{"id":5329,"date":"2019-10-26T14:52:15","date_gmt":"2019-10-26T16:52:15","guid":{"rendered":"http:\/\/nubo.ai\/?p=5329"},"modified":"2019-10-26T14:52:44","modified_gmt":"2019-10-26T16:52:44","slug":"modeling-and-simulation-of-global-and-sleep-states-in-acpi%e2%80%90compliant-energy%e2%80%90efficient-cloud-environments","status":"publish","type":"post","link":"https:\/\/nubo.ai\/?p=5329","title":{"rendered":"Modeling and simulation of global and sleep states in ACPI\u2010compliant energy\u2010efficient cloud environments."},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"5329\" class=\"elementor elementor-5329\" 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 more large\u2010scale data centers infrastructure costs increase, the more simulation\u2010based evaluations are needed to understand better the trade\u2010off between energy and performance and support the development of new energy\u2010aware resource allocation policies. Specifically, in the cloud computing field, various simulators are able to predict and measure the behavior of applications on different architectures using different resource allocation policies. Yet, only a few of them have the ability to simulate energy\u2010saving strategies, and none of them support the complete advanced configuration and power interface (ACPI) specification. ACPI defines a terminology for all possible power states of a machine and their associated power rate. The hardware industry has relied on ACPI to provide up\u2010to\u2010date standard interfaces for hardware discovery, configuration, power management, and monitoring, enabling a better understanding of the energy consumption level of different hardware states, referred to as ACPI G\u2010states, S\u2010states, and P\u2010states. In this paper, we improve the modeling and simulation of the ACPI G\/S\u2010states and show not only that these states offer different energy\u2010saving levels but also that state transitions consume energy. In addition, we model the latency to transit between two states and the effects on the turnaround time when the transitions are not performed conservatively. Furthermore, the equations provide essential information to quantify the trade\u2010off between energy consumption and performance and assist in the analysis\/decision on which strategy fits better in the environment and how it could be refined. Our expanded energy model was implemented in CloudSim and validated with simulation\u2010based experiments with a very high level of accuracy, with a standard deviation of at most 6%. Copyright \u00a9 2016 John Wiley &amp; Sons, Ltd.<\/p>\n<\/div>\n<p>https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/cpe.3839<\/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 more large\u2010scale data centers infrastructure costs increase, the more simulation\u2010based evaluations are needed to understand better the trade\u2010off between energy and performance and support the development of new energy\u2010aware resource allocation policies. Specifically, in the cloud computing field, various simulators are able to predict and measure the behavior of applications on different architectures using&#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\/5329"}],"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=5329"}],"version-history":[{"count":2,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5329\/revisions"}],"predecessor-version":[{"id":5331,"href":"https:\/\/nubo.ai\/index.php?rest_route=\/wp\/v2\/posts\/5329\/revisions\/5331"}],"wp:attachment":[{"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5329"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5329"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nubo.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5329"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}