{"id":5333,"date":"2019-10-26T14:54:00","date_gmt":"2019-10-26T16:54:00","guid":{"rendered":"http:\/\/nubo.ai\/?p=5333"},"modified":"2019-10-26T14:54:35","modified_gmt":"2019-10-26T16:54:35","slug":"e-eco-performance-aware-energy-efficient-cloud-data-center-orchestration","status":"publish","type":"post","link":"https:\/\/nubo.ai\/?p=5333","title":{"rendered":"E-eco: Performance-aware energy-efficient cloud data center orchestration"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"5333\" class=\"elementor elementor-5333\" data-elementor-settings=\"[]\">\n\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t<section class=\"elementor-element elementor-element-67fb4b02 elementor-section-boxed elementor-section-height-default elementor-section-height-default elementor-section elementor-top-section\" data-id=\"67fb4b02\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t<div class=\"elementor-element elementor-element-16f4ec7 elementor-column elementor-col-100 elementor-top-column\" data-id=\"16f4ec7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap  elementor-element-populated\">\n\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t<div class=\"elementor-element elementor-element-100db479 elementor-widget elementor-widget-text-editor\" data-id=\"100db479\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\"><p><!-- wp:paragraph --><\/p>\n<div>\n<p>The high\u00a0<a title=\"Learn more about Energy Consumption from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/energy-consumption\">energy consumption<\/a>\u00a0of data centers has been a recurring issue in recent research. In\u00a0<a title=\"Learn more about Cloud Environment from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/cloud-environment\">cloud environments<\/a>, several techniques are being used that aim for energy efficiency, ranging from scaling the processors frequency, to the use of sleep states during idle periods and the consolidation of\u00a0<a title=\"Learn more about virtual machine from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/virtual-machine\">virtual machines<\/a>. Although these techniques enable a reduction in\u00a0<a title=\"Learn more about Electric Power Utilization from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/engineering\/electric-power-utilization\">power consumption<\/a>, they usually impact application performance. In this paper, we present an orchestration of different energy-savings techniques in order to improve the trade-off between energy consumption and application performance. To this end, we implemented the Energy-Efficient Cloud Orchestrator &#8211; e-eco &#8211; a management system that acts along with the cloud load balancer deciding which technique to apply during execution. To evaluate e-eco, tests were carried out in a real environment using scale-out applications on a dynamic\u00a0<a title=\"Learn more about Cloud Infrastructure from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/cloud-infrastructure\">cloud infrastructure<\/a>, taking into account transactions per second as a\u00a0<a title=\"Learn more about Performance Metric from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/performance-metric\">performance metric<\/a>. In addition to the empirical experiments, we also analyzed the\u00a0<a title=\"Learn more about Scalability from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/computer-science\/scalability\">scalability<\/a>\u00a0of our approach with an enhanced version of the CloudSim simulator. Results of our evaluations demonstrated that e-eco is able to reduce energy consumption up to 25% compared to power-agnostic approaches at a cost of only 6% of extra SLA violations. When compared to existing power-aware approaches, e-eco achieved the best trade-off between performance and energy-savings. These results showed that our orchestration approach showed a better balance in regard to a more energy-efficient data center with smaller impact on application performance when compared with other works presented in the literature.<\/p>\n<\/div>\n<p>https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1084804516302569<\/p>\n<p><!-- \/wp:paragraph --><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"The high\u00a0energy consumption\u00a0of data centers has been a recurring issue in recent research. In\u00a0cloud environments, several techniques are being used that aim for energy efficiency, ranging from scaling the processors frequency, to the use of sleep states during idle periods and the consolidation of\u00a0virtual machines. Although these techniques enable a reduction in\u00a0power consumption, they usually&#8230;","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","footnotes":""},"categories":[49],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5333"}],"collection":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5333"}],"version-history":[{"count":2,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5333\/revisions"}],"predecessor-version":[{"id":5336,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5333\/revisions\/5336"}],"wp:attachment":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5333"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5333"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5333"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}