Fault-Tolerant Network Topologies for Datacenters

A Master of Science thesis in Computer Engineering by Heba Mahmoud Helal Attia entitled, "Fault-Tolerant Network Topologies for Datacenters," submitted in May 2017. Thesis advisor is Dr. Rana Ahmed. Soft and hard copy available. Embargo expires February 08, 2018.

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Main Author: Attia, Heba Mahmoud Helal (author)
Format: doctoralThesis
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/11073/8863
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author Attia, Heba Mahmoud Helal
author_facet Attia, Heba Mahmoud Helal
author_role author
dc.contributor.none.fl_str_mv Ahmed, Rana
dc.creator.none.fl_str_mv Attia, Heba Mahmoud Helal
dc.date.none.fl_str_mv 2017-06-08T07:56:08Z
2017-06-08T07:56:08Z
2017-05
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2017.13
http://hdl.handle.net/11073/8863
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Data Center Networks
Fault-Tolerance
Throughput
Network Topology
Performance Evaluation
Mininet
Genetic Algorithm
Dcell
Computer network architectures
Fault-tolerant computing
Data centers
Management
dc.title.none.fl_str_mv Fault-Tolerant Network Topologies for Datacenters
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Computer Engineering by Heba Mahmoud Helal Attia entitled, "Fault-Tolerant Network Topologies for Datacenters," submitted in May 2017. Thesis advisor is Dr. Rana Ahmed. Soft and hard copy available. Embargo expires February 08, 2018.
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identifier_str_mv 35.232-2017.13
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oai_identifier_str oai:repository.aus.edu:11073/8863
publishDate 2017
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spelling Fault-Tolerant Network Topologies for DatacentersAttia, Heba Mahmoud HelalData Center NetworksFault-ToleranceThroughputNetwork TopologyPerformance EvaluationMininetGenetic AlgorithmDcellComputer network architecturesFault-tolerant computingData centersManagementA Master of Science thesis in Computer Engineering by Heba Mahmoud Helal Attia entitled, "Fault-Tolerant Network Topologies for Datacenters," submitted in May 2017. Thesis advisor is Dr. Rana Ahmed. Soft and hard copy available. Embargo expires February 08, 2018.Data centers are an integral part of cloud computing infrastructure to support various cloud-based services such as web search, email, social networking, distributed file systems and scientific computing. Data centers provide huge computational power and storage, reliability, availability, and cost-effective solutions needed by the cloud applications. A data center network (DCN) topology connects thousands of servers within the datacenter and to the external world. The topology is vulnerable to failures due to the presence of huge number of servers, switches and links. Several data center network topologies have been proposed and implemented; however, most of them lack the ability to recover from failures. One of the biggest challenges in DCN is to provide a graceful degradation in performance in the event of a link or server failure. Fault-tolerance in a DCN topology can be provided by adding extra hardware (switches, links) or by provisioning of multiple redundant routing paths among servers. This thesis proposes two new fault-tolerant DCN topologies derived from the standard topology. The proposed topologies, − and −, are both cost-effective and scalable. In addition, the proposed topologies enhance the overall performance (throughput and latency) of topology, and offer graceful performance degradation in the case of a link or server failure. Furthermore, we propose a new mechanism to select the optimal path between the hosts in the topology using Genetic Algorithm (GA). Performance evaluation of the proposed topologies and techniques is done through a simulation study using realistic intra-datacenter traffic models, and the results are compared with the standard topology. The comparison is done in terms of various metrics such as throughput, latency, diameter, and average shortest path length. The simulation results show that the proposed topologies outperform the standard topology due to the availability of multiple alternate shortest paths between any pair of servers, resulting in an improvement of about 5% in throughput even for a small-size network. GA algorithm for the path selection is applied to the two proposed topologies, and it is found that there is a further improvement of about 2% in the throughput of the topologies.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)Ahmed, Rana2017-06-08T07:56:08Z2017-06-08T07:56:08Z2017-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2017.13http://hdl.handle.net/11073/8863en_USoai:repository.aus.edu:11073/88632025-06-26T12:32:44Z
spellingShingle Fault-Tolerant Network Topologies for Datacenters
Attia, Heba Mahmoud Helal
Data Center Networks
Fault-Tolerance
Throughput
Network Topology
Performance Evaluation
Mininet
Genetic Algorithm
Dcell
Computer network architectures
Fault-tolerant computing
Data centers
Management
status_str publishedVersion
title Fault-Tolerant Network Topologies for Datacenters
title_full Fault-Tolerant Network Topologies for Datacenters
title_fullStr Fault-Tolerant Network Topologies for Datacenters
title_full_unstemmed Fault-Tolerant Network Topologies for Datacenters
title_short Fault-Tolerant Network Topologies for Datacenters
title_sort Fault-Tolerant Network Topologies for Datacenters
topic Data Center Networks
Fault-Tolerance
Throughput
Network Topology
Performance Evaluation
Mininet
Genetic Algorithm
Dcell
Computer network architectures
Fault-tolerant computing
Data centers
Management
url http://hdl.handle.net/11073/8863