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Cluster Computing
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19-04-2017

A collaborative resource management for big IoT data processing in Cloud

Author: Abdulhameed Alelaiwi

Published in: Cluster Computing | Issue 2/2017

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Abstract

These days, handling large amounts of data generated from Internet of Things (IoT) applications in the Cloud has turned into a powerful solution for fulfilling Quality of Service requests from clients. However, to save on costs, the union of cloud providers, known as a cloud confederation, can be a promising methodology because this organization helps cloud suppliers to overcome the restrictions of physical assets in handling Big IoT Data. Nonetheless, the key challenge is to discover appropriate cloud collaborators to form a confederation that will achieve the required level of services characterized in service level agreements. In this paper, to execute heterogeneous Big IoT Data handling demands from clients, we build a cloud confederation model that determines ideal choices for target cloud providers. In addition, we present a multi-objective (MO) optimization model of collaborator selection among different clouds. To solve the MO optimization model, a general structure for a multi-objective genetic algorithm is also developed. The proposed model is tested through various test assessments.
previous article JarvSis: a distributed scheduler for IoT applications
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Metadata
Title
A collaborative resource management for big IoT data processing in Cloud
Author
Abdulhameed Alelaiwi
Publication date
19-04-2017
Publisher
Springer US
Published in
Cluster Computing / Issue 2/2017
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0839-y

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JarvSis: a distributed scheduler for IoT applications

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