are met and supporting the development of flexible and scalable applications for seamless integration across the continuum. To demonstrate the effectiveness of this approach and how the framework facilitates the development of applications within the edge-cloud continuum, we present a use case in the domain of smart cities.
2024
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Wireless communication,Cloud computing,Smart cities,Scalability,Computational modeling,Quality of service,Prediction algorithms,Real-time systems,Internet of Things,Standards,Edge-cloud continuum,Service composition,Abstract design,Smart cities,Requirements analysis,Platform interoperability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/522124
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