Transparent Application Adjustment for Efficient and Elastic Execution in the Cloud

192 Pages·2015·8.17 MB·English

Transparent Application
Adjustment for Efficient and
Elastic Execution in the Cloud
PhD THESIS
submitted in partial fulfillment of the requirements for the degree of
Doctor of Technical Sciences
within the
Vienna PhD School of Informatics
by
Rostyslav Zabolotnyi
Registration Number 1128386
totheFacultyofInformatics
attheTUWien
Advisor: Univ.Prof. SchahramDustdar
Externalreviewers:
AdamBarker. UniversityofStAndrews,England.
FrankLeymann. UniversityofStuttgart,Germany.
Vienna,24th August,2015
RostyslavZabolotnyi SchahramDustdar
Technische Universität Wien
A-1040 Wien Karlsplatz 13 Tel. [phone] www.tuwien.ac.at

Declaration of Authorship
RostyslavZabolotnyi
Tigergasse23-2720/2,Wien,Austria
I hereby declare that I have written this Doctoral Thesis independently, that I have
completely specified the utilized sources and resources and that I have definitely marked
all parts of the work - including tables, maps and figures - which belong to other works
or to the internet, literally or extracted, by referencing the source as borrowed.
Vienna,24th August,2015
RostyslavZabolotnyi
iii

Acknowledgements
This PhD thesis defines an ultimate accomplishment of my academic research career in
the Distributed Systems Group at TU Wien. Looking back over the last four years, I can
clearly confirm that it was an interesting experience that broadened my understanding
of computer science and university life.
First,IwouldliketothankmyauntOksanaSenchukforfindingandrecommendingme
such an interesting opportunity. Likewise, I would like to thank Prof. Hannes Werthner,
Prof. Hans Tompits and Ms. Clarissa Schmid for welcoming me as a participant of the
Vienna PhD School of Informatics and helping me with any study- or research-related
issue I had. Equally, I would like to express my gratitude to Prof. Schahram Dustdar
that agreed to work with me, accepted me in the Distributed Systems Group, and guided
me through my research and studies.
Furthermore, I want to thank all my colleagues from the Distributed Systems Group
and the PhD School for the fruitful discussions, support and collaboration. Notably, I
appreciate Philipp Leitner, Waldemar Hummer, Vitaliy Liptchinsky, Benjamin Satzger,
and Alessio Gambi for the help in shaping my research and a fruitful cooperation that
developed into the results that I am presenting in this thesis. Similarly, I am thankful
to Philipp Hoenisch who served me as the good example in almost every research and
development-related activity. I am also immensely grateful to Ass. Prof. Stefan Schulte,
whose facilitation and guidance over the last two years were perhaps the main reason I
actually completed my research work at all.
My special thanks are devoted to my family and friends, particularly to Serwah Sa-
betghadam, Konstantin Selyunin, and Maryna Kostikova, who supported me emotionally,
added colors, and adventures during my stay in Vienna.
Finally, I am grateful for financial support from the Vienna PhD School of Informatics
and European Community’s Seventh Framework Programme under grant agreement
318201 (SIMPLI-CITY).
v

Abstract
Cloud computing rapidly surpassed the phase of initial adoption and quickly gains
momentum on the market of information technologies. Companies, startups and regular
users leverage the cloud to avoid infrastructure or middleware costs, to gain flexibility in
computing usage and to obtain unlimited computational or storage resources available
on demand. However, along with cloud computing’s benefits, new challenges arrived. In
order to achieve the advantages of the cloud, developers have to redesign their existing
applications and build new ones with scalability and elasticity in mind. Additionally,
as the market of cloud providers developed, two competing application development
paradigms emerged. When bringing an application to the cloud, developers have to
decide if they follow the Infrastructure as a Service model, which provides flexibility and
software architecture freedom, or the Platform as a Service model that offers a higher
level of abstraction and a simpler application development process.
This thesis addresses emerging cloud computing challenges presenting a transparent
applicationdistributionapproachbasedontheJCloudScalemiddleware. Thedescribed
cloud application development approach hides boilerplate cloud interaction code from
developers and allows focusing on the business logic of the application instead. Providing
benefitscommontoPlatformasaServicesolutions, thediscussedapproachallowskeeping
flexibility and freedom that is missing in alternatives. However, this approach brings
in a set of distinctive challenges, that are targeted in this work. To solve the issue of
transparent application code integrity and synchronization, a solution for seamless code
distribution was built. To simplify the complexity of elastic application management, a
scaling definition language based on complex event processing application architecture
was designed. Finally, targeting effective cloud resource usage, a profiling-based task
scheduling solution was proposed. Each solution and framework, presented in this thesis,
denote the steps on the ongoing road to achieve the declared goal of transparent cloud
application distribution.
Developed approaches and solutions were thoroughly validated using accomplished
user studies and performance evaluations. The obtained results show that the presented
transparent cloud application development approach is appealing to developers, increases
productivity and simplifies cloud migration or cloud application construction without
significant performance costs.
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Contents
Acknowledgements v
Abstract vii
Contents ix
List of Figures xiii
List of Tables xiv
List of Listings xv
Earlier Publications xix
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Scientific Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Structure of the Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Background 9
2.1 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.1 Definition of Cloud Computing . . . . . . . . . . . . . . . . . . . . 9
2.1.2 Elastic Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.3 Cloud Computing Service Models . . . . . . . . . . . . . . . . . . . 11
2.2 Cloud Computing Communication . . . . . . . . . . . . . . . . . . . . . . 11
2.2.1 Communication Middleware . . . . . . . . . . . . . . . . . . . . . . 12
2.2.2 Communication in the Cloud . . . . . . . . . . . . . . . . . . . . . 13
2.3 Event-Driven Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4 Aspect-Oriented Programming . . . . . . . . . . . . . . . . . . . . . . . . 15
3 Related Work 19
3.1 Related Work on Transparent Distribution Frameworks . . . . . . . . . . 19
ix
3.2 Related Work on Transparent Code Distribution . . . . . . . . . . . . . . 23
3.3 Related Work on Scaling Behavior Definition . . . . . . . . . . . . . . . . 24
3.4 Related Work on Profile-Based Task Scheduling . . . . . . . . . . . . . . . 25
4 Case Study 27
5 The JCloudScale Middleware 31
5.1 Basic Notions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.1.1 Interacting With Cloud Objects. . . . . . . . . . . . . . . . . . . . 34
5.1.2 Static Fields and Methods in Cloud Objects . . . . . . . . . . . . . 35
5.1.3 Passing Data Objects . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.1.4 Fault Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.2 Application Code Distribution Framework . . . . . . . . . . . . . . . . . . 38
5.2.1 Program Code Distribution Challenges . . . . . . . . . . . . . . . . 38
5.2.2 Code Distribution Framework Overview . . . . . . . . . . . . . . . 39
5.2.3 Missing Code Detection . . . . . . . . . . . . . . . . . . . . . . . . 40
5.2.4 Communication Middleware . . . . . . . . . . . . . . . . . . . . . . 41
5.2.5 Trusted Code Storage Location . . . . . . . . . . . . . . . . . . . . 42
5.2.6 Code Versioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.2.7 Code Caching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.2.8 Batch Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5.2.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5.3 Target Application Development Process . . . . . . . . . . . . . . . . . . . 45
5.3.1 Target Application Setup . . . . . . . . . . . . . . . . . . . . . . . 45
5.3.2 COs Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.3.3 Configuring JCloudScale . . . . . . . . . . . . . . . . . . . . . . 48
5.3.4 Development Process . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6 Scaling Behavior 53
6.1 Autonomic Elasticity via Complex Event Processing . . . . . . . . . . . . 53
6.2 Cloud Targeting and Bursting . . . . . . . . . . . . . . . . . . . . . . . . . 57
6.3 A Declarative Event-Based Scaling Policy Language . . . . . . . . . . . . 59
6.3.1 Language Design Considerations . . . . . . . . . . . . . . . . . . . 60
6.3.2 SPEEDL Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 61
6.3.3 Top-Level Language Grammar . . . . . . . . . . . . . . . . . . . . 62
6.3.4 Event-Driven Elasticity . . . . . . . . . . . . . . . . . . . . . . . . 63
6.3.5 Task Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Task Scheduling Rules . . . . . . . . . . . . . . . . . . . . . . . . . 64
Task Migration Rules . . . . . . . . . . . . . . . . . . . . . . . . . 65
6.3.6 Resource Management . . . . . . . . . . . . . . . . . . . . . . . . . 66
Scale-Up Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Scale-Down Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
6.3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69