Litcius/Paper detail

Cloud-Edge Orchestration for the Internet of Things: Architecture and AI-Powered Data Processing

Yulei Wu

2020IEEE Internet of Things Journal230 citationsDOI

Abstract

The Internet of Things (IoT) has been deeply penetrated into a wide range of important and critical sectors, including smart city, water, transportation, manufacturing, and smart factory. Massive data are being acquired from a fast growing number of IoT devices. Efficient data processing is a necessity to meet diversified and stringent requirements of many emerging IoT applications. Due to the constrained computation and storage resources, IoT devices have resorted to the powerful cloud computing to process their data. However, centralized and remote cloud computing may introduce unacceptable communication delay since its physical location is far away from IoT devices. Edge cloud has been introduced to overcome this issue by moving the cloud in closer proximity to IoT devices. The orchestration and cooperation between the cloud and the edge provides a crucial computing architecture for IoT applications. Artificial intelligence (AI) is a powerful tool to enable the intelligent orchestration in this architecture. This article first introduces such a kind of computing architecture from the perspective of IoT applications. It then investigates the state-of-the-art proposals on AI-powered cloud-edge orchestration for the IoT. Finally, a list of potential research challenges and open issues is provided and discussed, which can provide useful resources for carrying out future research in this area.

Topics & Concepts

Cloud computingOrchestrationComputer scienceEdge computingDistributed computingEnhanced Data Rates for GSM EvolutionArchitectureEdge deviceBig dataInternet of ThingsFactory (object-oriented programming)The InternetEmbedded systemTelecommunicationsWorld Wide WebOperating systemVisual artsMusicalArtProgramming languageIoT and Edge/Fog ComputingBlockchain Technology Applications and SecurityCloud Computing and Resource Management
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