Dynamic resource allocation and management in virtual networks and Clouds

127 Pages·2017·3.14 MB·English

by  Houda Jmila

Dynamic resource allocation and management in virtual
networks and Clouds
Houda Jmila
To cite this version:
Houda Jmila. Dynamic resource allocation and management in virtual networks and Clouds. Net-
working and Internet Architecture [cs.NI]. Institut National des Télécommunications, 2015. English.
￿NNT: 2015TELE0023￿. ￿tel-01316894￿
HAL Id: tel-01316894
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THESE DE DOCTORAT CONJOINT TELECOM SUDPARIS et
L’UNIVERSITE PIERRE ET MARIE CURIE

Ecole doctorale : Informatique, Télécommunications et Electronique de Paris
Présentée par
Houda JMILA

Pour obtenir le grade de
DOCTEUR DE TELECOM SUDPARIS

Dynamic resource allocation and management
in virtual networks and Clouds

Soutenue le 21 décembre 2015 devant le jury composé de :

Rapporteurs :
Pascal Lorenz Professeur Université de Haute Alsace, France.
Luis Muñoz Professeur Université de Cantabrie, Santander.
Examinateurs :
Steven Martin Professeur Université Paris 11, France.
Lila Boukhatem Mdc. HDR Université Paris 11, France.
Mourad Gueroui Mdc. HDR Université de Versailles, France.
Nadjib Ait Saadi Mdc. Dr Université Paris 12, France.
Directeur de thèse :
Djamal Zeghlache Professeur Télécom SudParis. France.

Thèse N° 2015TELE0023

JOINT THESIS BETWEEN TELECOM SUDPARIS AND UNIVERSITY OF
PARIS 6 (UPMC)

Doctoral School : Informatique, Télécommunications et Electronique de Paris
Presented by
Houda JMILA

For the degree of
DOCTEUR DE TELECOM SUDPARIS

Dynamic resource allocation and management
in virtual networks and Clouds

Defence date : 21 December 2015

Jury Members :

Reviewers :
Pascal Lorenz Professor University of Haute Alsace, France.
Luis Muñoz Professor University of Cantabria, Santander.
Examiner :
Steven Martin Professor Paris 11 University, France.
Lila Boukhatem Mdc. HDR Paris 11 University, France.
Mourad Gueroui Mdc. HDR University of Versailles, France.
Nadjib Ait Saadi Mdc. Dr Paris 12 University, France.
Thesis Supervidor :
Djamal Zeghlache Professor Télécom SudParis. France.

Thèse N° 2015TELE0023

In Honor of my grandfathers and grandmothers, I dedicate this work as a
token of my deep love.

To my parents Khemais and Zahida,
I am particularly indebted for your sincere love, your unconditional trust
and continuous support during my PhD study years. Thank you for
everything!

To my dear husband Mohamed,
I am especially thankful for your love, your understanding and your
continuous support. You gave me strengths on weak days and showed me
the sun on rainy days. Thanks for always believing in me.

To my son Mouadh,
You are my sunshine, I hope you will be proud of your mom!

To my brothers Aladain and Daly,
Thanks for always standing by my side during difficult times and for the fun
moments I have shared with you!

To all JMILA, FEHRI and IBN KHEDHER family members,
Thanks for your love, kind support and continuous encouragement!
Acknowledgement

I would like to express my deep and sincere gratitude to my
supervisor, Prof. Djamal Zeghlache for his continuous support and
constant guidance during my PhD study years in the SAMOVAR
laboratory. Thank you for everything; it was a truly great experience
working with you!

My special appreciation goes to professors Pascal Lorenz, Luis Muñoz
and Steven Martin, and to Dr. Lila Boukhatem, Dr. Mourad Gueroui
and Dr. Nadjib Ait Saadi.

I would like also to thank the staff of Telecom SudParis. Many thanks
go to all my colleagues and friends inside and outside Telecom
SudParis for the excellent and truly enjoyable ambiance.
Abstract
Cloud computing is a promising technology enabling IT resources reservation and utiliza-
tion on a pay-as-you-go manner. In addition to the traditional computing resources, cloud
tenants expect compete networking of their dedicated resources to easily deploy network
functionsandservices. TheyneedtomanageanentireVirtualNetwork (VN)orinfrastruc-
ture. Thus, Cloud providers should deploy dynamic and adaptive resource provisioning
solutions to allocate virtual networks that reflect the time-varying needs of Cloud-hosted
applications. Prior work on virtual network resource provisioning only focused on the
problem of mapping the virtual nodes and links composing a virtual network request to
the substrate network nodes and paths, known as the Virtual network embedding (VNE)
problem. Little attention was paid to the resource management of the allocated resources
to continuously meet the varying demands of embedded virtual networks and to ensure
efficient substrate resource utilization.
The aim of this thesis is to enable dynamic and preventive virtual network resources
provisioning to deal with demand fluctuation during the virtual network lifetime, and to
enhance the substrate resources usage. To reach these goals, the thesis proposes adaptive
resource allocation algorithms for evolving virtual network requests. First, we will study
in depth the extension of a virtual node, i.e. an embedded virtual node requiring more
resources, when the hosting substrate node does not have enough available resources. Sec-
ond, we will improve the previous proposal to consider the substrate network profitability.
And finally we will deal with the bandwidth demand variation in embedded virtual links.
Consequently, thefirstpartofthisthesisprovidesaheuristicalgorithmthatdealswith
virtual nodes demand fluctuations. The main idea of the algorithm is to re-allocate one or
more co-located virtual nodes from the substrate node, hosting the evolving node, to free
resources(ormakeroom)fortheevolvingnode. Inadditiontominimizingthere-allocation
cost, our proposal proposal takes into account an reduces the service interruption during
migration. The previous algorithm was extended to design a preventive re-configuration
scheme to enhance substrate network profitability. In fact, our proposal takes advantage
of the resource demand perturbation to tidy up the SN at minimum cost and disruptions.
When re-allocating virtual nodes to make room for the extending node, we shift the
1
2
most congested virtual links to less saturated substrate resources to balance the load
among the SN. Our proposal offers the best trade off between re-allocation cost and load
balancing performance. Finally, a distributed, local-view and parallel framework was
devised to handle all forms of bandwidth demand fluctuations of the embedded virtual
links. It is composed of a Controller and three algorithms running in each substrate node
in a distributed and parallel manner. The framework is based on the self-stabilization
approach, and can manage many and different forms of bandwidth demand variations
simultaneously.
Contents
List of Figures v
List of Tables vii
Acronyms viii
1 Introduction 1
1.1 The Cloud Computing paradigm . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 The Cloud service models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 The Cloud environment actors . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Resource provisioning in the NaaS model . . . . . . . . . . . . . . . . . . . 5
1.5 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6 Thesis contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.7 Thesis Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2 State of the art: Virtual Network resource provisioning 11
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Network Virtualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.1 Substrate Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.2 Virtual Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.3 Virtual Network Resource Provisioning . . . . . . . . . . . . . . . . 13
2.3 Virtual Network Embedding strategies . . . . . . . . . . . . . . . . . . . . . 14
2.3.1 Initial VNE strategies . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1.1 Problem formulation . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1.2 Overview of existing approaches . . . . . . . . . . . . . . . 17
2.3.2 Dynamic Resource Management strategies . . . . . . . . . . . . . . . 19
2.3.2.1 Management of Virtual Networks resource demand fluctu-
ation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.2.2 Management of the Substrate Network usage . . . . . . . . 26
2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3 Virtual Networks Adaptation: Node Reallocation 31
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
i