A comparitive performance analysis of GENI control framework aggregates

Master of Science Department of Electrical and Computer Engineering Caterina M. Scoglio Network researchers for a long time have been investigating ways to improve network performance and reliability by devising new protocols, services, and network architectures. For the most part, these innovative...

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Main Author: Tare, Nidhi
Format: Report
Language:English
Published: Kansas State University
Subjects:
Online Access:http://hdl.handle.net/2097/3716
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spelling ftkansassu:oai:krex.k-state.edu:2097/3716 2023-05-15T17:53:39+02:00 A comparitive performance analysis of GENI control framework aggregates Tare, Nidhi May application/pdf http://hdl.handle.net/2097/3716 en_US eng Kansas State University http://hdl.handle.net/2097/3716 GENI GpENI planetlab ORCA Computer Science (0984) Report ftkansassu 2022-03-05T18:33:03Z Master of Science Department of Electrical and Computer Engineering Caterina M. Scoglio Network researchers for a long time have been investigating ways to improve network performance and reliability by devising new protocols, services, and network architectures. For the most part, these innovative ideas are tested through simulations and emulation techniques that though yield credible results; fail to account for realistic Internet measurements values like traffic, capacity, noise, and variable workload, and network failures. Overlay networks, on the other hand have existed for a decade, but they assume the current internet architecture is not suitable for clean-slate network architecture research. Recently, the Global Environment for Network Innovations (GENI) project aims to address this issue by providing an open platform comprising of a suite of highly programmable and shareable network facilities along with its control software. The aim of this report is to introduce GENI’s key architectural concepts, its control frameworks, and how they are used for dynamic resource allocation of computing and networking resources. We mainly discuss about the architectural concepts and design goals of two aggregates, namely the BBN Open Resource Control Architecture of the (BBNORCA) of the ORCA control framework and Great Plains Environment for Network Innovations (GpENI) belonging to the PlanetLab control framework. We then describe the procedure adopted for hardware and software setup of individual aggregates. After giving an overview of the two prototypes, an analysis of the simple experiments that were conducted on each of the aggregates is presented. Based on the study and experimental results, we present a comparative analysis of control framework architectures, their relative merits and demerits, experimentation ease, virtualization technology, and its suitability for a future GENI prototype. We use metrics such as scalability, leasing overhead, oversubscription of resources, and experiment isolation for comparison. Report Orca Kansas State University: K-State Research Exchange (K-REx)
institution Open Polar
collection Kansas State University: K-State Research Exchange (K-REx)
op_collection_id ftkansassu
language English
topic GENI
GpENI
planetlab
ORCA
Computer Science (0984)
spellingShingle GENI
GpENI
planetlab
ORCA
Computer Science (0984)
Tare, Nidhi
A comparitive performance analysis of GENI control framework aggregates
topic_facet GENI
GpENI
planetlab
ORCA
Computer Science (0984)
description Master of Science Department of Electrical and Computer Engineering Caterina M. Scoglio Network researchers for a long time have been investigating ways to improve network performance and reliability by devising new protocols, services, and network architectures. For the most part, these innovative ideas are tested through simulations and emulation techniques that though yield credible results; fail to account for realistic Internet measurements values like traffic, capacity, noise, and variable workload, and network failures. Overlay networks, on the other hand have existed for a decade, but they assume the current internet architecture is not suitable for clean-slate network architecture research. Recently, the Global Environment for Network Innovations (GENI) project aims to address this issue by providing an open platform comprising of a suite of highly programmable and shareable network facilities along with its control software. The aim of this report is to introduce GENI’s key architectural concepts, its control frameworks, and how they are used for dynamic resource allocation of computing and networking resources. We mainly discuss about the architectural concepts and design goals of two aggregates, namely the BBN Open Resource Control Architecture of the (BBNORCA) of the ORCA control framework and Great Plains Environment for Network Innovations (GpENI) belonging to the PlanetLab control framework. We then describe the procedure adopted for hardware and software setup of individual aggregates. After giving an overview of the two prototypes, an analysis of the simple experiments that were conducted on each of the aggregates is presented. Based on the study and experimental results, we present a comparative analysis of control framework architectures, their relative merits and demerits, experimentation ease, virtualization technology, and its suitability for a future GENI prototype. We use metrics such as scalability, leasing overhead, oversubscription of resources, and experiment isolation for comparison.
format Report
author Tare, Nidhi
author_facet Tare, Nidhi
author_sort Tare, Nidhi
title A comparitive performance analysis of GENI control framework aggregates
title_short A comparitive performance analysis of GENI control framework aggregates
title_full A comparitive performance analysis of GENI control framework aggregates
title_fullStr A comparitive performance analysis of GENI control framework aggregates
title_full_unstemmed A comparitive performance analysis of GENI control framework aggregates
title_sort comparitive performance analysis of geni control framework aggregates
publisher Kansas State University
publishDate
url http://hdl.handle.net/2097/3716
genre Orca
genre_facet Orca
op_relation http://hdl.handle.net/2097/3716
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