Evaluation of IoT stream processing at edge computing layer for semantic data enrichment

The fast development of Internet of Things (IoT) computing and technologies has prompted a decentralization of Cloud-based systems. Indeed, sending all the information from IoT devices directly to the Cloud is not a feasible option for many applications with demanding requirements on real-time respo...

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Detalles Bibliográficos
Autores: Xhafa Xhafa, Fatos|||0000-0001-6569-5497, Kilic, Burak, Krause, Paul
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/175277
Acceso en línea:https://hdl.handle.net/2117/175277
https://dx.doi.org/10.1016/j.future.2019.12.031
Access Level:acceso abierto
Palabra clave:Internet of things
Cloud computing
IoT Computing
Edge Computing
Data Stream Processing
Anomaly Detection
Data Stream Rate
Internet de les coses
Computació en núvol
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Descripción
Sumario:The fast development of Internet of Things (IoT) computing and technologies has prompted a decentralization of Cloud-based systems. Indeed, sending all the information from IoT devices directly to the Cloud is not a feasible option for many applications with demanding requirements on real-time response, low latency, energy-aware processing and security. Such decentralization has led in a few years to the proliferation of new computing layers between Cloud and IoT, known as Edge computing layer, which comprises of small computing devices (e.g. Raspberry Pi) to larger computing nodes such as Gateways, Road Side Units, Mini Clouds, MEC Servers, Fog nodes, etc. In this paper, we study the challenges of processing an IoT data stream in an Edge computing layer. By using a real life data stream set arising from a car data stream as well as a real infrastructure using Raspberry Pi and Node-Red server, we highlight the complexities of achieving real time requirements of applications based on IoT stream processing