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Cluster Computing
Erschienen in: Cluster Computing 2/2017

05.04.2017

JarvSis: a distributed scheduler for IoT applications

verfasst von: M. De Benedetti, F. Messina, G. Pappalardo, C. Santoro

Erschienen in: Cluster Computing | Ausgabe 2/2017

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Abstract

JarvSis is a distributed scheduler capable to automate the execution of multiple heterogeneous tasks on IoT and Robotics applications by means of a modular and adaptable software architecture. JarvSis is designed to accept pluggable modules that make it adaptable to any devices, from simple sensors to complex robots, that, in turn, expose remote interfaces, i.e. Web-API, MQTT or ROS message bus. Through JarvSis, the developer can easily configure and deploy hierarchies of control tasks running in the Cloud and in the Fog in order to interact and control IoT devices or robots that operate in the ground. Control tasks are organized in a hierarchical network on which Fog resources represent a bridge between the computational resources hosted in the Cloud, and IoT devices or robots operating in the “ground”. In such a network, the highest layer provides control and coordination, and is typically hosted in the Cloud, while the last layer is distributed in the Fog. The advantages provided by JarvSis are discussed by a detailed example in the robotic domain.
Vorheriger Artikel Collision detection for virtual environment using particle swarm optimization with adaptive cauchy mutation
Nächster Artikel A collaborative resource management for big IoT data processing in Cloud

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Fußnoten
1
e.g., a micro-controller with the needed firmware.
 
2
The list may not be exhaustive.
 
3
Here the period is intended to be not critical, thus it is treated in a best-effort way.
 
4
The needed configurations can be easily generated for each sub-area in order to represent a specific mission that must be performed by a specific robot.
 
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Metadaten
Titel
JarvSis: a distributed scheduler for IoT applications
verfasst von
M. De Benedetti
F. Messina
G. Pappalardo
C. Santoro
Publikationsdatum
05.04.2017
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 2/2017
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0836-1

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