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  • 1. Beco, S
    et al.
    Maraschini, A
    Pacini, F
    Biran, O
    Breitgand, O
    Meth, K
    Rochwerger, B
    Salant, E
    Silvera, E
    Tal, S
    Wolfsthal, Y
    Yehuda, M
    Caceres, J
    Hierro, J
    Emmerich, W
    Galis, A
    Edblom, Lennart
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Henriksson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hohl, A
    Levy, E
    Sampaio, A
    Scheuermann, B
    Wusthoff, M
    Latanicki, J
    Lopez, G
    Marin-Frisonroche, J
    Dorr, A
    Ferstl, F
    Huedo, E
    Llorente, I
    Montero, R
    Massonet, P
    Naqvi, S
    Dallons, G
    Pezz, M
    Puliafito, A
    Ragusa, C
    Scarpa, M
    Muscella, S
    Cloud Computing and RESERVOIR project2009In: Nuovo Cimento C, ISSN ISSN 1124-1896, Vol. 32, no 2, p. 99-103Article in journal (Refereed)
  • 2. Ben Yehuda, M.
    et al.
    Biran, O.
    Breitgand, D.
    Meth, K.
    Rochwerger, B.
    Salant, E.
    Silvera, E.
    Tal, S.
    Wolfsthal, Y.
    Cáceres, J.
    Hierro, J.
    Emmerich, W.
    Galis, A.
    Edblom, Lennart
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Henriksson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hohl, A.
    Levy, E.
    Sampaio, A.
    Scheuermann, B.
    Wusthoff, M.
    Latanicki, J.
    Lopez, G.
    Marin-Frisonroche, J.
    Dörr, A.
    Ferstl, F.
    Beco, S.
    Pacini, F.
    Llorente, I.
    Montero, R.
    Huedo, E.
    Massonet, P.
    Naqvi, S.
    Dallons, G.
    Pezzé, M.
    Puliato, A.
    Ragusa, C.
    Scarpa, M.
    Muscella, S.
    RESERVOIR: An ICT Infrastructure for Reliable and Effective Delivery of Services as Utilities2008Report (Other academic)
  • 3.
    Berglund, Ann-Charlotte
    et al.
    Linnaeus Centre for Bioinformatics, Uppsala Universitet.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Sandman, Björn
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Combining local and grid resources in scientific workflows (for Bioinformatics)2009Conference paper (Refereed)
    Abstract [en]

    We examine some issues that arise when using both local and Gridresources in scientific workflows. Our previous work addresses and illustratesthe benefits of a light-weight and generic workflow engine that manages andoptimizes Grid resource usage. Extending on this effort, we hereillustrate how a client tool for bioinformatics applications employs the engine tointerface with Grid resources. We also explore how to define data flowsthat transparently integrates local and Grid subworkflows. In addition, the benefits of parameter sweep workflows are examined and a means for describing this type of workflows in an abstract and concise manner is introduced. Finally, the above mechanisms are employed to perform an orthology detection analysis.

  • 4.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, High Performance Compting Center North (HPC2N). Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    A light-weight Grid workflow execution service enabling client and middleware independence2008In: Parallel Processing and Applied Mathematics: 7th International Conference on Parallel Processing and Applied Mathematics (PPAM 2007), Springer-Verlag , 2008, p. 754-761Conference paper (Refereed)
    Abstract [en]

    We present a generic and light-weight Grid workflow execution engine made available as a Grid service. A long-term goal is to facilitate the rapid development of application-oriented end-user workflow tools, while providing a high degree of Grid middleware-independence. The workflow engine is designed for workflow execution, independent of client tools for workflow definition. A flexible plugin-structure for middleware-integration provides a strict separation of the workflow execution and the processing of individual tasks, such as computational jobs or file transfers. The light-weight design is achieved by focusing on the generic workflow execution components and by leveraging state-of-the art Grid technology, e.g., for state management. The current prototype is implemented using the Globus Toolkit 4 (GT4) Java WS Core and has support for executing workflows produced by Karajan. It also includes plugins for task execution with GT4 as well as a high-level Grid job management framework.

  • 5.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Three fundamental dimensions of scientific workflow interoperability: model of computation, language, and execution environment2010In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 26, no 2, p. 245-256Article in journal (Refereed)
    Abstract [en]

    We investigate interoperability aspects of scientific workflow systems and argue that the workflow execution environment, the model of computation (MoC), and the workflow language form three dimensions that must be considered depending on the type of interoperability sought: at the activity, sub-workflow, or workflow levels. With a focus on the problems that affect interoperability, we illustrate how these issues are tackled by current scientific workflows as well as how similar problems have been addressed in related areas. Our long-term objective is to achieve (logical) interoperability between workflow systems operating under different MoCs, using distinct language features, and sharing activities running on different execution environments.

  • 6.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, High Performance Compting Center North (HPC2N). Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Östberg, Per-Olov
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Designing service-based resource management tools for a healthy grid ecosystem2008In: Parallel processing and applied mathematics: 7th International Conference on Parallel Processing and Applied Mathematics, Springer-Verlag , 2008, p. 259-270Conference paper (Refereed)
    Abstract [en]

    We present an approach for development of Grid resource management tools, where we put into practice internationally established high-level views of future Grid architectures. The approach addresses fundamental Grid challenges and strives towards a future vision of the Grid where capabilities are made available as independent and dynamically assembled utilities, enabling run-time changes in the structure, behavior, and location of software. The presentation is made in terms of design heuristics, design patterns, and quality attributes, and is centered around the key concepts of co-existence, composability, adoptability, adaptability, changeability, and interoperability. The practical realization of the approach is illustrated by five case studies (recently developed Grid tools) high-lighting the most distinct aspects of these key concepts for each tool. The approach contributes to a healthy Grid ecosystem that promotes a natural selection of “surviving” components through competition, innovation, evolution, and diversity. In conclusion, this environment facilitates the use and composition of components on a per-component basis.

  • 7.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Ali-Eldin, Ahmed
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Svärd, Petter
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Sedaghat, Mina
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Li, Wubin
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Self-management challenges for multi-cloud architectures2011In: Towards a Service-Based Internet: 4th European Conference, ServiceWave 2011, Poznan, Poland, October 26-28, 2011. Proceedings / [ed] Witold Abramowicz, Ignacio M. Llorente, Mike Surridge, Andrea Zisman and Julien Vayssière, Springer Berlin/Heidelberg, 2011, p. 38-49Conference paper (Refereed)
    Abstract [en]

    Addressing the management challenges for a multitude of distributed cloud architectures, we focus on the three complementary cloud management problems of predictive elasticity, admission control, and placement (or scheduling) of virtual machines. As these problems are intrinsically intertwined we also propose an approach to optimize the overall system behavior by policy-tuning for the tools handling each of them. Moreover, in order to facilitate the execution of some of the management decisions, we also propose new algorithms for live migration of virtual machines with very high workload and/or over low-bandwidth networks, using techniques such as caching, compression, and prioritization of memory pages.

  • 8. Ferrer, Ana Juan
    et al.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Aley-Eldin, Ahmed
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Zsigri, Csilla
    Sirvent, Rauel
    Guitart, Jordi
    Badia, Rosa M.
    Djemame, Karim
    Ziegler, Wolfgang
    Dimitrakos, Theo
    Nair, Srijith K.
    Kousiouris, George
    Konstanteli, Kleopatra
    Varvarigou, Theodora
    Hudzia, Benoit
    Kipp, Alexander
    Wesner, Stefan
    Corrales, Marcelo
    Forgo, Nikolaus
    Sharif, Tabassum
    Sheridan, Craig
    OPTIMIS: A holistic approach to cloud service provisioning2012In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 28, no 1, p. 66-77Article in journal (Refereed)
    Abstract [en]

    We present fundamental challenges for scalable and dependable service platforms and architectures that enable flexible and dynamic provisioning of cloud services. Our findings are incorporated in a toolkit targeting the cloud service and infrastructure providers. The innovations behind the toolkit are aimed at optimizing the whole service life cycle, including service construction, deployment, and operation, on a basis of aspects such as trust, risk, eco-efficiency and cost. Notably, adaptive self-preservation is crucial to meet predicted and unforeseen changes in resource requirements. By addressing the whole service life cycle, taking into account several cloud architectures, and by taking a holistic approach to sustainable service provisioning, the toolkit aims to provide a foundation for a reliable, sustainable, and trustful cloud computing industry.

  • 9.
    Klein, Cristian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Maggio, Martina
    Lund University.
    Årzén, Karl-Erik
    Lund University.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Brownout: Building More Robust Cloud Applications2014In: 36th International Conference on Software Engineering (ICSE 2014), ACM Digital Library, 2014, p. 700-711Conference paper (Refereed)
    Abstract [en]

    Self-adaptation is a first class concern for cloud applications, which should be able to withstand diverse runtime changes. Variations are simultaneously happening both at the cloud infrastructure level - for example hardware failures - and at the user workload level - flash crowds. However, robustly withstanding extreme variability, requires costly hardware over-provisioning. In this paper, we introduce a self-adaptation programming paradigm called brownout. Using this paradigm, applications can be designed to robustly withstand unpredictable runtime variations, without over-provisioning. The paradigm is based on optional code that can be dynamically deactivated through decisions based on control theory. We modified two popular web application prototypes - RUBiS and RUBBoS - with less than 170 lines of code, to make them brownout-compliant. Experiments show that brownout self-adaptation dramatically improves the ability to withstand flash-crowds and hardware failures.

  • 10.
    Klein, Cristian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Maggio, Martina
    Lund University.
    Årzén, Karl-Erik
    Lund University.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Introducing Service-level Awareness in the Cloud2013In: Proceedings of the 4th annual Symposium on Cloud Computing, Association for Computing Machinery (ACM), 2013Conference paper (Refereed)
  • 11.
    Klein, Cristian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Maggio, Martina
    Lund University.
    Årzén, Karl-Erik
    Lund University.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Introducing Service-level Awareness in the Cloud2013Report (Other academic)
    Abstract [en]

    Resource allocation in clouds is mostly done assuming hard requirements, applications either receive the requested resources or fail. Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient.

    To solve this issue, we introduce Service-Level (SL) awareness in clouds, assuming applications contain some optional code that can be dynamically deactivated as needed. First, we design a model for such applications and synthesize a controller to decide when to execute the optional code and when to skip it. Then, we propose a Resource Manager (RM) that allocates resources to multiple SL-aware applications in a fair manner. We theoretically prove properties of the overall system using control and game theory.

    To show the practical applicability, we implemented SL-aware versions of RUBiS and RUBBoS with less than 170 lines of code. Experiments show that SL-awareness may enable a factor 8 improvement in withstanding flash-crowds or failures. SL-awareness opens up more flexibility in cloud resource management, which is why we encourage further research by publishing all source code.

  • 12.
    Klein, Cristian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Papadopoulos, Alessandro Vittorio
    Lund University, Sweden.
    Dellkrantz, Manfred
    Lund University, Sweden.
    Dürango, Jonas
    Lund University, Sweden.
    Maggio, Martina
    Lund University.
    Årzén, Karl-Erik
    Lund University.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Improving Cloud Service Resilience using Brownout-Aware Load-Balancing2014In: 2014 IEEE 33RD INTERNATIONAL SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS (SRDS), IEEE Computer Society, 2014, p. 31-40Conference paper (Refereed)
    Abstract [en]

    We focus on improving resilience of cloud services (e.g., e-commerce website), when correlated or cascading failures lead to computing capacity shortage. We study how to extend the classical cloud service architecture composed of a load-balancer and replicas with a recently proposed self-adaptive paradigm called brownout. Such services are able to reduce their capacity requirements by degrading user experience (e.g., disabling recommendations).

    Combining resilience with the brownout paradigm is to date an open practical problem. The issue is to ensure that replica self-adaptivity would not confuse the load-balancing algorithm, overloading replicas that are already struggling with capacity shortage. For example, load-balancing strategies based on response times are not able to decide which replicas should be selected, since the response times are already controlled by the brownout paradigm.

    In this paper we propose two novel brownout-aware load-balancing algorithms. To test their practical applicability, we extended the popular lighttpd web server and load-balancer, thus obtaining a production-ready implementation. Experimental evaluation shows that the approach enables cloud services to remain responsive despite cascading failures. Moreover, when compared to Shortest Queue First (SQF), believed to be near-optimal in the non-adaptive case, our algorithms improve user experience by 5%, with high statistical significance, while preserving response time predictability.

  • 13. Kolodner, Elliot K
    et al.
    Tal, Sivan
    Kyriazis, Dimosthenis
    Naor, Dalit
    Allalouf, Miriam
    Bonelli, Lucia
    Brand, Per
    Eckert, Albert
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Gogouvitos, Spyridon V
    Harnik, Danny
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jaeger, Michael C
    Lakew, Ewnetu Bayuh
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Lopez, Jose Manuel
    Lorenz, Mirko
    Messina, Alberto
    Schulman-Peleg, Alexandra
    Talyansky, Roman
    Voulodimos, Athanasios
    Wolfsthal, Yaron
    A cloud environment for data-intensive storage services2011In: IEEE third international conference on Cloud computing technology and science (CloudCom), 2011, IEEE conference proceedings, 2011, p. 357-366Conference paper (Refereed)
    Abstract [en]

    The emergence of cloud environments has made feasible the delivery of Internet-scale services by addressing a number of challenges such as live migration, fault tolerance and quality of service. However, current approaches do not tackle key issues related to cloud storage, which are of increasing importance given the enormous amount of data being produced in today's rich digital environment (e.g. by smart phones, social networks, sensors, user generated content). In this paper we present the architecture of a scalable and flexible cloud environment addressing the challenge of providing data-intensive storage cloud services through raising the abstraction level of storage, enabling data mobility across providers, allowing computational and content-centric access to storage and deploying new data-oriented mechanisms for QoS and security guarantees. We also demonstrate the added value and effectiveness of the proposed architecture through two real-life application scenarios from the healthcare and media domains.

  • 14.
    Lakew, Ewnetu B.
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Klein, Cristian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Performance-Based Service Differentiation in Clouds2015In: 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), IEEE conference proceedings, 2015, p. 505-514Conference paper (Refereed)
    Abstract [en]

    Due to fierce competition, cloud providers need to run their data-centers efficiently. One of the issues is to increase data-center utilization while maintaining applications' performance targets. Achieving high data-center utilization while meeting applications' performance is difficult, as data-center overload may lead to poor performance of hosted services. Service differentiation has been proposed to control which services get degraded. However, current approaches are capacity-based, which are oblivious to the observed performance of each service and cannot divide the available capacity among hosted services so as to minimize overall performance degradation. In this paper we propose performance-based service differentiation. In case enough capacity is available, each service is automatically allocated the right amount of capacity that meets its target performance, expressed either as response time or throughput. In case of overload, we propose two service differentiation schemes that dynamically decide which services to degrade and to what extent. We carried out an extensive set of experiments using different services -- interactive as well as non-interactive -- by varying the workload mixes of each service over time. The results demonstrate that our solution precisely provides guaranteed performance or service differentiation depending on available capacity.

  • 15.
    Lakew, Ewnetu. B.
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Klein, Cristian
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tail Response Time Modeling and Control for Interactive Cloud ServicesManuscript (preprint) (Other academic)
  • 16.
    Lakew, Ewnetu Bayuh
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Cristian, Klein
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Francisco, Hernandez-Rodriguez
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Erik, Elmroth
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Towards faster response time models for vertical elasticity2014In: 2014 IEEE/ACM 7TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC), 2014, p. 560-565Conference paper (Refereed)
    Abstract [en]

    Resource provisioning in cloud computing is typ- ically coarse-grained. For example, entire CPU cores may be allocated for periods of up to an hour. The Resource-as-a- Service cloud concept has been introduced to improve the efficiency of resource utilization in clouds. In this concept, resources are allocated in terms of CPU core fractions, with granularities of seconds. Such infrastructures could be created using existing technologies such as lightweight virtualization using LXC or by exploiting the Xen hypervisor’s capacity for vertical elasticity. However, performance models for de- termining how much capacity to allocate to each application are currently lacking. To address this deficit, we evaluate two performance models for predicting mean response times: the previously proposed queue length model and the novel inverse model. The models are evaluated using 3 applications under both open and closed system models. The inverse model reacted rapidly and remained stable even with targets as low as 0.5 seconds. 

  • 17.
    Lakew, Ewnetu Bayuh
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Xu, Lei
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Management of distributed resource allocations in multi-cluster environments2012In: Performance Computing and Communications Conference (IPCCC) 2012, 31st International, IEEE, New York, USA: IEEE , 2012, p. 275-284Conference paper (Other academic)
    Abstract [en]

    We present a fully distributed solution for managing resource allocation for services running across multiple clusters in a large-scale cloud computing environment. Our solution allows individual services running across clusters to compete dynamically for allocations based on their rate of consumption while maintaining the global cloud level allocation limits. The solution monitors resource consumption by services that are spread over a number of clusters. Global polls are triggered only when the allocated balance in a cluster decreases below a threshold and allocations are reassigned in a manner that avoids further immediate global polls. Our solution achieves scalability by minimizing global message exchanges, increases performance by distributing requests, and improves availability by avoiding a single point of failure. We perform a range of simulations to verify the accuracy of our approach, to validate our theoretical results, and to evaluate against competing approaches.

  • 18.
    Lakew, Ewnetu Bayuh
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Lei, Xu
    School of Computing, Dublin City University, Ireland.
    Francisco, Hernandez-Rodriguez
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Erik, Elmroth
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Claus, Pahl
    School of Computing, Dublin City University, Ireland.
    A Tree-based Protocol for Enforcing Quotas in Clouds2014In: the IEEE 10th 2014 World Congress on Services (SERVICES 2014), IEEE Computer Society, 2014Conference paper (Refereed)
    Abstract [en]

    Services are more and more hosted on cloud nodes for enhancing their performance and increasing their availability. The virtually unlimited availability of resources enables service owners to consume resources without quantitative restrictions, paying only for what they consume. To avoid cost overrun, resource consumption must be controlled and capped when necessary.We present a distributed tree-based protocol to manage quotas in clouds that minimizes communication overhead and reduces the time required to inspect if a quota has been exhausted. Experimental evaluation shows that our protocol provides 42% more communication savings and is up to 15 times faster compared to a distributed baseline solution.

  • 19.
    Lakew, Ewnetu Bayuh
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Xu, Lei
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Pahl, Claus
    A synchronization mechanism for cloud accounting systems2014In: 2014 International Conference on Cloud and Autonomic Computing (ICCAC 2014), 2014, p. 111-120Conference paper (Refereed)
    Abstract [en]

    In current cloud systems, services run across multiple geographically distributed clusters and continuously generate resource usage data due to constant resource consumption. In the context of accounting, resource usage data generated from each cluster during service runtime must be collected and aggregated into a single cloud-wide record so that a single bill can be created. This paper presents a mechanism to synchronize accounting records among distributed accounting system peers. Run time resource usage generated from different clusters is synchronized to maintain a single cloud-wide view of the data so that a single bill can be created. We provide a set of accounting system requirements and an evaluation which verifies that the solution fulfills these requirements. Experimental results show that our solution produces less overhead in terms of data exchange and scales near-linearly with the size of clusters with no single point of failure.

  • 20.
    Metsch, Thijs
    et al.
    Intel Labs Europe, Intel Ireland.
    Ibidunmoye, Olumuyiwa
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bayon-Molino, Victor
    Intel Labs Europe, Intel Ireland.
    Butler, Joe
    Intel Labs Europe, Intel Ireland.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Apex lake: a framework for enabling smart orchestration2015In: Proceedings of the Industry Track of the 16th ACM/IFIP/USENIX Middleware Conference, New York, USA: Association for Computing Machinery (ACM), 2015, p. 1-7, article id 1Conference paper (Refereed)
    Abstract [en]

    The introduction of a Software-defined infrastructures brings additional challenges to the management of cloud infrastructure. With the impending convergence of telecommunications and cloud infrastructures, datacenters become an essential part of an overall integrated environment. The potential scale of such environments has significant implications as traditional orchestration approaches cannot scale appropriately. However, the combination of infrastructure topology, fine-grained operational data and advanced analytics, has the potential to deliver a scalable approach to facilitate orchestration and resource management. In this paper we introduce Apex Lake, a framework designed to address the question of "how to efficiently define and maintain a physical and logical resource and service landscape enriched by operational data, to support orchestration for optimized service delivery?" We also demonstrate with a use-case illustrating how functionalities provided by Apex Lake can be used dealing with performance anomalies.

  • 21.
    Papadopoulos, Alessandro Vittorio
    et al.
    Lund University, Sweden.
    Klein, Cristian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Maggio, Martina
    Lund University.
    Dürango, Jonas
    Lund University, Sweden.
    Dellkrantz, Manfred
    Lund University, Sweden.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Årzén, Karl-Erik
    Lund University.
    Control-based load-balancing techniques: Analysis and performance evaluation via a randomized optimization approach2016In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 52, p. 24-34Article in journal (Refereed)
    Abstract [en]

    Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas - copies of the application with the same functionality - for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer. Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing. To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF)-believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.

  • 22.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    A virtual machine re-packing approach to the horizontal vs. vertical elasticity trade-off for cloud autoscaling2013In: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference, ACM Press, 2013, p. Article no. 6-Conference paper (Refereed)
    Abstract [en]

    An automated solution to horizontal vs. vertical elasticity problem is central to make cloud autoscalers truly autonomous. Today's cloud autoscalers are typically varying the capacity allocated by increasing and decreasing the number of virtual machines (VMs) of a predefined size (horizontal elasticity), not taking into account that as load varies it may be advantageous not only to vary the number but also the size of VMs (vertical elasticity). We analyze the price/performance effects achieved by different strategies for selecting VM-sizes for handling increasing load and we propose a cost-benefit based approach to determine when to (partly) replace a current set of VMs with a different set. We evaluate our repacking approach in combination with different auto-scaling strategies. Our results show a range of 7% up to 60% cost saving in total resource utilization cost of our sample applications and workloads.

  • 23.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Peer to peer resource management for cloud data centersManuscript (preprint) (Other academic)
  • 24.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Unifying cloud management: towards overall governance of business level objectives2011In: Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on, IEEE Computer Society , 2011, p. -597Conference paper (Refereed)
    Abstract [en]

    We address the challenge of providing unified cloud resource management towards an overall business level objective, given the multitude of managerial tasks to be performed and the complexity of any architecture to support them. Resource level management tasks include elasticity control, virtual machine and data placement, autonomous fault management, etc, which are intrinsically difficult problems since services normally have unknown lifetime and capacity demands that varies largely over time. To unify the management of these problems, (for optimization with respect to some higher level business level objective, like optimizing revenue while breaking no more than a certain percentage of service level agreements)becomes even more challenging as the resource level managerial challenges are far from independent. After providing the general problem formulation, we review recent approaches taken by the research community, including mainly general autonomic computing technology for large-scale environments and resource level management tools equipped with some business oriented or otherwise qualitative features. We propose and illustrate a policy-driven approach where a high-level management system monitors overall system and services behavior and adjusts lower level policies (e.g., thresholds for admission control, elasticity control, server consolidation level, etc) for optimization towards the measurable business level objectives.

  • 25.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Autonomic resource allocation for cloud data centers: a peer to peer approach2014In: 2014 International Conference on Cloud and Autonomic Computing (ICCAC 2014), IEEE Computer Society, 2014, , p. 10p. 131-140Conference paper (Refereed)
    Abstract [en]

    We address the problem of resource management for large scale cloud data centers. We propose a Peer to Peer (P2P) resource management framework, comprised of a number of agents, overlayed as a scale-free network. The structural properties of the overlay, along with dividing the management responsibilities among the agents enables the management framework to be scalable in terms of both the number of physical servers and incoming Virtual Machine (VM) requests, while it is computationally feasible. While our framework is intended for use in different cloud management functionalities, e.g. admission control or fault tolerance, we focus on the problem of resource allocation in clouds. We evaluate our approach by simulating a data center with 2500 servers, striving to allocate resources to 20000 incoming VM placement requests. The simulation results indicate that by maintaining an efficient request propagation, we can achieve promising levels of performance and scalability when dealing with large number of servers and placement requests.

  • 26.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Girdzijauskas, Šarūnas
    Divide the task, multiply the outcome: cooperative VM consolidation2014In: Proceedings of The 6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2014), IEEE, 2014, , p. 6p. 300-305Conference paper (Refereed)
    Abstract [en]

    Efficient resource utilization is one of the mainconcerns of cloud providers, as it has a direct impact onenergy costs and thus their revenue. Virtual machine (VM)consolidation is one the common techniques, used by infrastruc-ture providers to efficiently utilize their resources. However,when it comes to large-scale infrastructures, consolidationdecisions become computationally complex, since VMs aremulti-dimensional entities with changing demand and unknownlifetime, and users often overestimate their actual demand.These uncertainties urges the system to take consolidationdecisions continuously in a real time manner.In this work, we investigate a decentralized approach forVM consolidation using Peer to Peer (P2P) principles. Weinvestigate the opportunities offered by P2P systems, as scalableand robust management structures, to address VM consol-idation concerns. We present a P2P consolidation protocol,considering the dimensionality of resources and dynamicityof the environment. The protocol benefits from concurrencyand decentralization of control and it uses a dimension awaredecision function for efficient consolidation. We evaluate theprotocol through simulation of 100,000 physical machinesand 200,000 VM requests. Results demonstrate the potentialsand advantages of using a P2P structure to make resourcemanagement decisions in large scale data centers. They showthat the P2P approach is feasible and scalable and producesresource utilization of 75% when the consolidation aim is 90%.

  • 27. Talyansky, Roman
    et al.
    Lakew, Ewnetu Bayuh
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Klein, Cristian
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Levy, Eliezer
    Towards Optimized Self-Management of Distributed Object Storage Systems2015Report (Other academic)
    Abstract [en]

    Cloud storage is increasingly adopted by users due to simplified storage systems compared to on-premise storage. These systems are mostly presented as Object Storage Systems (OSSs), hiding issues, such as redundancy, from users. As new industries are considering adopting clouds for storage, OSSs have to evolve to support new needs. Among the most challenging is assuring guaranteed performance.

    In this paper, we present Controllable Trade-offs (CTO), an OSS-agnostic solution to add performance guarantees. CTO presents itself as a thin layer that mediates requests between the user and the OSS. For generic support, performance is controlled by tuning the rejection probability, and implemented as a user-side queue. Results show that CTO may reduce penalties 3.23 times on average and up to 68 times when the load is high.

  • 28.
    Tomás, Luis
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Klein, Cristian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    The straw that broke the camel’s back: safe cloud overbooking with application brownout2014In: 2014 International Conference on Cloud and Autonomic Computing (ICCAC 2014), IEEE Press, 2014, p. 151-160Conference paper (Refereed)
    Abstract [en]

    Resource overbooking is an admission control technique to increase utilization in cloud environments. However, due to uncertainty about future application workloads, overbooking may result in overload situations and deteriorated performance. We mitigate this using brownout, a feedback approach to application performance steering, that ensures graceful degradation during load spikes and thus avoids overload. Additionally, brownout management information is included into the overbooking system, enabling the development of improved reactive methods to overload situations. Our combined brownout-overbooking approach is evaluated based on real-life interactive workloads and non-interactive batch applications. The results show that our approach achieves an improvement of resource utilization of 11 to 37 percentage points, while keeping response times lower than the set target of 1 second, with negligible application degradation.

  • 29.
    Xu, Lei
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Lakew, Ewnetu Bayuh
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernandez-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    A Scalable Accounting Solution for Prepaid Services in Cloud Systems2012In: Proceedings of the 2012 IEEE Ninth International Conference on Services Computing, 2012, p. 81-89Conference paper (Refereed)
    Abstract [en]

    Prepaid charging, an essential option for the accounting of cloud services, provides effective financial control for both service providers and customers. However, it has to be supported by real-time credit checking and cost calculation. These real-time actions consume resources of the providers' network and impose high overhead. To tackle this issue, we present a scalable accounting solution in which an accounting component is hosted in every cluster constituting a cloud system. Each of our accounting component supervises service consumptions based on a calculated interval of a service bundle that is composed of all services hosted in a cluster and consumed by one customer simultaneously. Credit will be re-allocated when a customer's credit in one cluster is not enough to compensate further usage, and the allocation is performed based on service consumptions. This work is intended to reduce the cost of prepaid services and to ensure service provision is not hampered by the charging part. Additionally, we perform theoretical and experimental analyses that indicate this work can provide an inexpensive accounting solution for the long-lived services in storage clouds.

1 - 29 of 29
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