Torres Viñals, Jordi
Total activity: 217
Expertise
Big Data, Cloud Computing, Distributed Systems, Green Computing, Hight Performance Computing
Professional category
University professor
Doctoral courses
Doctor en Informàtica
University degree
Llicenciat en Informàtica
Research group
CAP - High Performace Computing Group
Department
Department of Computer Architecture
School
Barcelona School of Informatics (FIB)
E-mail
torresac.upc.edu
Contact details
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Links of interest
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1 to 50 of 217 results
  • Deadline-based MapReduce workload management

     Polo, Jorda; Becerra Fontal, Yolanda; Carrera Perez, David; Steinder, Malgorzata; Whalley, Ian; Torres Viñals, Jordi; Ayguade Parra, Eduard
    IEEE transactions on network and service management
    Date of publication: 2013
    Journal article

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    This paper presents a scheduling technique for multi-job MapReduce workloads that is able to dynamically build performance models of the executing workloads, and then use these models for scheduling purposes. This ability is leveraged to adaptively manage workload performance while observing and taking advantage of the particulars of the execution environment of modern data analytics applications, such as hardware heterogeneity and distributed storage. The technique targets a highly dynamic environment in which new jobs can be submitted at any time, and in which MapReduce workloads share physical resources with other workloads. Thus the actual amount of resources available for applications can vary over time. Beyond the formulation of the problem and the description of the algorithm and technique, a working prototype (called Adaptive Scheduler) has been implemented. Using the prototype and medium-sized clusters (of the order of tens of nodes), the following aspects have been studied separately: the scheduler's ability to meet high-level performance goals guided only by user-defined completion time goals; the scheduler's ability to favor data-locality in the scheduling algorithm; and the scheduler's ability to deal with hardware heterogeneity, which introduces hardware affinity and relative performance characterization for those applications that can benefit from executing on specialized processors.

  • Power-aware multi-data center management using machine learning

     Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    International Workshop on Power-aware Algorithms, Systems, and Architectures
    Presentation's date: 2013-10-01
    Presentation of work at congresses

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    The cloud relies upon multi-datacenter (multi-DC) infrastructures distributed along the world, where people and enterprises pay for resources to offer their web-services to worldwide clients. Intelligent management is required to automate and manage these infrastructures, as the amount of resources and data to manage exceeds the capacities of human operators. Also, it must take into account the cost of running the resources (energy) and the quality of service towards web-services and clients. (De-)consolidation and priming proximity to clients become two main strategies to allocate resources and properly place these web-services in the multi-DC network. Here we present a mathematical model to describe the scheduling problem given web-services and hosts across a multi-DC system, enhancing the decision makers with models for the system behavior obtained using machine learning. After running the system on real DC infrastructures we see that the model drives web-services to the best locations given quality of service, energy consumption, and client proximity, also (de-)consolidating according to the resources required for each web-service given its load.

  • Empowering automatic data-center management with machine learning

     Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    ACM Symposium on Applied Computing
    Presentation's date: 2013-03-21
    Presentation of work at congresses

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    The Cloud as computing paradigm has become nowadays crucial for most Internet business models. Managing and optimizing its performance on a moment-by-moment basis is not easy given as the amount and diversity of elements involved (hardware, applications, workloads, customer needs...). Here we show how a combination of scheduling algorithms and data mining techniques helps improving the performance and profitability of a data-center running virtualized web-services. We model the data-center's main resources (CPU, memory, IO), quality of service (viewed as response time), and workloads (incoming streams of requests) from past executions. We show how these models to help scheduling algorithms make better decisions about job and resource allocation, aiming for a balance between throughput, quality of service, and power consumption.

  • Power-aware multi-data center management using machine learning

     Berral, Josep; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    International Workshop on Power-aware Algorithms, Systems, and Architectures
    Presentation's date: 2013-10-01
    Presentation of work at congresses

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    The cloud relies upon multi-data center (multi-DC) infrastructures distributed along the world, where people and enterprises pay for resources to offer their web-services to worldwide clients. Intelligent management is required to automate and manage these infrastructures, as the amount of resources and data to manage exceeds the capacities of human operators. Also, it must take into account the cost of running the resources (energy) and the quality of service towards web-services and clients. (De-)consolidation and priming proximity to clients become two main strategies to allocate resources and properly place these web-services in the multi-DC network. Here we present a mathematical model to describe the scheduling problem given web-services and hosts across a multi-DC system, enhancing the decision makers with models for the system behavior obtained using machine learning. After running the system on real DC infrastructures we see that the model drives web-services to the best locations given quality of service, energy consumption, and client proximity, also (de-)consolidating according to the resources required for each web-service given its load.

  • Improved self-management of datacenter systems applying machine learning

     Berral Garcia, Josep Lluis
    Defense's date: 2013-11-22
    Universitat Politècnica de Catalunya
    Theses

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  • Autonomic placement of mixed batch and transactional workloads

     Carrera Perez, David; Steinder, Malgorzata; Whalley, Ian; Torres Viñals, Jordi; Ayguade Parra, Eduard
    IEEE transactions on parallel and distributed systems
    Date of publication: 2012-02-01
    Journal article

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  • EMOTIVE cloud: the BSC's IaaS open source solution for cloud computing

     Vaqué, Alex; Goiri Presa, Iñigo; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Date of publication: 2012-01
    Book chapter

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  • Toward energy-aware scheduling using machine learning

     Berral Garcia, Josep Lluis; Goiri Presa, Iñigo; Nou Castell, Ramon; Julià Massó, Ferran; Fitó Comellas, Josep Oriol; Guitart Fernández, Jordi; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    Date of publication: 2012-07-30
    Book chapter

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  • Green data center infrastructures in the cloud computing era

     Ricciardi, Sergio; Palmieri, Francesco; Torres Viñals, Jordi; Di Martino, Beniamino; Santos Boada, German; Sole Pareta, Josep
    Date of publication: 2012-11-29
    Book chapter

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  • GreenHadoop: leveraging green energy in data-processing frameworks

     Goiri, Iñigo; Le, Kien; Nguyen, Thu D.; Guitart Fernández, Jordi; Torres Viñals, Jordi; Bianchini, Ricardo
    ACM European Conference on Computer Systems
    Presentation's date: 2012-04-10
    Presentation of work at congresses

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  • A methodology for the evaluation of high response time on E-commerce users and sales

     Poggi, Nicolas; Carrera Perez, David; Gavaldà Mestre, Ricard; Ayguade Parra, Eduard; Torres Viñals, Jordi
    Information systems frontiers
    Date of publication: 2012-10-06
    Journal article

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  • Economic model of a cloud provider operating in a federated cloud

     Goiri Presa, Iñigo; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Information systems frontiers
    Date of publication: 2012-09
    Journal article

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    Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. On the one hand, the providers can serve most of the requests owning only a restricted amount of resources, but this forces to reject customers during peak hours. On the other hand, valley hours incur in under-utilization of the resources, which forces the providers to increase their prices to be profitable. Federation overcomes these limitations and allows providers to dynamically outsource resources to others in response to demand variations. Furthermore, it allows providers with underused resources to rent them to other providers. Both techniques make the provider getting more profit when used adequately. Federation of Cloud providers requires having a clear understanding of the consequences of each decision. In this paper, we present a characterization of providers operating in a federated Cloud which helps to choose the most convenient decision depending on the environment conditions. These include when to outsource to other providers, rent free resources to other providers (i.e., insourcing), or turn off unused nodes to save power. We characterize these decisions as a function of several parameters and implement a federated provider that uses this characterization to exploit federation. Finally, we evaluate the profitability of using these techniques using the data from a real provider.

  • Energy-efficient and multifaceted resource management for profit-driven virtualized data centers

     Goiri, Iñigo; Berral Garcia, Josep Lluis; Fitó Comellas, Josep Oriol; Julià Massó, Ferran; Nou Castell, Ramon; Guitart Fernández, Jordi; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    Future generation computer systems
    Date of publication: 2012-05
    Journal article

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    As long as virtualization has been introduced in data centers, it has been opening new chances for resource management. Nowadays, it is not just used as a tool for consolidating underused nodes and save power; it also allows new solutions to well-known challenges, such as heterogeneity management. Virtualization helps to encapsulate Web-based applications or HPC jobs in virtual machines (VMs) and see them as a single entity which can be managed in an easier and more efficient way. We propose a new scheduling policy that models and manages a virtualized data center. It focuses on the allocation of VMs in data center nodes according to multiple facets to optimize the provider’s profit. In particular, it considers energy efficiency, virtualization overheads, and SLA violation penalties, and supports the outsourcing to external providers. The proposed approach is compared to other common scheduling policies, demonstrating that a provider can improve its benefit by 30% and save power while handling other challenges, such as resource outsourcing, in a better and more intuitive way than other typical approaches do.

    Postprint (author’s final draft)

  • Energy accounting for shared virtualized environments under DVFS using PMC-based power models

     Bertran Monfort, Ramon; Becerra Fontal, Yolanda; Carrera Perez, David; Beltran Querol, Vicenç; Gonzalez Tallada, Marc; Martorell Bofill, Xavier; Navarro Mas, Nacho; Torres Viñals, Jordi; Ayguade Parra, Eduard
    Future generation computer systems
    Date of publication: 2012-02
    Journal article

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  • Adaptive scheduling on power-aware managed data-centers using machine learning

     Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    ACM/IEEE International Conference on Grid Computing
    Presentation's date: 2011-09-22
    Presentation of work at congresses

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    Energy-related costs have become one of the major economic factors in IT data-centers, and companies and the research community are currently working on new efficient power-aware resource management strategies, also known as “Green IT”. Here we propose an autonomic scheduling of tasks and web-services over cloud environments, focusing on the profit optimization by executing a set of tasks according to servicelevel agreements minus its costs like power consumption. The principal contribution is the use of machine learning techniques in order to predict a priori resource usages, like CPU consumption, and estimate the tasks response time based on the monitored data traffic characteristics. Further, in order to optimize the scheduling, an exact solver based on mixed integer linear programming is used as a proof of concept, and also compared to some approximate algorithm solvers to find valid alternatives for the NP-hard problem of exact schedule solving. Experiments show that machine learning algorithms can predict system behaviors with acceptable accuracy, also the ILP solver obtains the optimal solution managing to adjust appropriately the schedule according to profits and cost of power increases, also reducing migrations when their cost is taken into consideration. Finally, is demonstrated that one of the approximate algorithm solvers is much faster but close in terms of the optimization goal to the exact solver.

  • Resource-aware adaptive scheduling for MapReduce clusters

     Polo, Jordà; Castillo, Claris; Carrera Perez, David; Becerra Fontal, Yolanda; Whalley, Ian; Steinder, Malgorzata; Torres Viñals, Jordi; Ayguade Parra, Eduard
    ACM/IFIP/USENIX International Middleware Conference
    Presentation's date: 2011-12-16
    Presentation of work at congresses

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  • GreenSlot: scheduling energy consumption in green datacenters

     Goiri Presa, Iñigo; Le, Kien; Haque, Md. E.; Beauchea, Ryan; Nguyen, Thu D.; Guitart Fernández, Jordi; Torres Viñals, Jordi; Bianchini, Ricardo
    International Conference for High Performance Computing, Networking, Storage and Analysis
    Presentation's date: 2011-11-16
    Presentation of work at congresses

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  • Optimal resource allocation in a virtualized software aging platform with software rejuvenation

     Alonso López, Javier; Goiri Presa, Iñigo; Guitart Fernández, Jordi; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    IEEE International Symposium on Software Reliability Engineering
    Presentation's date: 2011-11-29
    Presentation of work at congresses

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  • Intelligent placement of datacenters for Internet services

     Goiri Presa, Iñigo; Le, Kien; Guitart Fernández, Jordi; Torres Viñals, Jordi; Bianchini, Ricardo
    International Conference on Distributed Computing Systems
    Presentation's date: 2011-06-20
    Presentation of work at congresses

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  • Towards sustainable solutions for European cloud computing

     Le, Kien; Nguyen, Thu D.; Goiri, Iñigo; Bianchini, Ricardo; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Upgrade
    Date of publication: 2011-10
    Journal article

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  • Proactive Software Rejuvenation solution for web enviroments on virtualized platforms

     Alonso López, Javier
    Defense's date: 2011-02-21
    Department of Computer Architecture, Universitat Politècnica de Catalunya
    Theses

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  • Empresas en la nube: ventajas y retos del cloud computing

     Torres Viñals, Jordi
    Date of publication: 2011-06-01
    Book

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  • Empreses en el núvol: claus per entendre la internet global

     Torres Viñals, Jordi
    Date of publication: 2011-06-01
    Book

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  • A path to achieving a self-managed Grid middleware

     Nou Castell, Ramon; Julià, Ferran; Hogan, Kevin; Torres Viñals, Jordi
    Future generation computer systems
    Date of publication: 2011-01
    Journal article

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  • Characterization of workload and resource consumption for an online travel and booking site

     Poggi Mastrokalo, Nicolas; Carrera Perez, David; Gavaldà Mestre, Ricard; Torres Viñals, Jordi; Ayguade Parra, Eduard
    IEEE International Symposium on Workload Characterization
    Presentation's date: 2010-12-02
    Presentation of work at congresses

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    Checkpoint-based fault-tolerant infrastructure for virtualized service providers  Open access

     Goiri Presa, Iñigo; Julià, Ferran; Guitart Fernández, Jordi; Torres Viñals, Jordi
    IEEE/ IFIP Network Operations and management Symposium
    Presentation's date: 2010-04-19
    Presentation of work at congresses

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    Crash and omission failures are common in service providers: a disk can break down or a link can fail anytime. In addition, the probability of a node failure increases with the number of nodes. Apart from reducing the provider’s computation power and jeopardizing the fulfillment of his contracts, this can also lead to computation time wasting when the crash occurs before finishing the task execution. In order to avoid this problem, efficient checkpoint infrastructures are required, especially in virtualized environments where these infrastructures must deal with huge virtual machine images. This paper proposes a smart checkpoint infrastructure for virtualized service providers. It uses Another Union File System to differentiate read-only from read-write parts in the virtual machine image. In this way, read-only parts can be checkpointed only once, while the rest of checkpoints must only save the modifications in read-write parts, thus reducing the time needed to make a checkpoint. The checkpoints are stored in a Hadoop Distributed File System. This allows resuming a task execution faster after a node crash and increasing the fault tolerance of the system, since checkpoints are distributed and replicated in all the nodes of the provider. This paper presents a running implementation of this infrastructure and its evaluation, demonstrating that it is an effective way to make faster checkpoints with low interference on task execution and efficient task recovery after a node failure.

  • Performance-driven task co-scheduling for MapReduce environments

     Polo, Jordà; Carrera Perez, David; Becerra Fontal, Yolanda; Torres Viñals, Jordi; Steinder, Malgorzata; Ayguade Parra, Eduard; Whalley, Ian
    IEEE Network Operations and Management Symposium (NOMS)
    Presentation's date: 2010-04-21
    Presentation of work at congresses

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    Adaptive on-line software aging prediction based on machine learning  Open access

     Alonso López, Javier; Torres Viñals, Jordi; Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard
    IEEE/IFIP International Conference on Dependable Systems and Networks
    Presentation's date: 2010-07-28
    Presentation of work at congresses

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    The growing complexity of software systems is resulting in an increasing number of software faults. According to the literature, software faults are becoming one of the main sources of unplanned system outages, and have an important impact on company benefits and image. For this reason, a lot of techniques (such as clustering, fail-over techniques, or server redundancy) have been proposed to avoid software failures, and yet they still happen. Many software failures are those due to the software aging phenomena. In this work, we present a detailed evaluation of our chosen machine learning prediction algorithm (M5P) in front of dynamic and non-deterministic software aging. We have tested our prediction model on a three-tier web 12EE application achieving acceptable prediction accuracy against complex scenarios with small training data sets. Furthermore, we have found an interesting approach to help to determine the root cause failure: The model generated by machine learning algorithms.

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    Multifaceted resource management for dealing with heterogeneous workloads in virtualized data centers  Open access

     Goiri Presa, Iñigo; Fitó Comellas, Josep Oriol; Julià Masso, Ferran; Nou Castell, Ramon; Berral Garcia, Josep Lluis; Guitart Fernández, Jordi; Torres Viñals, Jordi
    ACM/IEEE International Conference on Grid Computing
    Presentation's date: 2010-10-25
    Presentation of work at congresses

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    As long as virtualization has been introduced in data centers, it has been opening new chances for resource management. Now, it is not just used as a tool for consolidating underused nodes and save power, it also allows new solutions to well-known challenges, such as fault tolerance or heterogeneity management. Virtualization helps to encapsulate Web-based applications or HPC jobs in virtual machines and see them as a single entity which can be managed in an easier way. This paper proposes a new scheduling policy to model and manage a virtualized data center which mainly focuses on the allocation of VMs in data center nodes according to multiple facets while optimizing the provider’s profit. In particular, it considers energy efficiency, virtualization overheads, fault tolerance, and SLA violation penalties, while adding the ability to outsource resources to external providers. Using our approach, a data center can improve the provider’s benefit by 15% and get a power reduction while solving well-known challenges, such as fault tolerance and outsourcing, in a better a more intuitive way that typical approaches do.

  • Access to the full text
    Characterizing cloud federation for enhancing providers' profit  Open access

     Goiri Presa, Iñigo; Guitart Fernández, Jordi; Torres Viñals, Jordi
    IEEE International Conference on Cloud Computing Technology and Science
    Presentation's date: 2010-07-05
    Presentation of work at congresses

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    Cloud federation has been proposed as a new paradigm that allows providers to avoid the limitation of owning only a restricted amount of resources, which forces them to reject new customers when they have not enough local resources to fulfill their customers’ requirements. Federation allows a provider to dynamically outsource resources to other providers in response to demand variations. It also allows a provider that has underused resources to rent part of them to other providers. Both things could make the provider to get more profit when used adequately. This requires that the provider has a clear understanding of the potential of each federation decision, in order to choose the most convenient depending on the environment conditions. In this paper, we present a complete characterization of providers’ federation in the Cloud, including decision equations to outsource resources to other providers, rent free resources to other providers (i.e. insourcing), or shutdown unused nodes to save power, and we characterize these decisions as a function of several parameters. Then, we demonstrate in the evaluation section how a provider can enhance its profit by using these equations to exploit federation, and how the different parameters influence which is the best decision on each situation.

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    BSC contributions in energy-aware resource management for large scale distributed systems  Open access

     Torres Viñals, Jordi; Ayguade Parra, Eduard; Carrera Perez, David; Guitart Fernández, Jordi; Beltran Querol, Vicenç; Becerra Fontal, Yolanda; Badia Sala, Rosa Maria; Labarta Mancho, Jesus Jose; Valero Cortes, Mateo
    Workshop of the COST Action IC0804 on Energy Efficiency in Large Scale Distributed Systems
    Presentation's date: 2010-04-15
    Presentation of work at congresses

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    This paper introduces the work being carried out at Barcelona Supercomputing Center in the area of Green Computing. We have been working in resource management for a long time and recently we included the energy parameter in the decision process, considering that for a more sustainable science, the paradigm will shift from “time to solution” to “kWh to the solution”. We will present our proposals organized in four points that follow the cloud computing stack. For each point we will enumerate the latest achievements that will be published during 2010 that are the basics for our future research. To conclude the paper we will review our ongoing and future research work and an overview of the projects where BSC is participating.

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    Energy-aware scheduling in virtualized datacenters  Open access

     Goiri Presa, Iñigo; Julià Massó, Ferran; Nou Castell, Ramon; Berral Garcia, Josep Lluis; Guitart Fernández, Jordi; Torres Viñals, Jordi
    IEEE International Conference on Cluster Computing
    Presentation's date: 2010-09-20
    Presentation of work at congresses

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    The reduction of energy consumption in large-scale datacenters is being accomplished through an extensive use of virtualization, which enables the consolidation of multiple workloads in a smaller number of machines. Nevertheless, virtualization also incurs some additional overheads (e.g. virtual machine creation and migration) that can influence what is the best consolidated configuration, and thus, they must be taken into account. In this paper, we present a dynamic job scheduling policy for power-aware resource allocation in a virtualized datacenter. Our policy tries to consolidate workloads from separate machines into a smaller number of nodes, while fulfilling the amount of hardware resources needed to preserve the quality of service of each job. This allows turning off the spare servers, thus reducing the overall datacenter power consumption. As a novelty, this policy incorporates all the virtualization overheads in the decision process. In addition, our policy is prepared to consider other important parameters for a datacenter, such as reliability or dynamic SLA enforcement, in a synergistic way with power consumption. The introduced policy is evaluated comparing it against common policies in a simulated environment that accurately models HPC jobs execution in a virtualized datacenter including power consumption modeling and obtains a power consumption reduction of 15% with respect to typical policies.

  • Performance management of accelerated MapReduce workloads in heterogeneous clusters

     Polo, Jordà; Carrera Perez, David; Becerra Fontal, Yolanda; Beltran Querol, Vicenç; Torres Viñals, Jordi; Ayguade Parra, Eduard
    International Conference on Parallel Processing
    Presentation's date: 2010-09-16
    Presentation of work at congresses

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  • Accurate energy accounting for shared virtualized environments using PMC-based power modeling techniques

     Bertran Monfort, Ramon; Becerra Fontal, Yolanda; Carrera Perez, David; Beltran Querol, Vicenç; Gonzalez Tallada, Marc; Martorell Bofill, Xavier; Torres Viñals, Jordi; Ayguade Parra, Eduard
    ACM/IEEE International Conference on Grid Computing
    Presentation's date: 2010-10-27
    Presentation of work at congresses

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  • Enforcing service level agreements using an economically enhanced resource manager

     Macias Lloret, Mario; Smith, Garry; Rana, Omer; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Date of publication: 2010-01
    Book chapter

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  • Extended resource management using client classification and economic enhancements

     Püschel, Tim; Borissov, Nikolay; Neumann, Dirk; Macias Lloret, Mario; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Date of publication: 2010-01
    Book chapter

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    Commercialization of computing resources will become more and more important as the transition from Grid computing in academic environments to commercial services based on concepts such as utility or Cloud computing progresses. This results in the necessity to not only base components on technical aspects, but also to include economical aspects in their design. This paper presents a framework that links technical and economical aspects to the management of computational resources. Economic enhancements like dynamic pricing and client classification are introduced based on a technical resource management environment and positioned within this resulting in a proposed architecture for an Economically Enhanced Resource Manager (EERM). The introduced approach is evaluated considering various economic design criteria and example scenarios.

  • Access to the full text
    Towards energy-aware scheduling in data centers using machine learning  Open access

     Berral Garcia, Josep Lluis; Goiri Presa, Iñigo; Nou Castell, Ramon; Julià, Ferran; Guitart Fernández, Jordi; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    1st International Conference on Energy-Efficient Computing and Networking
    Presentation's date: 2010-04-15
    Presentation of work at congresses

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    As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to nd better and more efficient power-aware resource management strategies. There is a growing interest in "Green" IT and there is still a big gap in this area to be covered. In order to obtain an energy-efficient data center, we propose a framework that provides an intelligent consolidation methodology using di erent techniques such as turning on/o ff machines, power-aware consolidation algorithms, and machine learning techniques to deal with uncertain information while maximizing performance. For the machine learning approach, we use models learned from previous system behaviors in order to predict power consumption levels, CPU loads, and SLA timings, and improve scheduling decisions. Our framework is vertical, because it considers from watt consumption to workload features, and cross-disciplinary, as it uses a wide variety of techniques. We evaluate these techniques with a framework that covers the whole control cycle of a real scenario, using a simulation with representative heterogeneous workloads, and we measure the quality of the results according to a set of metrics focused toward our goals, besides traditional policies. The results obtained indicate that our approach is close to the optimal placement and behaves better when the level of uncertainty increases.

    Postprint (author’s final draft)

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    J2EE instrumentation for software aging root cause application component determination with AspectJ  Open access

     Alonso López, Javier; Torres Viñals, Jordi; Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard
    IEEE Workshop on Dependable Parallel, Distributed and Network-Centric System
    Presentation's date: 2010-04-23
    Presentation of work at congresses

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    Unplanned system outages have a negative impact on company revenues and image. While the last decades have seen a lot of efforts from industry and academia to avoid them, they still happen and their impact is increasing. According to many studies, one of the most important causes of these outages is software aging. Software aging phenomena refers to the accumulation of errors, usually provoking resource contention, during long running application executions, like web applications, which normally cause applications/systems hang or crash. Determining the software aging root cause failure, not the resource or resources involved in, is a huge task due to the growing day by day complexity of the systems. In this paper we present a monitoring framework based on Aspect Programming to monitor the resources used by every application component in runtime. Knowing the resources used by every component of the application we can determine which components are related to the software aging. Furthermore, we present a case study where we evaluate our approach to determine in a web application scenario, which components are involved in the software aging with promising results.

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    An integer linear programming representation for data-center power-aware management  Open access

     Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    Date: 2010-11-12
    Report

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    This work exposes how to represent a grid data-center based scheduling problem, taking the advantages of the virtualization and consolidation techniques, as a linear integer programming problem including all three mentioned factors. Although being integer linear programming (ILP) a computationally hard problem, specifying correctly its constraints and optimization function can contribute to find integer optimal solutions in relative short time. So ILP solutions can help designers and system managers not only to apply them to schedulers but also to create new heuristics and holistic functions that approximate well to the optimal solutions in a quicker way.

    Postprint (author’s final draft)

  • Maximizing revenue in grid markets using an economically enhanced resource manager

     Macias Lloret, Mario; Rana, Omer; Smith, Garry; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Concurrency and Computation: Practice and Experience
    Date of publication: 2010-09
    Journal article

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    Traditional resource management has had as its main objective the optimization of throughput, based on parameters such as CPU, memory, and network bandwidth. With the appearance of Grid markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The Self-organizing ICT Resource Management (SORMA) project aims at allowing resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA’s motivation is to achieve efficient resource utilization by maximizing revenue for resource providers and minimizing the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that the desired quality of service levels meet the expectations of market participants. This paper explains the proposed use of an economically enhanced resource manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximization across multiple service level agreements and provides an application scenario to demonstrate its usefulness and effectiveness.

  • A survey on performance management for Internet applications

     Guitart Fernández, Jordi; Torres Viñals, Jordi; Ayguade Parra, Eduard
    Concurrency and computation. Practice and experience
    Date of publication: 2010-01-01
    Journal article

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    Internet applications have become indispensable for many business and personal processes, turning the performance of these applications into a key issue. For this reason, recent research has comprehensively explored mechanisms for managing the performance of these applications, with special focus on dealing with overload situations and providing QoS guarantees to clients. This paper makes a survey on the different proposals in the literature for managing Internet applications' performance. We present a complete taxonomy that characterizes and classifies these proposals into several categories including request scheduling, admission control, service differentiation, dynamic resource management, service degradation, control theoretic approaches, works using queuing models, observation-based approaches that use runtime measurements, and overall approaches combining several mechanisms. For each work, we provide a brief description in order to provide the reader with a global understanding of the research progress in this area.

    Internet applications have become indispensable for many business and personal processes, turning the performance of these applications into a key issue. For this reason, recent research has comprehensively explored mechanisms for managing the performance of these applications, with special focus on dealing with overload situations and providing QoS guarantees to clients. This paper makes a survey on the different proposals in the literature for managing Internet applications’ performance. We present a complete taxonomy that characterizes and classifies these proposals into several categories including request scheduling, admission control, service differentiation, dynamic resource management, service degradation, control theoretic approaches, works using queuing models, observation-based approaches that use runtime measurements, and overall approaches combining several mechanisms. For each work, we provide a brief description in order to provide the reader with a global understanding of the research progress in this area.

  • Exploiting semantics and virtualization for SLA-driven resource allocation in service providers

     Ejarque, Jorge; de Palol, Marc; Goiri Presa, Iñigo; Julià, Ferran; Guitart Fernández, Jordi; Badia Sala, Rosa Maria; Torres Viñals, Jordi
    Concurrency and computation. Practice and experience
    Date of publication: 2010-04-01
    Journal article

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    Resource management is a key challenge that service providers must adequately face in order to accomplish their business goals. This paper introduces a framework, the semantically enhanced resource allocator (SERA), aimed to facilitate service provider management, reducing costs and at the same time fulfilling the QoS agreed with the customers. The SERA assigns resources depending on the information given by the service providers according to its business goals and on the resource requirements of the tasks. Tasks and resources are semantically described and these descriptions are used to infer the resource assignments. Virtualization is used to provide an application specific and isolated virtual environment for each task. In addition, the system supports fine-grain dynamic resource distribution among these virtual environments based on Service-Level Agreements. The required adaptation is implemented using agents, guarantying enough resources to each task in order to meet the agreed performance goals.

  • Self-adaptive utility-based web session management

     Poggi, N; Moreno, T; Berral Garcia, Josep Lluis; Gavaldà Mestre, Ricard; Torres Viñals, Jordi
    Computer networks
    Date of publication: 2009-07
    Journal article

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    Heterogeneous QoS resource manager with prediction  Open access

     Nou Castell, Ramon; Torres Viñals, Jordi
    International Conference on Autonomic and Autonomous Systems
    Presentation's date: 2009-04
    Presentation of work at congresses

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    As long as computers continue to get more CPU processing power, data centers need to optimize their power usage. We can do this and maintain the same complexity level as before by using virtualized environments. We can put a large number of small isolated servers, inside a large one and improve a large number of values like the wattage or power consumption, space usage, and resource usage. In this paper, we present a prototype with which we distribute resources between two virtualized servers, one with Tomcat and another with Globus, and both sharing the same host. The prototype is able to maintain the required SLA and QoS using prediction with simulation in real time. Our goal is to demonstrate that simulation can be used to improve resource managers decissions. In this paper, we use those simulations inside a shared server with several different applications using virtualization.

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    Speeding up distributed MapReduce applications using hardware accelerators  Open access

     Becerra Fontal, Yolanda; Beltran Querol, Vicenç; Carrera Perez, David; Gonzalez Tallada, Marc; Torres Viñals, Jordi; Ayguade Parra, Eduard
    International Conference on Parallel Processing
    Presentation's date: 2009-09-22
    Presentation of work at congresses

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    In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogeneous at multiple levels: from asymmetric processors, to different system architectures, operating systems and networks. Exploiting the intrinsic multi-level parallelism present in such a complex execution environment has become a challenging task using traditional parallel and distributed programming models. As a result, an increasing need for novel approaches to exploiting parallelism has arisen in these environments. MapReduce is a data-driven programming model originally proposed by Google back in 2004 as a flexible alternative to the existing models, specially devoted to hiding the complexity of both developing and running massively distributed applications in large compute clusters. In some recent works, the MapReduce model has been also used to exploit parallelism in other non-distributed environments, such as multi-cores, heterogeneous processors and GPUs. In this paper we introduce a novel approach for exploiting the heterogeneity of a Cell BE cluster linking an existing MapReduce runtime implementation for distributed clusters and one runtime to exploit the parallelism of the Cell BE nodes. The novel contribution of this work is the design and evaluation of a MapReduce execution environment that effectively exploits the parallelism existing at both the Cell BE cluster level and the heterogeneous processors level.

  • Elastic management of tasks in virtualized environments

     Goiri Presa, Iñigo; Guitart Fernández, Jordi; Torres Viñals, Jordi
    Jornadas de Paralelismo
    Presentation's date: 2009-09-16
    Presentation of work at congresses

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    Introducing virtual execution environment for application lifecycle management and SLA-driven resource distribution within service providers  Open access

     Goiri, Iñigo; Julià, Ferran; Ejarque, Jorge; de Palol, Marc; Badia Sala, Rosa Maria; Guitart Fernández, Jordi; Torres Viñals, Jordi
    IEEE International Symposium on Network Computing and Applications
    Presentation's date: 2009-07-10
    Presentation of work at congresses

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    Resource management is a key challenge that service providers must adequately face in order to ensure their profitability. This paper describes a proof-of-concept framework for facilitating resource management in service providers, which allows reducing costs and at the same time fulfilling the quality of service agreed with the customers. This is accomplished by means of virtualization. Our approach provides application-specific virtual environments and consolidates them in order to achieve a better utilization of the providers resources. In addition, it implements self-adaptive capabilities for dynamically distributing the providers resources among these virtual environments based on Service Level Agreements. The proposed solution has been implemented as a part of the Semantically-Enhanced Resource Allocator prototype developed within the BREIN European project. The evaluation shows that our prototype is able to react in very short time under changing conditions and avoid SLA violations by rescheduling efficiently the resources.

  • Predicting web server crashes: a case study in comparing prediction algorithms

     Alonso López, Javier; Torres Viñals, Jordi; Gavaldà Mestre, Ricard
    International Conference on Autonomic and Autonomous Systems
    Presentation's date: 2009-04-20
    Presentation of work at congresses

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  • Using Virtualization to Improve Software Rejuvenation

     Silva, L.M.; Alonso López, Javier; Torres Viñals, Jordi
    IEEE transactions on computers
    Date of publication: 2009-10-29
    Journal article

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  • Towards Self-Adaptable Monitoring Framework For Self-Healing

     Alonso López, Javier; Torres Viñals, Jordi; Griffith, Rean; Kaiser, Gail; Moura, Luis
    Date of publication: 2009-02
    Book chapter

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