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1. Energy-Efficiency Models for Resource Provisioning and Application Migration in Clouds

Author

Adrian Muresan, Luis Rodero-Merino, Frédéric Desprez, and Eddy Caron

Subjects
World Wide Web, Engineering, Software, Open source, business.industry, Cloud testing, Provisioning, Cloud computing, Load balancing (computing), business, Data science, Popularity, Scaling
Abstract

Over the past years, the Cloud phenomenon had an impressive increase in popularity in both the software industry and research worlds. The most interesting feature that Cloud Computing brings, from a Cloud client's point of view, is the on-demand resource provisioning model. This allows Cloud client platforms to be scaled up in order to accommodate more incoming clients and to scale down when the platform has unused resources, and this can all be done while the platform is running. As a result, the physical resources are used more efficiently and the Cloud client saves expenses. Achieving the above mentioned is not trivial and is done by leveraging more direct functionalities that Clouds provide. Three of these key functionalities are automatic scaling, load balancing and monitoring. They represent the focus of the current work. This report is divided into three main parts, one for each of the three main topics of interest: auto-scaling, load balancing and monitoring. We detail each of the three topics and present details on their presence and implementation in the commercial, open-source and research worlds. Among the commercial Cloud platform providers we have focused on Amazon EC2, Microsoft Azure, GoGrid and RackSpace. From the open-source initiatives we have focused our attention on Nimbus, Eucalyptus and OpenNebula. We have also detailed endeavours in the research world that are relevant to the topic of interest and are not connected to any of the Cloud providers. By studying this report, the reader will be able to understand the role that each of the three Cloud features plays for a Cloud client, will understand their inner workings and will be aware of the state-of-the-art available in current commercial and open-source Cloud platforms.

Published
2017
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2. Using clouds to scale grid resources: An economic model

Author

Adrian Muresan, Eddy Caron, Luis Rodero-Merino, Frédéric Desprez, Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Computer Networks and Communications, Computer science, Distributed computing, Cloud computing, 02 engineering and technology, computer.software_genre, DIET, Task (project management), Resource (project management), 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], Informática, Telecomunicaciones, business.industry, 020206 networking & telecommunications, Grid, Hardware and Architecture, Virtual machine, Middleware, Scalability, 020201 artificial intelligence & image processing, Economic model, business, Cloud, computer, Software
Abstract

Infrastructure as a Service clouds are a flexible and fast way to obtain (virtual) resources as demand varies. Grids, on the other hand, are middleware platforms able to combine resources from different administrative domains for task execution. Clouds can be used by grids as providers of devices such as virtual machines, so they only use the resources they need. But this requires grids to be able to decide when to allocate and release those resources. Here we introduce and analyze by simulations an economic mechanism (a) to set resource prices and (b) resolve when to scale resources depending on the users’ demand. This system has a strong emphasis on fairness, so no user hinders the execution of other users’ tasks by getting too many resources. Our simulator is based on the well-known GridSim software for grid simulation, which we expand to simulate infrastructure clouds. The results show how the proposed system can successfully adapt the amount of allocated resources to the demand, while at the same time ensuring that resources are fairly shared among users.

Published
2012
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3. Building Safe PaaS Clouds: a Survey on Security in Multitenant Software Platforms

Author

Eddy Caron, Frédéric Desprez, Luis M. Vaquero, Adrian Muresan, Luis Rodero-Merino, Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Hewlett Packard Research Labs (HP Labs), Hewlett-Packard, École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
General Computer Science, Java, Computer science, Cloud computing, 02 engineering and technology, Computer security, computer.software_genre, Software, 0202 electrical engineering, electronic engineering, information engineering, Code (cryptography), Multitenancy, PaaS, Container, computer.programming_language, JavaBeans, business.industry, Hosting environment, 020207 software engineering, NET, Container (abstract data type), Security, 020201 artificial intelligence & image processing, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, Law, computer, Cloud
Abstract

International audience; This paper surveys the risks brought by multitenancy in software platforms, along with the most prominent solutions proposed to address them. A multitenant platform hosts and executes software from several users (tenants). The platform must ensure that no malicious or faulty code from any tenant can interfere with the normal execution of other users' code or with the platform itself. This security requirement is specially relevant in Platform-as-a-Service (PaaS) clouds. PaaS clouds offer an execution environment based on some software platform. Unless PaaS systems are deemed as safe environments users will be reluctant to trust them to run any relevant application. This requires to take into account how multitenancy is handled by the software platform used as the basis of the PaaS offer. This survey focuses on two technologies that are or will be the platform-of-choice in many PaaS clouds: Java and .NET. We describe the security mechanisms they provide, study their limitations as multitenant platforms and analyze the research works that try to solve those limitations. We include in this analysis some standard container technologies (such as Enterprise Java Beans) that can be used to standardize the hosting environment of PaaS clouds. Also we include a brief discussion of Operating Systems (OSs) traditional security capacities and why OSs are unlikely to be chosen as the basis of PaaS offers. Finally, we describe some research initiatives that reinforce security by monitoring the execution of untrusted code, whose results can be of interest in multitenant systems.

Published
2012
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4. Budget Constrained Resource Allocation for Non-deterministic Workflows on an IaaS Cloud

Author

Eddy Caron, Frédéric Desprez, Frédéric Suter, and Adrian Muresan

Subjects
Workflow, Computer science, business.industry, Distributed computing, Resource allocation, Cloud computing, Provisioning, business, Budget constraint, Workflow management system, Workflow technology, Scheduling (computing)
Abstract

Many scientific applications are described through workflow structures. Due to the increasing level of parallelism offered by modern computing infrastructures, workflow applications now have to be composed not only of sequential programs, but also of parallel ones. Cloud platforms bring on-demand resource provisioning and pay-as-you-go billing model. Then the execution of a workflow corresponds to a certain budget. The current work addresses the problem of resource allocation for non-deterministic workflows under budget constraints. We present a way of transforming the initial problem into sub-problems that have been studied before. We propose two new allocation algorithms that are capable of determining resource allocations under budget constraints and we present ways of using them to address the problem at hand.

Published
2012
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5. Pattern Matching Based Forecast of Non-periodic Repetitive Behavior for Cloud Clients

Author

Frédéric Desprez, Eddy Caron, Adrian Muresan, Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Computer Networks and Communications, Computer science, business.industry, 020206 networking & telecommunications, Workload, Cloud computing, 02 engineering and technology, Cloud user, computer.software_genre, Workload prediction, Repetitive behavior, Resource (project management), Hardware and Architecture, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Data mining, Pattern matching, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, Scaling, computer, Software, Information Systems
Abstract

International audience; The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. As a result, the question of efficient resource scaling arises. Prediction is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose an approach to the problem of workload prediction based on identifying similar past occurrences of the current short-term workload history. We present in detail the Cloud client resource auto-scaling algorithm that uses the above approach to help when scaling decisions are made, as well as experimental results by using real-world Cloud client application traces. We also present an overall evaluation of this approach , its potential and usefulness for enabling efficient auto-scaling of Cloud user resources.

Published
2011
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6. Auto-scaling, load balancing and monitoring in commercial and open-source clouds

Author

Eddy Caron, Frédéric Desprez, Luis Rodero-Merino, Adrian Muresan, Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Ethernet, business.industry, Computer science, Pipeline (computing), Node (networking), InfiniBand, 020206 networking & telecommunications, Cloud computing, 02 engineering and technology, computer.software_genre, Supercomputer, Virtual machine, 0202 electrical engineering, electronic engineering, information engineering, Benchmark (computing), Operating system, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, computer
Abstract

International audience; Over the past years, the Cloud phenomenon had an impressive increase in popularity in both the software industry and research worlds. The most interesting feature that Cloud Computing brings, from a Cloud client's point of view, is the on-demand resource provisioning model. This allows Cloud client platforms to be scaled up in order to accommodate more incoming clients and to scale down when the platform has unused resources, and this can all be done while the platform is running. As a result, the physical resources are used more efficiently and the Cloud client saves expenses. Achieving the above mentioned is not trivial and is done by leveraging more direct functionalities that Clouds provide. Three of these key functionalities are automatic scaling, load balancing and monitoring. They represent the focus of the current work. This report is divided into three main parts, one for each of the three main topics of interest: auto-scaling, load balancing and monitoring. We detail each of the three topics and present details on their presence and implementation in the commercial, open-source and research worlds. Among the commercial Cloud platform providers we have focused on Amazon EC2, Microsoft Azure, GoGrid and RackSpace. From the open-source initiatives we have focused our attention on Nimbus, Eucalyptus and OpenNebula. We have also detailed endeavours in the research world that are relevant to the topic of interest and are not connected to any of the Cloud providers. By studying this report, the reader will be able to understand the role that each of the three Cloud features plays for a Cloud client, will understand their inner workings and will be aware of the state-of-the-art available in current commercial and open-source Cloud platforms.

Published
2011

7. Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching

Author

Adrian Muresan, Frédéric Desprez, Eddy Caron, Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Algorithms and Scheduling for Distributed Heterogeneous Platforms (GRAAL), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), ANR-08-SEGI-0025,SPADES,Plateforme de Services Pour Architecture Petascale et DistribuéES.(2008), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
business.industry, Computer science, Real-time computing, Approximation algorithm, SPADES, 020206 networking & telecommunications, Workload, Cloud computing, 02 engineering and technology, Cloud Computing, Grid, computer.software_genre, Resource (project management), Grid computing, Cloud testing, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Pattern matching, business, computer
Abstract

International audience; The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. As a result, the question of efficient resource scaling arises. Prediction is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose an approach to the problem of workload prediction based on identifying similar past occurrences of the current short-term workload history. We present in detail the Cloud client resource auto-scaling algorithm that uses the above approach to help when scaling decisions are made, as well as experimental results by using real-world traces from Cloud and Grid platforms. We also present an overall evaluation of this approach, its potential and usefulness for enabling efficient auto-scaling of Cloud user resources.

Published
2010
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8. Cloud Computing Resource Management through a Grid Middleware: A Case Study with DIET and Eucalyptus

Author

D. Loureiro, Frédéric Desprez, Eddy Caron, Adrian Muresan, Algorithms and Scheduling for Distributed Heterogeneous Platforms (GRAAL), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), INRIA, École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), and Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Information management, Eucalyptus, DIET-Solve, business.industry, Computer science, Distributed computing, 020206 networking & telecommunications, Cloud computing, 02 engineering and technology, Cloud Computing, computer.software_genre, DIET, Grid computing, Server, Middleware, Scalability, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, The Internet, Resource management, resource management, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, computer
Abstract

International audience; The Cloud phenomenon is quickly growing towards becoming the de facto standard of Internet Computing, storage and hosting both in industry and academia. The large scalability possibilities offered by Cloud platforms can be harnessed not only for services and applications hosting but also as a raw on-demand computing resource. This paper proposes the use of a Cloud system as a raw computational on-demand resource for a Grid middleware. We illustrate a proof of concept by considering the DIET-Solve Grid middleware and the EUCALYPTUS open-source Cloud platform.

Published
2009
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