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Lookup NU author(s): Professor Raj Ranjan
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2016 Elsevier Inc. In this paper, we present a framework for resource management of Streaming Data Analytics Flows (SDAF). Using advanced techniques in control and optimization theory, we design an adaptive control system tailored to the data ingestion, analytics, and storage layers of the SDAF that is able to continuously detect and self-adapt to workload changes for meeting the users' service level objectives. Our experiments based on a real-world SDAF show that, the proposed control scheme is able to reduce the deviation from desired utilization of resources by up to 48% compared to existing techniques.
Author(s): Khoshkbarforoushha A, Khosravian A, Ranjan R
Publication type: Article
Publication status: Published
Journal: Journal of Computer and System Sciences
Print publication date: 01/11/2017
Online publication date: 29/11/2016
Acceptance date: 07/11/2016
Date deposited: 20/08/2017
ISSN (print): 0022-0000
ISSN (electronic): 1090-2724
Publisher: Academic Press Inc.
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