An Elastic Middleware Platform for Concurrent and Distributed Cloud and MapReduce Simulations

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by  Pradeeban Kathiravelu

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1 Pradeeban Kathiravelu
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0 Thesis to obtain the Master of Science Degree in
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Information Systems and Computer Engineering
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: Supervisor: Doctor Lu´ıs Manuel Antunes Veiga
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Examination Committee
Chairperson: Doctor Jos´e Carlos Alves Pereira Monteiro
Supervisor: Doctor Lu´ıs Manuel Antunes Veiga
MemberoftheCommittee: Doctor Ricardo Jorge Freire Dias
September 2014

Acknowledgements
Cloud2Sim was a brain-child of Prof. Lu´ıs Manuel Antunes Veiga who proposed the topic and ac-
ceptedmyinteresttoworkonthistopic. Iwouldliketothankmysupervisorforleadingmethrough-
out the project with his creative suggestions on making the thesis better and guidance throughout
the thesis. His lectures and guidance were always motivating.
I would like to thank Prof. Jo˜ao Coelho Garcia for his motivations and inspirations. Prof. Luis
Rodrigues helped us at various occasions. I would also like to thank Prof. Johan Montelius for his
leadership and guidance, during my third semester at KTH Royal Institute of Technology. I would
like to thank all the professors who taught us at IST and KTH Royal Institute of Technology during
my master studies.
Erasmus Mundus offered us an opportunity to come from different countries and study at these
wonderful institutes. I would like to extend my thanks to the Education, Audiovisual and Culture
Executive Agency (EACEA) of the European Union, and EMDC consortium for selecting me for the
scholarship. My thanks goes to all my friends who shared the same journey with me with Erasmus
Mundus, making my studies a pleasant experience.
This work was partially supported by Erasmus Mundus Master Courses Scholarship (Category A),
provided by EACEA.
Lisboa, January 18, 2016
Pradeeban Kathiravelu

European Master in Distributed
Computing (EMDC)
ThisthesisisapartofthecurriculaoftheEuropeanMasterinDistributedComputing,acooperation
betweenKTHRoyalInstituteofTechnologyinSweden, InstitutoSuperiorT´ecnico(IST)inPortugal
and Universitat Polit`ecnica de Catalunya (UPC) in Spain. This double degree master program is
supported by the Education, Audiovisual and Culture Executive Agency (EACEA) of the European
Union.
My study track during the master studies of the two years is as follows:
First year: Instituto Superior T´ecnico, Universidade de Lisboa
Third semester: KTH Royal Institute of Technology
Fourth semester (Thesis): INESC-ID/Instituto Superior T´ecnico, Universidade de Lisboa
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To my parents and my teachers

Resumo
Ainvestigac¸˜aonocontextodaComputa¸c˜aoemNuvemenvolveumgrandenu´merodeentidades,como
utilizadores, clientes, aplicac¸˜oes, e m´aquinas virtuais. Devido ao acesso limitado e disponibilidade
vari´avel de recursos, os investigadores testam os seus prot´otipos em ambientes de simulac¸˜ao, em vez
dos ambientes reais na Nuvem. Contudo, ambientes de simula¸c˜ao nuvem actuais, como CloudSim
e EmuSim s˜ao executados sequencialmente. Um ambiente de simula¸c˜ao mais avanc¸ado poderia ser
criado estendendo-os, aproveitando as mais recentes tecnologias, bem como a disponibilidade de
computadores multi-core e os clusters nos laborat´orios de investigac¸˜ao. Embora a computac¸˜ao tenha
evolu´ıdo com a programa¸c˜ao multi-core, o paradigma MapReduce e as plataformas de middleware,
as simula¸c˜oes de escalonamento e gest˜ao de recursos na nuvem e de MapReduce ainda n˜ao exploram
estes avan¸cos. Neste trabalho, desenvolvemos o Cloud2Sim, atacando esta falta de correspondˆencia
entre simulac¸˜oes e tecnologia atual que elas tentam simular.
Propomos um simulador de nuvem, Cloud2Sim, concorrente e distribu´ıdo, estendendo o simulador
CloudSim, usando o armazenamento chave-valor em mem´oria distribu´ıda Hazelcast. Fornecemos
uma avaliac¸a˜o das implementa¸c˜oes de MapReduce no Hazelcast e Infinispan, distribuindo de forma
adaptativaaexecuc¸˜aodeumcluster, fornecendotamb´emmeiosparasimulac¸˜aodeexecuc¸˜oesMapRe-
duce. A nossa solu¸c˜ao dinˆamica escala as simula¸c˜oes de nuvens e MapReduce para v´arios n´os que
executam Hazelcast e Infinispan, com base na carga. O modelo de execuc¸˜ao distribu´ıdo e a soluc¸˜ao
de escalonamento adaptativo podem tornar-se um middleware geral para auto-scaling numa infras-
trutura multi-cliente (multi-tenanted).