The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture.

Enabling stream processing for people-centric IoT based on the fog computing paradigm / Amaxilatis, Dimitrios; Akrivopoulos, Orestis; Chatzigiannakis, Ioannis; Tselios, Christos. - STAMPA. - (2018), pp. 1-8. (Intervento presentato al convegno 22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017 tenutosi a Limassol; Cyprus) [10.1109/ETFA.2017.8247674].

Enabling stream processing for people-centric IoT based on the fog computing paradigm

Chatzigiannakis, Ioannis
Writing – Original Draft Preparation
;
2018

Abstract

The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture.
2018
22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017
Electrical and Electronic Engineering; Control and Systems Engineering; Industrial and Manufacturing Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Enabling stream processing for people-centric IoT based on the fog computing paradigm / Amaxilatis, Dimitrios; Akrivopoulos, Orestis; Chatzigiannakis, Ioannis; Tselios, Christos. - STAMPA. - (2018), pp. 1-8. (Intervento presentato al convegno 22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017 tenutosi a Limassol; Cyprus) [10.1109/ETFA.2017.8247674].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1111772
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