261 research outputs found

    Polymorphism of mitochondrial genes in populations of Leporinus friderici (Bloch, 1794) : intraspecific structure and zoogeography of the neotropical fish

    Get PDF
    On the basis of faunistic and floristic inventories, various authors have developed the forest refuge theory explain species diversity in humid tropical regions. Renno et al. (1990) used electrophoretic markers to study the genetiic structure of #Leporinus friderici$ and suggested the existence of an aquatic refuge on the Guiana shield. In the present study, mitochondrial markers (RFLP) confirmed and complemented the previous electrophoretic study. Four multimorphs were evidenced, allowing the populations to be separated into sets on either side of the eastern edge of the Guiana refuge, i.e. the Kourou river region in French Guiana. (Résumé d'auteur

    Vertical Elasticity on Marathon and Chronos Mesos frameworks

    Full text link
    [EN] Marathon and Chronos are two popular Mesos frameworks that are widely used for deploying fault-tolerant services and periodic batch jobs. Marathon and Chronos provide by design mechanisms for horizontal elasticity, scaling up and down the number of job and service instances. Horizontal elasticity is appropriate when the problems that are solved are inherently parallel. However, when the problem cannot benefit from an increase of the amount of resources, vertical elasticity must be considered. This work implements on top of Marathon and Chronos Mesos frameworks, a mechanism to vary the resources associated to an executor dynamically, according to its progress and considering specific Quality of Service (QoS). The mechanism developed provides a wrapper executable and a service that takes the decision of increasing or decreasing the resources allocated to different Chronos iterations or a long-living Marathon application. The mechanism makes use of checkpointing techniques to preserve the execution of Marathon applications and leverages OpenStack Monasca for the monitoring. \footnote{The work in this article has been funded by projects BIGCLOE and EUBra-BIGSEA, BIGLOE is funded by the Spanish ``Ministerio de Econom\'ia, Industria y Competitividad" with reference number TIN2016-79951-R and EUBra-BIGSEA is funded jointly by the European Commission under the Cooperation Programme, Horizon 2020 grant agreement No 690116 and the Brazilian Ministério de Ciência, Tecnologia e Inovação (MCTI).The work in this article has been funded by projects BIGCLOE and EUBra BIGSEA, BIGLOE is funded by the Spanish "Ministerio de Economia, Industria y Competitividad" with reference number TIN2016-79951-R and EUBra-BIGSEA is funded jointly by the European Commission under the Cooperation Programme, Horizon 2020 grant agreement No 690116 and the Brazilian Ministerio de Ciencia, Tecnologia e Inovacao (MCTI).López-Huguet, S.; Natanael, I.; Brito, A.; Blanquer Espert, I. (2019). Vertical Elasticity on Marathon and Chronos Mesos frameworks. Journal of Parallel and Distributed Computing. 133:179-192. https://doi.org/10.1016/j.jpdc.2019.01.002S17919213

    How to find information on national food and nutrient consumption surveys across Europe: systematic literature review and questionnaires to selected country experts are both good strategies

    Get PDF
    The present research was conducted within the framework of the EURopean micronutrient RECommendations Aligned project. in order to identify the best practice in assessing nutrient intakes, a search strategy for collecting data from national food consumption surveys/studies in Europe was developed. Systematic literature searches were carried out on twenty-eight European and the four European Free Trade Association Countries. A questionnaire was also sent to two to five experts in each country. Systematic reviews using PubMed yielded 12 703 abstracts that were reduced to 200 studies using inclusion and exclusion criteria. Similarly, a search of ministry web sites yielded 3033 hits. and subsequently reduced to nine Surveys. Belgium, France, Germany, Ireland, Sweden, Spain and the United Kingdom were the countries with most data and Slovenia and Liechtenstein were those with the least. Seventy-eight expert questionnaires were obtained from all Countries except for Liechtenstein. Luxembourg and Slovakia. Detailed results and references are given. A systematic search and questionnaires are equally good at identifying national surveys across countries. Literature searching provides globally accessible and objective information albeit limited, whereas the questionnaire provides information that, depending upon responders, can be more complete. A combination of both strategies is recommended

    Tuberculosis treatment adherence and fatality in Spain

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>The adherence to long tuberculosis (TB) treatment is a key factor in TB control programs. Always some patients abandon the treatment or die. The objective of this study is to identify factors associated with defaulting from or dying during antituberculosis treatment.</p> <p>Methods</p> <p>Prospective study of a large cohort of TB cases diagnosed during 2006-2007 by 61 members of the Spanish Society of Pneumology and Thoracic Surgery (SEPAR). Predictive factors of completion outcome (cured plus completed treatment vs. defaulters plus lost to follow-up) and fatality (died <it>vs. </it>the rest of patients) were based on logistic regression, calculating odds ratios (OR) and 95% confidence intervals (CI).</p> <p>Results</p> <p>Of the 1490 patients included, 29.7% were foreign-born. The treatment outcomes were: cured 792 (53.2%), completed treatment 540 (36.2%), failure 2 (0.1%), transfer-out 33 (2.2%), default 27 (1.8%), death 27 (1.8%), lost to follow-up 65 (4.4%), other 4 (0.3%). Completion outcome reached 93.5% and poor adherence was associated with: being an immigrant (OR = 2.03; CI:1.06-3.88), living alone (OR = 2.35; CI:1.05-5.26), residents of confined institutions (OR = 4.79; CI:1.74-13.14), previous treatment (OR = 2.93; CI:1.44-5.98), being an injecting drug user (IDU) (OR = 9.51; CI:2.70-33.47) and treatment comprehension difficulties (OR = 2.93; CI:1.44-5.98). Case fatality was 1.8% and it was associated with the following variables: age 50 or over (OR = 10.88; CI:1.12-105.01), retired (OR = 12.26;CI:1.74-86.04), HIV-infected (OR = 9.93; CI:1.48-66.34), comprehension difficulties (OR = 4.07; CI:1.24-13.29), IDU (OR = 23.59; CI:2.46-225.99) and Directly Observed Therapy (DOT) (OR = 3.54; CI:1.07-11.77).</p> <p>Conclusion</p> <p>Immigrants, those living alone, residents of confined institutions, patients treated previously, those with treatment comprehension difficulties, and IDU patients have poor adherence and should be targeted for DOT. To reduce fatality rates, stricter monitoring is required for patients who are retired, HIV-infected, IDU, and those with treatment comprehension difficulties.</p

    Permanent Polymer Coating for in vivo MRI Visualization of Tissue Reinforcement Prostheses

    Get PDF
    The clinical advantage of MRI visualization of prostheses in soft tissue prolapses is very appealing as over 1?000?000 MRI-transparent synthetic meshes are implanted annually, and postoperative complications such as mesh shrinkage and migration are frequent. Here, the synthesis of a new material composed of a DTPA-Gd complex grafted onto a backbone of PMA via a covalent bond is described (DTPA-Gd-PMA). This new polymer is sprayed onto meshes and gives an MR signal for a long period without any significant release of Gd. In vitro cytocompatibility tests on fibroblasts show limited cytotoxicity. Microscopic investigations indicate that vital cells rapidly colonize the material. Finally, coated meshes implanted in rats are easily recognizable using an MR imaging system

    Dynamic management of virtual infrastructures

    Full text link
    The final publication is available at Springer via http://dx.doi.org/10.1007/s10723-014-9296-5Cloud infrastructures are becoming an appropriate solution to address the computational needs of scientific applications. However, the use of public or on-premises Infrastructure as a Service (IaaS) clouds requires users to have non-trivial system administration skills. Resource provisioning systems provide facilities to choose the most suitable Virtual Machine Images (VMI) and basic configuration of multiple instances and subnetworks. Other tasks such as the configuration of cluster services, computational frameworks or specific applications are not trivial on the cloud, and normally users have to manually select the VMI that best fits, including undesired additional services and software packages. This paper presents a set of components that ease the access and the usability of IaaS clouds by automating the VMI selection, deployment, configuration, software installation, monitoring and update of Virtual Appliances. It supports APIs from a large number of virtual platforms, making user applications cloud-agnostic. In addition it integrates a contextualization system to enable the installation and configuration of all the user required applications providing the user with a fully functional infrastructure. Therefore, golden VMIs and configuration recipes can be easily reused across different deployments. Moreover, the contextualization agent included in the framework supports horizontal (increase/decrease the number of resources) and vertical (increase/decrease resources within a running Virtual Machine) by properly reconfiguring the software installed, considering the configuration of the multiple resources running. This paves the way for automatic virtual infrastructure deployment, customization and elastic modification at runtime for IaaS clouds.The authors would like to thank to thank the financial support received from the Ministerio de Economia y Competitividad for the project CodeCloud (TIN2010-17804).Caballer Fernández, M.; Blanquer Espert, I.; Moltó, G.; Alfonso Laguna, CD. (2015). Dynamic management of virtual infrastructures. Journal of Grid Computing. 13(1):53-70. https://doi.org/10.1007/s10723-014-9296-5S5370131de Alfonso, C., Caballer, M., Alvarruiz, F., Molto, G., Hernández, V.: Infrastructure deployment over the cloud. In: 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, pp. 517–521. IEEE. (2011). doi: 10.1109/CloudCom.2011.77Alvarruiz, F., De Alfonso, C., Caballer, M., Hernández, V.: An energy manager for high performance computer clusters. In: 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications, pp. 231–238. (2012). doi: 10.1109/ISPA.2012.38Amazon Web Services: AWS CloudFormation. (2013). http://aws.amazon.com/es/cloudformation/Apache: Whirr (2013). http://whirr.apache.org/Blanquer, I., Brasche, G., Lezzi, D.: Requirements of scientific applications in cloud offerings. In: Proceedings of the 2012 6th Iberian Grid Infrastructure Conference, IBERGRID ’12, pp. 173–182 (2012)Bresnahan, J., Freeman, T., LaBissoniere, D., Keahey, K.: Managing appliance launches in infrastructure clouds. In: Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, TG ’11, pp. 12:1–12:7. ACM, New York (2011). doi: 10.1145/2016741.2016755Buyya, R., Ranjan, R., Calheiros, R.N.: InterCloud: utility-oriented federation of cloud computing environments for scaling of application services. Algoritm. Archit. Parallel Process. 6081, 20 (2010)Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Futur. Gener. Comput. Syst. 25(6), 599–616 (2009). doi: 10.1016/j.future.2008.12.001Caballer, M., De Alfonso, C., Alvarruiz, F., Moltó, G.: EC3: elastic cloud computing cluster. J. Comput. Syst. Sci. (2013). doi: 10.1016/j.jcss.2013.06.005Caballer, M., García, A., Moltó, G., de Alfonso, C.: Towards SLA-driven management of cloud infrastructures to elastically execute scientific applications. In: 6th Iberian Grid Infrastructure Conference (IberGrid), pp. 207–218 (2012)Carrión, J.V., Moltó, G., De Alfonso, C., Caballer, M., Hernández, V.: A generic catalog and repository service for virtual machine images. In: 2nd International ICST Conference on Cloud Computing CloudComp 2010 (2010)Cuomo, A., Modica, G., Distefano, S., Puliafito, A., Rak, M., Tomarchio, O., Venticinque, S., Villano, U.: An SLA-based broker for cloud infrastructures. J. Grid Comput 11(1), 1–25 (2012). doi: 10.1007/s10723-012-9241-4DeHaan, M.: Ansible. http://ansible.cc/ (2013)Distributed Management Task Force, Inc: Open Virtualization Format (OVF) (2010). http://dmtf.org/sites/default/files/standards/documents/DSP0243_1.1.0.pdfDistributed Management Task Force, Inc: Cloud Infrastructure Management Interface (CIMI) Model and REST Interface over HTTP Specification (2012). http://dmtf.org/sites/default/files/standards/documents/DSP0263_1.0.1.pdfEGI.eu: Seeking new horizons: EGI’s role for 2020. Tech. rep. (2012). https://documents.egi.eu/public/RetrieveFile?docid=1098&version=4&filename=EGI-1098-D230-final.pdfElmroth, E., Tordsson, J., Hernández, F.: Self-management challenges for multi-cloud architectures. Towards a service-based internet. Lect. Notes Comput. Sci. 6994, 38–49 (2011)HashiCorp: Vagrant (2013). http://www.vagrantup.com/Jacob, A.: Infrastructure in the cloud era. In: Proceedings of the 2009 International OReilly Conference Velocity (2009)Juve, G., Deelman, E.: Automating application deployment in infrastructure clouds. In: Proceedings of the 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, CLOUDCOM ’11, pp. 658–665. IEEE Computer Society, Washington DC (2011). doi: 10.1109/CloudCom.2011.102Keahey, K., Freeman, T.: Contextualization: providing one-click virtual clusters. In: 4th IEEE International Conference on eScience, pp. 301–308 (2008)Keahey, K., Freeman, T.: Architecting a large-scale elastic environment: recontextualization and adaptive cloud services for scientific computing (2012)Kecskemeti, G., Kertesz, A., Marosi, A., Kacsuk, P.: Interoperable resource management for establishing federated clouds. In: Achieving Federated and SelfManageable Cloud Infrastructures Theory and Practice, pp. 18–35 (2012). doi: 10.4018/978-1-4666-1631-8.ch002Kertesz, A., Kecskemeti, G., Oriol, M., Kotcauer, P., Acs, S., Rodríguez, M., Mercè, O., Marosi, A.C., Marco, J., Franch, X.: Enhancing federated cloud management with an integrated service monitoring approach. J. Grid Comput. 11(4), 699–720 (2013). doi: 10.1007/s10723-013-9269-0Loutas, N., Kamateri, E., Bosi, F., Tarabanis, K.: Cloud computing interoperability: the state of play. 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, pp. 752–757 (2011). doi: 10.1109/CloudCom.2011.116Marshall, P., Keahey, K., Freeman, T.: Elastic site: using clouds to elastically extend site resources. In: Proceedings of the 2010 IEEE/ACM 10th International Conference on Cluster, Cloud and Grid Computing, CCGRID ’10, pp. 43–52. IEEE Computer Society, Washington DC (2010). doi: 10.1109/CCGRID.2010.80Massie, M.L., Chun, B.N., Culler, D.E.: The ganglia distributed monitoring system: design, implementation, and experience. Parallel Comput. 30(5-6), 817–840 (2004)Mell, P., Grance, T.: The NIST definition of cloud computing. NIST Special Publication 800-145 (Final). Tech. rep. (2011). http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdfMoltó, G., Caballer, M., Romero, E., Alfonso, C.D.: Elastic memory management of virtualized infrastructures for applications with dynamic memory requirements. In: Proceedings of the International Conference on Computational Science ICCS 2013, pp. 159–168. Elsevier (2013). doi: 10.1016/j.procs.2013.05.179Morfeo: Claudia (2013). http://claudia.morfeo-project.org/wiki/index.php/Main_PageOASIS: Topology and Orchestration Specification for Cloud Applications Version 1.0 (2013). http://docs.oasis-open.org/tosca/TOSCA/v1.0/TOSCA-v1.0.htmlOCCI working group within the Open Grid Forum: Open Cloud Computing Interface Infrastructure (2011). http://ogf.org/documents/GFD.184.pdfOpscode: Chef (2013). http://www.opscode.com/chef/Pawluk, P., Simmons, B., Smit, M., Litoiu, M., Mankovski, S.: Introducing STRATOS: a cloud broker service. In: 2012 IEEE 5th International Conference on Cloud Computing, pp. 891–898 (2012). doi: 10.1109/CLOUD.2012.24Puppet Labs: IT Automation Software for System Administrators (2013). http://www.puppetlabs.com/Redl, C., Breskovic, I., Brandic, I., Dustdar, S.: Automatic SLA matching and provider selection in grid and cloud computing markets. In: Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing, GRID ’12, pp. 85–94. IEEE Computer Society, Washington (2012). doi: 10.1109/Grid.2012.18Rodero-Merino, L., Vaquero, L.M., Gil, V., Galán, F., Fontán, J., Montero, R.S., Llorente, I.M.: From infrastructure delivery to service management in clouds. Futur. Gener. Comput. Syst. 26(8), 1226–1240 (2010). doi: 10.1016/j.future.2010.02.013StratusLab: Claudia Platform (2013). http://stratuslab.eu/doku.php/claudiaSundareswaran, S., Squicciarini, A., Lin, D.: A brokerage-based approach for cloud service selection. In: Proceedings of the 2012 IEEE 5th International Conference on Cloud Computing, CLOUD ’12, pp. 558–565 (2012). doi: 10.1109/CLOUD.2012.119Telefónica Investigación y Desarrollo S.A. Unipersonal.: Telefónicas TCloud API Specification. (2010). http://www.tid.es/files/doc/apis/TCloud_API_Spec_v0.9.pdfYangui, S., Marshall, I.J., Laisne, J.P., Tata, S.: CompatibleOne: The open source cloud broker. J. Grid Comput. (2013). doi: 10.1007/s10723-013-9285-

    High-resolution tSZ cartography of clusters of galaxies with NIKA at the IRAM 30-m telescope

    Full text link
    The thermal Sunyaev-Zeldovich effect (tSZ) is a powerful probe to study clusters of galaxies and is complementary with respect to X-ray, lensing or optical observations. Previous arcmin resolution tSZ observations ({\it e.g.} SPT, ACT and Planck) only enabled detailed studies of the intra-cluster medium morphology for low redshift clusters (z<0.2z < 0.2). Thus, the development of precision cosmology with clusters requires high angular resolution observations to extend the understanding of galaxy cluster towards high redshift. NIKA2 is a wide-field (6.5 arcmin field of view) dual-band camera, operated at 100 mK100 \ {\rm mK} and containing 3300\sim 3300 KID (Kinetic Inductance Detectors), designed to observe the millimeter sky at 150 and 260 GHz, with an angular resolution of 18 and 12 arcsec respectively. The NIKA2 camera has been installed on the IRAM 30-m telescope (Pico Veleta, Spain) in September 2015. The NIKA2 tSZ observation program will allow us to observe a large sample of clusters (50) at redshift ranging between 0.5 and 1. As a pathfinder for NIKA2, several clusters of galaxies have been observed at the IRAM 30-m telescope with the NIKA prototype to cover the various configurations and observation conditions expected for NIKA2.Comment: Proceedings of the 28th Texas Symposium on Relativistic Astrophysics, Geneva, Switzerland, December 13-18, 201

    Association of sepsis-related mortality with early increase of TIMP-1/MMP-9 ratio

    Get PDF
    Objective: Higher circulating levels of tissue inhibitor of matrix metalloproteinases (TIMP)-1 at the time of severe sepsis diagnosis have been reported in nonsurviving than in surviving patients. However, the following questions remain unanswered: 1) Does TIMP-1/MMP-9 ratio differ throughout the first week of intensive care between surviving and nonsurviving patients? 2) Is there an association between TIMP-1/MMP-9 ratio and sepsis severity and mortality during such period? 3) Could TIMP-1/MMP-9 ratio during the first week be used as an early biomarker of sepsis outcome? 4) Is there an association between TIMP-1/MMP-9 ratio and coagulation state and circulating cytokine levels during the first week of intensive care in these patients? The present study sought to answer these questions. Methods: Multicenter, observational and prospective study carried out in six Spanish Intensive Care Units (ICUs) of 295 patients with severe sepsis. Were measured circulating levels of TIMP-1, MMP-9, tumour necrosis factor (TNF)-alpha, interleukin (IL)-10 and plasminogen activator inhibitor (PAI)-1 at day 1, 4 and 8. End-point was 30-day mortality. Results: We found higher TIMP-1/MMP-9 ratio during the first week in non-surviving (n = 98) than in surviving patients (n = 197) (p, 0.01). Logistic regression analyses showed that TIMP-1/MMP-9 ratio at days 1, 4 and 8 was associated with mortality. Receiver operating characteristic (ROC) curves showed that TIMP-1/MMP-9 ratio at days 1, 4 and 8 could predict mortality. There was an association between TIMP-1/MMP-9 ratio and TNF-alpha, IL-10, PAI-1 and lactic acid levels, SOFA score and platelet count at days 1, 4 and 8. Conclusions: The novel findings of our study were that non-surviving septic patients showed persistently higher TIMP-1/ MMP-9 ratio than survivors ones during the first week, which was associated with severity, coagulation state, circulating cytokine levels and mortality; thus representing a new biomarker of sepsis outcome

    Challenges and strategies in the repair of ruptured annulus fibrosus

    Get PDF
    Lumbar discectomy is the surgical procedure most frequently performed for patients suffering from low back pain and sciatica. Disc herniation as a consequence of degenerative or traumatic processes is commonly encountered as the underlying cause for the painful condition. While discectomy provides favourable outcome in a majority of cases, there are conditions where unmet requirements exist in terms of treatment, such as large disc protrusions with minimal disc degeneration; in these cases, the high rate of recurrent disc herniation after discectomy is a prevalent problem. An effective biological annular repair could improve the surgical outcome in patients with contained disc herniations but otherwise minor degenerative changes. An attractive approach is a tissue-engineered implant that will enable/stimulate the repair of the ruptured annulus. The strategy is to develop three-dimensional scaffolds and activate them by seeding cells or by incorporating molecular signals that enable new matrix synthesis at the defect site, while the biomaterial provides immediate closure of the defect and maintains the mechanical properties of the disc. This review is structured into (1) introduction, (2) clinical problems, current treatment options and needs, (3) biomechanical demands, (4) cellular and extracellular components, (5) biomaterials for delivery, scaffolding and support, (6) pre-clinical models for evaluation of newly developed cell- and material-based therapies, and (7) conclusions. This article highlights that an interdisciplinary approach is necessary for successful development of new clinical methods for annulus fibrosus repair. This will benefit from a close collaboration between research groups with expertise in all areas addressed in this review

    Multi-elastic Datacenters: Auto-scaled Virtual Clusters on Energy-Aware Physical Infrastructures

    Full text link
    [EN] Computer clusters are widely used platforms to execute different computational workloads. Indeed, the advent of virtualization and Cloud computing has paved the way to deploy virtual elastic clusters on top of Cloud infrastructures, which are typically backed by physical computing clusters. In turn, the advances in Green computing have fostered the ability to dynamically power on the nodes of physical clusters as required. Therefore, this paper introduces an open-source framework to deploy elastic virtual clusters running on elastic physical clusters where the computing capabilities of the virtual clusters are dynamically changed to satisfy both the user application's computing requirements and to minimise the amount of energy consumed by the underlying physical cluster that supports an on-premises Cloud. For that, we integrate: i) an elasticity manager both at the infrastructure level (power management) and at the virtual infrastructure level (horizontal elasticity); ii) an automatic Virtual Machine (VM) consolidation agent that reduces the amount of powered on physical nodes using live migration and iii) a vertical elasticity manager to dynamically and transparently change the memory allocated to VMs, thus fostering enhanced consolidation. A case study based on real datasets executed on a production infrastructure is used to validate the proposed solution. The results show that a multi-elastic virtualized datacenter provides users with the ability to deploy customized scalable computing clusters while reducing its energy footprint.The results of this work have been partially supported by ATMOSPHERE (Adaptive, Trustworthy, Manageable, Orchestrated, Secure, Privacy-assuring Hybrid, Ecosystem for Resilient Cloud Computing), funded by the European Commission under the Cooperation Programme, Horizon 2020 grant agreement No 777154.Alfonso Laguna, CD.; Caballer Fernández, M.; Calatrava Arroyo, A.; Moltó, G.; Blanquer Espert, I. (2018). Multi-elastic Datacenters: Auto-scaled Virtual Clusters on Energy-Aware Physical Infrastructures. Journal of Grid Computing. 17(1):191-204. https://doi.org/10.1007/s10723-018-9449-zS191204171Buyya, R.: High Performance Cluster Computing: Architectures and Systems. Prentice Hall PTR, Upper Saddle River (1999)de Alfonso, C., Caballer, M., Alvarruiz, F., Moltó, G.: An economic and energy-aware analysis of the viability of outsourcing cluster computing to the cloud. Futur. Gener. Comput. Syst. (Int. J. Grid Comput eScience) 29, 704–712 (2013). https://doi.org/10.1016/j.future.2012.08.014Williams, D., Jamjoom, H., Liu, Y.H., Weatherspoon, H.: Overdriver: handling memory overload in an oversubscribed cloud. ACM SIGPLAN Not. 46(7), 205 (2011). https://doi.org/10.1145/2007477.1952709 . http://dl.acm.org/citation.cfm?id=2007477.1952709Valentini, G., Lassonde, W., Khan, S., Min-Allah, N., Madani, S., Li, J., Zhang, L., Wang, L., Ghani, N., Kolodziej, J., Li, H., Zomaya, A., Xu, C.Z., Balaji, P., Vishnu, A., Pinel, F., Pecero, J., Kliazovich, D., Bouvry, P.: An overview of energy efficiency techniques in cluster computing systems. Clust. Comput. 16(1), 3–15 (2013). https://doi.org/10.1007/s10586-011-0171-xDe Alfonso, C., Caballer, M., Hernández, V.: Efficient power management in high performance computer clusters. In: Proceedings of the 1st International Multi-conference on Innovative Developments in ICT, Proceedings of the International Conference on Green Computing 2010 (ICGreen 2010), 39–44 (2010)OpenNebula: OpenNebula Cloud Software https://opennebula.org/ . [Online; accessed 12-June-2017]OpenStack: OpenStack Cloud Software. http://openstack.org . [Online; accessed 12 June 2017]VMWare: VMWare vCenter Server. https://www.vmware.com/products/vcenter-server.html . [Online; accessed 12 June 2017]De Alfonso, C., Blanquer, I.: Automatic consolidation of virtual machines in on-premises cloud platforms. In: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp 1070–1079 (2017). https://doi.org/10.1109/CCGRID.2017.128Chase, J.S., Irwin, D.E., Grit, L.E., Moore, J.D., Sprenkle, S.E.: Dynamic virtual clusters in a grid site manager. In: Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing, HPDC ’03, p 90. IEEE Computer Society, Washington, DC (2003). http://dl.acm.org/citation.cfm?id=822087.823392Doelitzscher, F., Held, M., Reich, C., Sulistio, A.: Viteraas: Virtual cluster as a service. In: 2011 IEEE Third International Conference on Cloud Computing Technology and Science (CloudCom), pp 652–657 (2011). https://doi.org/10.1109/CloudCom.2011.101Wei, X., Wang, H., Li, H., Zou, L.: Dynamic deployment and management of elastic virtual clusters. In: 2011 Sixth Annual Chinagrid Conference (ChinaGrid), pp 35–41 (2011). https://doi.org/10.1109/ChinaGrid.2011.31de Assuncao, M.D., di Costanzo, A., Buyya, R.: Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters. In: Proceedings of the 18th ACM International Symposium on High Performance Distributed Computing, HPDC ’09, pp 141–150. ACM, New York (2009). https://doi.org/10.1145/1551609.1551635 . http://doi.acm.org/10.1145/1551609.1551635Marshall, P., Keahey, K., Freeman, T.: Elastic site: Using clouds to elastically extend site resources. In: 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), pp 43–52 (2010). https://doi.org/10.1109/CCGRID.2010.80Niu, S., Zhai, J., Ma, X., Tang, X., Chen, W.: Cost-effective cloud hpc resource provisioning by building semi-elastic virtual clusters. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC ’13, pp 56:1–56:12. ACM, New York (2013). https://doi.org/10.1145/2503210.2503236 . http://doi.acm.org/10.1145/2503210.2503236Bialecki, A., Cafarella, M., Cutting, D., Omalley, O.: Hadoop: a framework for running applications on large clusters built of commodity hardware. Tech. rep. Apache Hadoop. http://hadoop.apache.org (2005)MIT: StarCluster Elastic Load Balancer. http://web.mit.edu/stardev/cluster/docs/0.92rc2/manual/load_balancer.htmlAppliance, C.C.S.: Creating elastic virtual clusters. http://cernvm.cern.ch/portal/elasticclusters (2015)Research project, T.G.: The games research project. http://www.green-datacenters.eu (2013)Cioara, T., Anghel, I., Salomie, I., Copil, G., Moldovan, D., Kipp, A.: Energy aware dynamic resource consolidation algorithm for virtualized service centers based on reinforcement learning. In: 2011 10th International Symposium on Parallel and Distributed Computing (ISPDC), pp 163–169 (2011). https://doi.org/10.1109/ISPDC.2011.32Farahnakian, F., Liljeberg, P., Plosila, J.: Energy-efficient virtual machines consolidation in cloud data centers using reinforcement learning. In: 2014 22nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp 500–507 (2014). https://doi.org/10.1109/PDP.2014.109Masoumzadeh, S., Hlavacs, H.: Integrating vm selection criteria in distributed dynamic vm consolidation using fuzzy q-learning. In: 2013 9th International Conference on Network and Service Management (CNSM), pp 332–338 (2013). https://doi.org/10.1109/CNSM.2013.6727854Feller, E., Rilling, L., Morin, C.: Energy-aware ant colony based workload placement in clouds. In: 2011 12th IEEE/ACM International Conference on Grid Computing (GRID), pp 26–33 (2011). https://doi.org/10.1109/Grid.2011.13Pop, C.B., Anghel, I., Cioara, T., Salomie, I., Vartic, I.: A swarm-inspired data center consolidation methodology. In: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, WIMS ’12, pp 41:1–41:7. ACM, New York (2012). https://doi.org/10.1145/2254129.2254180Marzolla, M., Babaoglu, O., Panzieri, F.: Server consolidation in clouds through gossiping. In: Proceedings of the 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WOWMOM ’11, pp 1–6. IEEE Computer Society, Washington, DC (2011). https://doi.org/10.1109/WoWMoM.2011.5986483Ghafari, S., Fazeli, M., Patooghy, A., Rikhtechi, L.: Bee-mmt: A load balancing method for power consumption management in cloud computing. In: 2013 Sixth International Conference on Contemporary Computing (IC3), pp 76–80 (2013). https://doi.org/10.1109/IC3.2013.6612165Ajiro, Y., Tanaka, A.: Improving packing algorithms for server consolidation. In: International CMG Conference, pp. 399–406. Computer Measurement Group (2007)Verma, A., Ahuja, P., Neogi, A.: pmapper: power and migration cost aware application placement in virtualized systems. In: Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, Middleware ’08, pp 243–264. Springer, New York (2008)Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28 (5), 755–768 (2012). https://doi.org/10.1016/j.future.2011.04.017Guazzone, M., Anglano, C., Canonico, M.: Exploiting vm migration for the automated power and performance management of green cloud computing systems. In: Proceedings of the First International Conference on Energy Efficient Data Centers, E2DC’12, pp 81–92. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-33645-4_8Shi, L., Furlong, J., Wang, R.: Empirical evaluation of vector bin packing algorithms for energy efficient data centers. In: 2013 IEEE Symposium on Computers and Communications (ISCC), pp 000,009–000,015 (2013). https://doi.org/10.1109/ISCC.2013.6754915Tomás, L., Tordsson, J.: Improving cloud infrastructure utilization through overbooking. In: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference on - CAC ’13, p 1. ACM Press, New York (2013). https://doi.org/10.1145/2494621.2494627Dawoud, W., Takouna, I., Meinel, C.: Elastic vm for cloud resources provisioning optimization. In: Abraham, A., Lloret Mauri, J., Buford, J., Suzuki, J., Thampi, S. (eds.) Advances in Computing and Communications, Communications in Computer and Information Science, vol. 190, pp 431–445. Springer, Berlin (2011). https://doi.org/10.1007/978-3-642-22709-7_43Tasoulas, E., Haugerund, H.R., Begnum, K.: Bayllocator: a proactive system to predict server utilization and dynamically allocate memory resources using Bayesian networks and ballooning. In: Proceedings of the 26th International Conference on Large Installation System Administration: Strategies, Tools, and Techniques, pp. 111–122. USENIX Association (2012)Hines, M.R., Gordon, A., Silva, M., Da Silva, D., Ryu, K., Ben-Yehuda, M.: Applications know best: performance-driven memory overcommit with Ginkgo. In: 2011 IEEE Third International Conference on Cloud Computing Technology and Science, pp. 130–137. IEEE. https://doi.org/10.1109/CloudCom.2011.27 (2011)Litke, A.: Manage resources on overcommitted KVM hosts. Tech. rep. IBM. http://www.ibm.com/developerworks/library/l-overcommit-kvm-resources/ (2011)De Alfonso, C., Caballer, M., Alvarruiz, F., Hernández, V.: An energy management system for cluster infrastructures. Comput. Electr. Eng. 39(8), 2579–2590 (2013). https://doi.org/10.1016/j.compeleceng.2013.05.004Moltó, G., Caballer, M, de Alfonso, C.: Automatic memory-based vertical elasticity and oversubscription on cloud platforms. Futur. Gener. Comput. Syst. 56, 1–10 (2016). https://doi.org/10.1016/j.future.2015.10.002Calatrava, A., Romero, E., Moltó, G., Caballer, M., Alonso, J.M.: Self-managed cost-efficient virtual elastic clusters on hybrid Cloud infrastructures. Futur. Gener. Comput. Syst. 61, 13–25 (2016). https://doi.org/10.1016/j.future.2016.01.018 . http://authors.elsevier.com/sd/article/S0167739X16300024 , http://linkinghub.elsevier.com/retrieve/pii/S0167739X16300024Caballer, M., Chatziangelou, M., Calatrava, A., Moltó, G., Pérez, A.: IM integration in the EGI VMOps Dashboard. In: EGI Conference 2017 and INDIGO Summit 2017 (2017)Calatrava, A., Caballer, M., Moltó, G., Pérez, A.: Virtual Elastic Clusters in the EGI LToS with EC3. In: EGI Conference 2017 and INDIGO Summit 2017 (2017)Iosup, A., Li, H., Jan, M., Anoep, S., Dumitrescu, C., Wolters, L., Epema, D.H.: The grid workloads archive. Futur. Gener. Comput. Syst. 24(7), 672–686 (2008). https://doi.org/10.1016/j.future.2008.02.003 . http://www.sciencedirect.com/science/article/pii/S0167739X08000125Nordugrid dataset, the grid workloads archive (Online; accessed 27-March-2017). http://gwa.ewi.tudelft.nl/datasets/gwa-t-3-nordugrid/report/Caballer, M., Blanquer, I., Moltó, G., de Alfonso, C: Dynamic Management of Virtual Infrastructures. J. Grid Comput. 13, 53–70 (2015). https://doi.org/10.1007/s10723-014-9296-5 . http://link.springer.com/article/10.1007/s10723-014-9296-
    corecore