Cost-effective traffic scheduling for Cloud resource management

Cloud resource management experienced massive strategy development throughout recent years. A traffic scheduling pattern becomes more significant in Cloud for adapting heterogeneous processing demands. We present priority-based traffic scheduling for downlink resource management aims to sustain Qual...

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Main Authors: Shareef, Zayd Ashraf Najeeb, Hussin, Masnida, Abdullah, Azizol, Muhammed, Abdullah
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Online Access:http://psasir.upm.edu.my/id/eprint/57676/1/Cost-effective%20traffic%20scheduling%20for%20Cloud%20resource%20management.pdf
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author Shareef, Zayd Ashraf Najeeb
Hussin, Masnida
Abdullah, Azizol
Muhammed, Abdullah
author_facet Shareef, Zayd Ashraf Najeeb
Hussin, Masnida
Abdullah, Azizol
Muhammed, Abdullah
author_sort Shareef, Zayd Ashraf Najeeb
collection UPM
description Cloud resource management experienced massive strategy development throughout recent years. A traffic scheduling pattern becomes more significant in Cloud for adapting heterogeneous processing demands. We present priority-based traffic scheduling for downlink resource management aims to sustain Quality of Services (QoS) in Cloud which provide Cost-Effective Best Effort service (CEBE). Our traffic scheduling embraces two main functions are priority assignment and resource bandwidth allocation. Specifically, we leverage prioritization for several downlink services, and then dynamically allocate suitable bandwidth for improving accessibility while providing efficient communication cost. Our simulation results illustrate that priority-based traffic scheduling has more substantial performance in terms of throughput and delay than others.
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spelling upm.eprints-576762017-10-25T02:29:09Z http://psasir.upm.edu.my/id/eprint/57676/ Cost-effective traffic scheduling for Cloud resource management Shareef, Zayd Ashraf Najeeb Hussin, Masnida Abdullah, Azizol Muhammed, Abdullah Cloud resource management experienced massive strategy development throughout recent years. A traffic scheduling pattern becomes more significant in Cloud for adapting heterogeneous processing demands. We present priority-based traffic scheduling for downlink resource management aims to sustain Quality of Services (QoS) in Cloud which provide Cost-Effective Best Effort service (CEBE). Our traffic scheduling embraces two main functions are priority assignment and resource bandwidth allocation. Specifically, we leverage prioritization for several downlink services, and then dynamically allocate suitable bandwidth for improving accessibility while providing efficient communication cost. Our simulation results illustrate that priority-based traffic scheduling has more substantial performance in terms of throughput and delay than others. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57676/1/Cost-effective%20traffic%20scheduling%20for%20Cloud%20resource%20management.pdf Shareef, Zayd Ashraf Najeeb and Hussin, Masnida and Abdullah, Azizol and Muhammed, Abdullah (2015) Cost-effective traffic scheduling for Cloud resource management. In: 2015 IEEE Student Conference on Research and Development (SCOReD), 13-14 Dec. 2015, Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. (pp. 189-194). 10.1109/SCORED.2015.7449300
spellingShingle Shareef, Zayd Ashraf Najeeb
Hussin, Masnida
Abdullah, Azizol
Muhammed, Abdullah
Cost-effective traffic scheduling for Cloud resource management
title Cost-effective traffic scheduling for Cloud resource management
title_full Cost-effective traffic scheduling for Cloud resource management
title_fullStr Cost-effective traffic scheduling for Cloud resource management
title_full_unstemmed Cost-effective traffic scheduling for Cloud resource management
title_short Cost-effective traffic scheduling for Cloud resource management
title_sort cost effective traffic scheduling for cloud resource management
url http://psasir.upm.edu.my/id/eprint/57676/1/Cost-effective%20traffic%20scheduling%20for%20Cloud%20resource%20management.pdf
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