Information Technology T E R Z O (cid:127) M O S S U C Cloud Computing with e-Science Applications C A The amount of data in everyday life has been exploding. This data increase has been especially significant in scientific fields, where substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how cloud computing can improve data management in data-heavy fields such as bioinformatics, earth science, and computer science. C l o The book begins with an overview of cloud models supplied by the u d National Institute of Standards and Technology (NIST), and then: C o (cid:127) Discusses the challenges imposed by big data on scientific data m infrastructures, including security and trust issues p u (cid:127) Covers vulnerabilities such as data theft or loss, privacy concerns, t i infected applications, threats in virtualization, and cross-virtual n machine attack g (cid:127) Describes the implementation of workflows in clouds, proposing an w architecture composed of two layers—platform and application i t h (cid:127) Details infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) solutions based on public, private, e - and hybrid cloud computing models S c Cloud Computing (cid:127) Demonstrates how cloud computing aids in resource control, vertical i e and horizontal scalability, interoperability, and adaptive scheduling n c e Featuring significant contributions from research centers, universities, A and industries worldwide, Cloud Computing with e-Science Applications w i t h p presents innovative cloud migration methodologies applicable to a variety of p fields where large data sets are produced. The book provides the scientific li e-Science Applications c community with an essential reference for moving applications to the cloud. a t i o n s EDITED BY OLIVIER TERZO (cid:127) LORENZO MOSSUCCA K20498 Cloud Computing with e-Science Applications Cloud Computing with e-Science Applications EDITED BY OLIVIER TERZO ISMB, TURIN, ITALY LORENZO MOSSUCCA ISMB, TURIN, ITALY Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2015 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Version Date: 20141212 International Standard Book Number-13: 978-1-4665-9116-5 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents Preface ....................................................................................................................vii Acknowledgments ..............................................................................................xiii About the Editors ..................................................................................................xv List of Contributors ............................................................................................xvii 1 Evaluation Criteria to Run Scientific Applications in the Cloud .........1 Eduardo Roloff, Alexandre da Silva Carissimi, and Philippe Olivier Alexandre Navaux 2 Cloud-Based Infrastructure for Data-Intensive e-Science Applications: Requirements and Architecture .......................................17 Yuri Demchenko, Canh Ngo, Paola Grosso, Cees de Laat, and Peter Membrey 3 Securing Cloud Data ....................................................................................41 Sushmita Ruj and Rajat Saxena 4 Adaptive Execution of Scientific Workflow Applications on Clouds .......................................................................................................73 Rodrigo N. Calheiros, Henry Kasim, Terence Hung, Xiaorong Li, Sifei Lu, Long Wang, Henry Palit, Gary Lee, Tuan Ngo, and Rajkumar Buyya 5 Migrating e-Science Applications to the Cloud: Methodology and Evaluation .....................................................................89 Steve Strauch, Vasilios Andrikopoulos, Dimka Karastoyanova, and Karolina Vukojevic-Haupt 6 Closing the Gap between Cloud Providers and Scientific Users .....115 David Susa, Harold Castro, and Mario Villamizar 7 Assembling Cloud-Based Geographic Information Systems: A Pragmatic Approach Using Off-the-Shelf Components.................141 Muhammad Akmal, Ian Allison, and Horacio González–Vélez 8 HCloud, a Healthcare-Oriented Cloud System with Improved Efficiency in Biomedical Data Processing ................163 Ye Li, Chenguang He, Xiaomao Fan, Xucan Huang, and Yunpeng Cai v vi Contents 9 RPig: Concise Programming Framework by Integrating R with Pig for Big Data Analytics ...............................................................193 MingXue Wang and Sidath B. Handurukande 10 AutoDock Gateway for Molecular Docking Simulations in Cloud Systems ........................................................................................217 Zoltán Farkas, Péter Kacsuk, Tamás Kiss, Péter Borsody, Ákos Hajnal, Ákos Balaskó, and Krisztián Karóczkai 11 SaaS Clouds Supporting Biology and Medicine ..................................237 Philip Church, Andrzej Goscinski, Adam Wong, and Zahir Tari 12 Energy-Aware Policies in Ubiquitous Computing Facilities .............267 Marina Zapater, Patricia Arroba, José Luis Ayala Rodrigo, Katzalin Olcoz Herrero, and José Manuel Moya Fernandez Preface The interest in cloud computing in both industry and research domains is continuously increasing to address new challenges of data management, com- putational requirements, and flexibility based on needs of scientific commu- nities, such as custom software environments and architectures. It provides cloud platforms in which users interact with applications remotely over the Internet, bringing several advantages for sharing data, for both applications and end users. Cloud computing provides everything: computing power, computing infrastructure, applications, business processes, storage, and interfaces, and can provide services wherever and whenever needed. Cloud computing provides four essential characteristics: elasticity; scal- ability; dynamic provisioning of applications, storage, and resources; and billing and metering of service usage in a pay-as-you-go model. This flexibil- ity of management and resource optimization is also what attracts the main scientific communities to migrate their applications to the cloud. Scientific applications often are based on access to large legacy data sets and application software libraries. Usually, these applications run in dedicated high performance computing (HPC) centers with a low-latency interconnec- tion. The main cloud features, such as customized environments, flexibility, and elasticity, could provide significant benefits. Since every day the amount of data is exploding, this book describes how cloud computing technology can help such scientific communities as bio- informatics, earth science, and many others, especially in scientific domains where large data sets are produced. Data in more scenarios must be captured, communicated, aggregated, stored, and analyzed, which opens new chal- lenges in terms of tool development for data and resource management, such as a federation of cloud infrastructures and automatic discovery of services. Cloud computing has become a platform for scalable services and deliv- ery in the field of services computing. Our intention is to put the empha- sis on scientific applications using solutions based on cloud computing models—public, private, and hybrid—with innovative methods, including data capture, storage, sharing, analysis, and visualization for scientific algo- rithms needed for a variety of fields. The intended audience includes those who work in industry, students, professors, and researchers from informa- tion technology, computer science, computer engineering, bioinformatics, science, and business fields. Actually, applications migration in the cloud is common, but a deep analy- sis is important to focus on such main aspects as security, privacy, flexibility, resource optimization, and energy consumption. This book has 12 chapters; the first two are on exposing a proposal strategy to move applications in the cloud. The other chapters are a selection of some vii viii Preface applications used on the cloud, including simulations on public transport, biological analysis, geographic information system (GIS) applications, and more. Various chapters come from research centers, universities, and indus- tries worldwide: Singapore, Australia, China, Hong Kong, India, Brazil, Colombia, the Netherlands, Germany, the United Kingdom, Hungary, Spain, and Ireland. All contributions are significant; most of the research leading to results has received funding from European and regional projects. After a brief overview of cloud models provided by the National Institute of Standards and Technology (NIST), Chapter 1 presents several criteria to meet user requirements in e-science fields. The cloud computing model has many possible combinations; the public cloud offers an alternative to avoid the up-front cost of buying dedicated hardware. Preliminary analysis of user requirements using specific criteria will be a strong help for users for the development of e-science services in the cloud. Chapter 2 discusses the challenges that are imposed by big data on sci- entific data infrastructures. A definition of big data is shown, presenting the main application fields and its characteristics: volume, velocity, variety, value, and veracity. After identifying research infrastructure requirements, an e-science data infrastructure is introduced using cloud technology to answer future big data requirements. This chapter focuses on security and trust issues in handling data and summarizes specific requirements to access data. Requirements are defined by the European Research Area (ERA) for infrastructure facility, data-processing and management functionalities, access control, and security. One of the important aspects in the cloud is certainly security due to the use of personal and sensitive information, especially derived mainly by social n etwork and health information. Chapter 3 presents a set of impor- tant vulnerability issues, such as data theft or loss, privacy issues, infected applications, threats in virtualization, and cross-virtual machine attack. Many techniques are used to protect against cloud service providers, such as homomorphic encryption, access control using attributes based on encryp- tion, and data auditing through provable data possession and proofs of irretrievability. The chapter underlines points that are still open, such as security in the mobile cloud, distributed data auditing for clouds, and secure multiparty computation on the cloud. Many e-science applications can be modeled as workflow applications, defined as a set of tasks dependent on each other. Cloud technology and platforms are a possible solution for hosting these applications. Chapter 4 discusses implementation aspects for execution of workflows in clouds. The proposal architecture is composed of two layers: platform and application. The first one, described as scientific workflow, enables operations such as dynamic resource provisioning, automatic scheduling of applications, fault tolerance, security, and privacy in data access. The second one defines data analytic applications enabling simulation of the public transport system of Singapore and the effect of unusual events in its network. This application