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Anton Beloglazov f752fd47e5 Added the Requests library, removed sniffer
2012-09-19 14:45:26 +10:00

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<title>OpenStack Neat: A Framework for Dynamic Consolidation of Virtual Machines in OpenStack Clouds</title>
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<div id="header">
<h1 class="title">OpenStack Neat: A Framework for Dynamic Consolidation of Virtual Machines in OpenStack Clouds</h1>
<h2 class="author">Anton Beloglazov</h2>
<h2 class="author">Rajkumar Buyya</h2>
<h3 class="date">14th of August 2012</h3>
</div>
<div id="TOC">
<ul>
<li><a href="#summary"><span class="toc-section-number">1</span> Summary</a></li>
<li><a href="#release-note"><span class="toc-section-number">2</span> Release Note</a></li>
<li><a href="#rationale"><span class="toc-section-number">3</span> Rationale</a></li>
<li><a href="#user-stories"><span class="toc-section-number">4</span> User stories</a></li>
<li><a href="#assumptions"><span class="toc-section-number">5</span> Assumptions</a></li>
<li><a href="#design"><span class="toc-section-number">6</span> Design</a><ul>
<li><a href="#components"><span class="toc-section-number">6.1</span> Components</a><ul>
<li><a href="#global-manager"><span class="toc-section-number">6.1.1</span> Global Manager</a><ul>
<li><a href="#vm-placement."><span class="toc-section-number">6.1.1.1</span> VM Placement.</a></li>
<li><a href="#rest-api."><span class="toc-section-number">6.1.1.2</span> REST API.</a></li>
<li><a href="#switching-hosts-on-and-off."><span class="toc-section-number">6.1.1.3</span> Switching Hosts On and Off.</a></li>
</ul></li>
<li><a href="#local-manager"><span class="toc-section-number">6.1.2</span> Local Manager</a><ul>
<li><a href="#underload-detection."><span class="toc-section-number">6.1.2.1</span> Underload Detection.</a></li>
<li><a href="#overload-detection."><span class="toc-section-number">6.1.2.2</span> Overload Detection.</a></li>
<li><a href="#vm-selection."><span class="toc-section-number">6.1.2.3</span> VM Selection.</a></li>
</ul></li>
<li><a href="#data-collector"><span class="toc-section-number">6.1.3</span> Data Collector</a></li>
</ul></li>
<li><a href="#data-stores"><span class="toc-section-number">6.2</span> Data Stores</a><ul>
<li><a href="#central-database"><span class="toc-section-number">6.2.1</span> Central Database</a></li>
<li><a href="#local-file-based-data-store"><span class="toc-section-number">6.2.2</span> Local File-Based Data Store</a></li>
</ul></li>
<li><a href="#configuration-file"><span class="toc-section-number">6.3</span> Configuration File</a></li>
</ul></li>
<li><a href="#implementation"><span class="toc-section-number">7</span> Implementation</a><ul>
<li><a href="#libraries"><span class="toc-section-number">7.1</span> Libraries</a></li>
<li><a href="#global-manager-1"><span class="toc-section-number">7.2</span> Global Manager</a></li>
<li><a href="#local-manager-1"><span class="toc-section-number">7.3</span> Local Manager</a></li>
<li><a href="#data-collector-1"><span class="toc-section-number">7.4</span> Data Collector</a></li>
</ul></li>
<li><a href="#testdemo-plan"><span class="toc-section-number">8</span> Test/Demo Plan</a></li>
<li><a href="#unresolved-issues"><span class="toc-section-number">9</span> Unresolved issues</a></li>
<li><a href="#bof-agenda-and-discussion"><span class="toc-section-number">10</span> BoF agenda and discussion</a></li>
<li><a href="#references"><span class="toc-section-number">11</span> References</a></li>
</ul>
</div>
<h1 id="summary"><a href="#TOC"><span class="header-section-number">1</span> Summary</a></h1>
<p>OpenStack Neat is a project intended to provide an extension to OpenStack implementing dynamic consolidation of Virtual Machines (VMs) using live migration. The major objective of dynamic VM consolidation is to improve the utilization of physical resources and reduce energy consumption by re-allocating VMs using live migration according to their real-time resource demand and switching idle hosts to the sleep mode. For example, assume that two VMs are placed on two different hosts, but the combined resource capacity required by the VMs to serve the current load can be provided by just one of the hosts. Then, one of the VMs can be migrated to the host serving the other VM, and the idle host can be switched to a low power mode to save energy.</p>
<p>Apart from consolidating VMs, the system should be able to react to increases in the resource demand and deconsolidate VMs when necessary to avoid performance degradation. In general, the problem of dynamic VM consolidation can be split into 4 sub-problems:</p>
<ol style="list-style-type: decimal">
<li>Deciding when a host is considered to be underloaded, so that all the VMs should be migrated from it, and the host should be switched to a low power mode, such as the sleep mode.</li>
<li>Deciding when a host is considered to be overloaded, so that some VMs should be migrated from the host to other hosts to avoid performance degradation.</li>
<li>Selecting VMs to migrate from an overloaded host out of the full set of the VMs currently served by the host.</li>
<li>Placing VMs selected for migration to other active or re-activated hosts.</li>
</ol>
<p>This work is conducted within the <a href="http://www.cloudbus.org/">Cloud Computing and Distributed Systems (CLOUDS) Laboratory</a> at the University of Melbourne. The problem of dynamic VM consolidation considering Quality of Service (QoS) constraints has been studied from the theoretical perspective and algorithms addressing the sub-problems listed above have been proposed <span class="citation">[1], [2]</span>. The algorithms have been evaluated using <a href="http://code.google.com/p/cloudsim/">CloudSim</a> and real-world workload traces collected from more than a thousand <a href="https://www.planet-lab.org/">PlanetLab</a> VMs hosted on servers located in more than 500 places around the world.</p>
<p>The aim of the OpenStack Neat project is to provide an extensible framework for dynamic consolidation of VMs based on the OpenStack platform. The framework should provide an infrastructure enabling the interaction of components implementing the 4 decision-making algorithms listed above. The framework should allow configuration-driven switching of different implementations of the decision-making algorithms. The implementation of the framework will include the algorithms proposed in our previous works <span class="citation">[1], [2]</span>.</p>
<h1 id="release-note"><a href="#TOC"><span class="header-section-number">2</span> Release Note</a></h1>
<p>The functionality covered by this project will be implemented in the form of services separate from the core OpenStack services. The services of this project will interact with the core OpenStack services using their public APIs. It will be required to create a new Keystone user within the <code>service</code> tenant. The project will also require a new MySQL database for storing historical data on the resource usage by VMs. The project will provide a script for automated initialization of the database. The services provided by the project will need to be run on the management as well as compute hosts.</p>
<h1 id="rationale"><a href="#TOC"><span class="header-section-number">3</span> Rationale</a></h1>
<p>The problem of data center operation is high energy consumption, which has risen by 56% from 2005 to 2010, and in 2010 accounted to be between 1.1% and 1.5% of the global electricity use <span class="citation">[3]</span>. Apart from high operating costs, this results in substantial carbon dioxide (CO<sub>2</sub>) emissions, which are estimated to be 2% of the global emissions <span class="citation">[4]</span>. The problem has been partially addressed by improvements in the physical infrastructure of modern data centers. As reported by the <a href="http://opencompute.org/">Open Compute Project</a>, Facebook’s Oregon data center achieves a Power Usage Effectiveness (PUE) of 1.08, which means that approximately 93% of the data center’s energy consumption are consumed by the computing resources. Therefore, now it is important to focus on the resource management aspect, i.e. ensuring that the computing resources are efficiently utilized to serve applications.</p>
<p>Dynamic consolidation of VMs has been shown to be efficient in improving the utilization of data center resources and reducing energy consumption, as demonstrated by numerous studies <span class="citation">[5–16]</span>. In this project, we aim to implement an extensible framework for dynamic VM consolidation specifically targeted at the OpenStack platform.</p>
<h1 id="user-stories"><a href="#TOC"><span class="header-section-number">4</span> User stories</a></h1>
<ul>
<li>As a Cloud Administrator or Systems Integrator, I want to support dynamic VM consolidation to improve the utilization of the data center’s resources and reduce energy consumption.</li>
<li>As a Cloud Administrator, I want to minimize the price of the service provided to the consumers by reducing the operating costs through the reduced energy consumption.</li>
<li>As a Cloud Administrator, I want to decrease the carbon dioxide emissions into the environment by reducing energy consumption by the data center’s resources.</li>
<li>As a Cloud Administrator, I want to provide QoS guarantees to the consumers, while applying dynamic VM consolidation.</li>
<li>As a Cloud Service Consumer, I want to pay the minimum price for the service provided through the minimized energy consumption of the computing resources.</li>
<li>As a Cloud Service Consumer, I want to use Green Cloud resources, whose provider strives to reduce the impact on the environment in terms of carbon dioxide emissions.</li>
</ul>
<h1 id="assumptions"><a href="#TOC"><span class="header-section-number">5</span> Assumptions</a></h1>
<ul>
<li>Nova uses a <em>shared storage</em> for storing VM instance data, thus supporting <em>live migration</em> of VMs. For example, a shared storage can be provided using Network File System (NFS), or GlusterFS as described in <span class="citation">[17]</span>.</li>
<li>All the compute hosts must have a user, which is enabled to switch the machine into the sleep mode, which is also referred to as “Suspend to RAM”. This user is used by the global controller to connect to the compute hosts using SSH and switch them into the sleep mode when necessary.</li>
</ul>
<h1 id="design"><a href="#TOC"><span class="header-section-number">6</span> Design</a></h1>
<div class="figure">
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" alt="The deployment diagram" /><p class="caption">The deployment diagram</p>
</div>
<p>The system is composed of a number of components and data stores, some of which are deployed on the compute hosts, and some on the management host (Figure 1). In the following sections, we discuss the design and interaction of the components, as well as the specification of the data stores, and available configuration options.</p>
<h2 id="components"><a href="#TOC"><span class="header-section-number">6.1</span> Components</a></h2>
<p>As shown in Figure 1, the system is composed of three main components:</p>
<ul>
<li><em>Global manager</em> – a component that is deployed on the management host and makes global management decisions, such as mapping VM instances on hosts, and initiating VM migrations.</li>
<li><em>Local manager</em> – a component that is deployed on every compute host and makes local decisions, such as deciding that the host is underloaded or overloaded, and selecting VMs to migrate to other hosts.</li>
<li><em>Data collector</em> – a component that is deployed on every compute host and is responsible for collecting data about the resource usage by VM instances, as well as storing these data locally and submitting the data to the central database.</li>
</ul>
<h3 id="global-manager"><a href="#TOC"><span class="header-section-number">6.1.1</span> Global Manager</a></h3>
<div class="figure">
<img 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g+2RCJxJ+8sL0cymZTjXzwejxwVVTdq5QKz2ezdd98tP/KPBYDK/xra0MCXDADwbY/6xgg7AEAB6zW+DAAAAED9/FlBEwAAAGDt8X+8AYBve9Q9+joBAArIedk8AAAAACwXqRMAoIBbt27JsnwJPQAAAACUj9QJALAE3i4PAAAAYAVInQAABUxNTckyqRMAAACAFSB1AgAUMD09Lcs7d+6kQQAAAAAsF6kTAKCA3/zmN7Lc0tJCgwAAAABYLlInAECudDptmqb8+OCDD9ImAAAAAJaL1AkAkOvSpUuyrOu6zWajTQAAAAAsF6kTACDX6dOnZfmVV16hQQAAAACsAKkTAOAvJJPJaDQqP+7evZs2AQAAALACpE4AgL9w9OhRWfZ4PHa7nTYBAAAAsAKkTgCA/5fJZCKRiPz42muv0SYAAAAAVoYJYgEA/6+rq0uWNU1zuVy0ydrzer2iMDIy4nA4aBAAAADUKFInAMD/icVi1o5O7777Lm2yLuRdGBoaInUCAABA7WKEHQBAURQlm80+//zz8qOu6263m2YBAAAAsGKkTgAARVGU/v7+VColP46OjtbohcRisYaGhoaGhtq9F+HvVX9HJ6/X29DQYBgGP0EAAADIxwg7AIBiGEYwGJQfQ6GQ0+ms0Wv5/PPPa/12yHmdqp91SCYAAACQg9QJADa6ZDLp8/nkR03TDh06VLuXMzU1xT1dG+l0mkbAnbD2kquhsBUAwLc9ykfqBAAbWjqd3rVrl/yoqmo0GrXZavhfh/J732QyGZGbOBwOu91ewXMQNRfrL5bNZm/duqUoyp10KBOVrKyGdDqdyWTsdnvBEXxirSiXbpmvvvpquQe9w6tGnbHm3fwdAgB826MuMa8TAGxc6XRa0zTrdE4ffPBBjb40LZlM5kzn1PC9ZDKZc9V9fX0NDQ2bNm1qbGxsbGzctGlTQ0OD1+uNx+PLPa48iqj5+PHjzc3NouacOrPZrGEYbW1td999tzhuQ0PD4OBgiTpzzlwcYnBwsLm5WVSyefPmvr6+WCwmVllPpmBtmUzG6/U+8MADjY2NfX191s0ymczg4ODmzZvFWtkymzdvNgwjm81aNxbTObW2tsrfJsUh8n+VjMVibW1tDQ0NstqGhoa2trbjx4/n1AkAAID6Q+oEAPVAdk4pX37kFAgE6v69dRMTE5qmWSexkiKRiKZpx48fX1nN2WzW6/X29PSYpplTp+hR9eKLL/p8vmg0at3L7/fnpD9L3jK/3y8PkUqlgsFga2vr4OBgOc9AV1dXwb5g6XR627Ztfr/f+jzIQ/h8vr179y43JMpms4ODg62trTmXrChKNBrt6enZu3fvCp5bAAAA1BBSJwCobbFYrLm5+fTp08vdKz9yGhgYqN12cDgc4XA4EAjIJflvgovFYh0dHeKqNU0Lh8OmaSYSiXA47PF4xDY9PT0reyPbiy++KOIVj8czPj6uaZpc5fV6BwcHRdyjadr4+Lg8nKIowWCwnPAlk8nIW6aqaigUMk3TNM1QKKSqqt/vf/vttwvuKM9kampKnIOu6x6Pp6WlRSzPZrPWmgOBwOTkpGma1saMRqMnT56UH48cORIOh2XNHo9HNPWRI0esDeL3+0VZ13V5O3Rdl3Vu27aNHk8AAAD1bBEASrL+eZxIJFb7cIlEQh7O4/HUX3tW8AInJyetf/aXv2MoFMr5tyAQCNRf8+avlc2l6/rCwkLOWhmyqKqav7YYazPqum79GRkfH7euVVV1cnJSrp2bm1NVVawKhUIF67TWFg6H5XLTNK3bW6vKfxjkj7Cqqqqq5v8UT05Oyn2tZ7i4uLiwsNDb21usSWXN4XC4xI3Ib+3x8XF5wvn7YuPgN1IA4NsedY++TgBQe0T/ptbWVjnS6urVq+XsKKb16enpyYmcarqXU/mNJpvrww8/zJ8xfWBgQEQhqVTq3LlzKzjEpUuXrFNl79mzx7r2ypUr1gGMDofj6aefFuVy3rv31ltvyYjK5XJZVzkcjg8++GDJGlKp1KlTp/In875586a4cE3TcoZY2my2oaEh+TF/nqlijh49KiOnCxcu5LR2e3u7PGF5XQAAAKg/pE4AUEuSyWRbW5s1bxJyPhYUj8e3bduWM61POBzeCJGToigfffSRKOi6Xuy9bIcPHxaF8+fPL7d+a69AwWazWcfZ5cc9coybmPiphHQ6LW/x7t278zdwu93W7k4Fqara3t6ev9zr9X7zzTeLi4tffvll/lprW3399ddltoZ8zF555ZWCr0R89NFH5aNbfpgFAACA2kLqBAC1IZlMer3exsbG/LmZhRLJRSaT6evry5nISQz42jjvr71+/booHDhwoNg2zzzzjCiU2XfMat++ffkLt2/fLgr5mZSiKA899JAoFLun1jsoyzkdnaTOzs7SJy+7Vi2XzM5u3rxZzvbWs33iiScKbmO322W1165d4wccAACgLtloAgCocslk8ujRowVfPWaVSqXktNlSNps9d+6cz+fLWa7rumEY+dvXsXKCpB//+MeiUE7fsRyy41L5a5uamsqs/I9//OOS2+zcubP0yRfMxayPysWLF2/cuDE1NXX16tUVtIBkDUBLvKFvbm5OFG7fvs2POQAAQF0idQKANfXdd9/t2rXrypUrShnjqsrMm4R4PG7tBSPypv7+fmv/JiEUCh06dKjguKc6JmOUYn2FcmSz2Qo20Q9/+MM72T0ej69q48Tj8RdeeOFOkiYra9+lMp9eAAAA1CVSJwBYU/fcc4+InBRF+f3vf19ss2XlTcLMzIwoZDKZ06dPHzt2LD9v0jRtbGwsf4KhDeXee++t3ZNfcvKmFTh+/Lh1gnmPxyN6RblcLtFWjY2NK6684NBCAAAAbBCkTgBQXVaQNwnXr1+Px+PvvfdeMBjMX6uq6vDwcGdn50br4iRpmib68kxNTZWTu61lQ1knHS9o69atopCfJN650dFRUdB1fXR09M5DSevIQcMw+KEGAADYsEidAKBarDhvEiKRSLF9N+aQuhzbt29fcgSZfEfbkjFQxc+t9AZywqkSZGe3ZbG+He/f/u3fKtIPzvrau2QyucH71gEAAGxkvMMOANaffD9dZSfBUVU1EAjMz893d3dv8MhJUZSHH35YFE6fPl1sm48++kgUloyB1vdpKbj8xIkTK6jt008/lU9LwRmvYrHYcuu0zlIvgzwAAABsQKROALCe0un0auRNmqaFw+HZ2dmBgQFrx5MNJZvNWj8+88wzohCNRjOZTMFdZHBT+nVva8/pdMoZnc6fP5+/QSwWW9nguyXfH/fyyy8vWUl+Nys5nVOx3bPZbF9f38TExJJz6gMAAKB2kToBwLq5ffv2Aw88UNm8qbe3d3Jy8ssvv/R6vRu8f9O5c+esH91utxw39/Of/zwnk1IUZXBwUAQ3qqp2dnZW2+UcPnxYFHp6enK6O6XT6eeff35l1cr+TalUKqdbUzab9Xq91mGJ09PT1g1knya/35/TnkNDQ6JgmmbBqZ36+/uDwWBHR4eu6/n3AgAAAPWB1AkA1s1///d/V7bCM2fOjIyMuN3uDduk1imE+vv7DcMwDENmNO+++64oRKPRvXv3io426XQ6Ho/39fX5/X6xdnh4uAoDO5k6KYqya9euwcHBWCwWi8UGBwc1TUulUit7W9xDDz0ke1G9/PLLhmFkMplkMmkYxpYtWyKRiK7rgUBAbHDu3LmJiQnZnj/72c/yW1veCHk+Pp+vr68vFouJmicmJrxer5jzXlXVaDTK8E8AAIB6xe95AFA/Lly48E//9E8bvBF6e3tFopFKpXw+n6Io4XBYpFFut3t8fLyjo0NRlGg0Go1G83cPhUJer7cKr8vhcExOTra2topL8/v9MiZTFGVycvLmzZui35yu6+VXa7fbh4eHRUOZpikKkq7rFy5cuHjxoviYSqVE6y0uLiqK8sQTT8gt5ZsTZeudOXPG4XCI5cFgsOCrFS9evGidBAoAAAB1hr5OAFA/mCJHUZTh4eESsUt7e/vc3FzBDTRNSyQS3d3dVXtpbrc7kUj09vbKoYK6rodCoUQiYe3gttwcx+v1jo+Pyx5PUiAQuHDhgs1ma29vD4VC+Ts6HA7TNPN3FGw228jIyOTkZMENdF03TbPg/OUAAACoGw3if1cCQIm/SOXEQ4lEYrVfgp5MJhsbG0XZ4/EUnBGmplkvcDXwrS6k02k5SVOxFCaZTF67dk1RlKamptV+sCtOTIhunSp+cHBQ9H4KBAIDAwMrezivXbt2+/btlpYWh8ORPw+9GFuX01bZbPbWrVvXrl1ramoquJd1G9HadrudLk5QFKWhoYHvLgDg2x71jRF2ALBu7r777oWFhcrWmU6n+XteURSHw7FkOzidzpoLm6T8cOeTTz4RBfm2vuVaskEKrrXZbEvuWM42AAAAqD+kTgCwbv7u7/4umUyKXjnxeHxmZub69et3+Eq7TCZD6lSXJiYmzp49e/XqVUVRPvvss5wZuLPZrJym6tFHH6W5AAAAUA1InQBgnYleOXKCG/ESsXQ6PTU1tYIcampqih4ldampqUk+CXv37hUzLomPyWRy//79oqzresExbgAAAMDaI3UCgKpjt9vtdrsMjwzDkNPi3LhxY2pq6vLly2LSonwzMzM0YF1yOp0ej0cET9FodMeOHdu3b3/44Yf/8Ic/yNfDqar64Ycf0lYAAACoEqROAFALX9aWaXHES9ZkDnX79u3z589fvXrVNE1FUa5fv05z1auRkRFFUUTwZJqmuONWFy9epKMTAAAAqugPGZoAAGry69uSQ3m9XrFQvGIM9crhcBiGMTQ09Pbbb587d072d9M07dVXX92/fz+REwAAAKrrzxaaAADqBjM6bZC7PDIyIvo9AQAAANXsLpoAANbSd999t2vXLlH+yU9+QoMAAAAAqFekTgCwpu65554rV66IssPhoEEAAAAA1CtSJwAAAAAAAFQeqRMAAAAAAAAqj9QJAAAAAAAAlUfqBAAAA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" alt="The global manager: a sequence diagram" /><p class="caption">The global manager: a sequence diagram</p>
</div>
<p>The global manager is deployed on the management host and is responsible for making VM placement decisions and initiating VM migrations. It exposes a REST web service, which accepts requests from local managers. The global manager processes only one type of requests – reallocation of a set of VM instances. As shown in Figure 2, once a request is received, the global manager invokes a VM placement algorithm to determine destination hosts to migrate the VMs to. Once a VM placement is determined, the global manager submits a request to the Nova API to migrate the VMs. The global manager is also responsible for switching idle hosts to the sleep mode, as well as re-activating hosts when necessary.</p>
<h4 id="vm-placement."><a href="#TOC"><span class="header-section-number">6.1.1.1</span> VM Placement.</a></h4>
<p>The global manager is agnostic of a particular implementation of the VM placement algorithm in use. The VM placement algorithm to use can be specified in the configuration file described later using the <code>algorithm_vm_placement</code> option. A VM placement algorithm can call the Nova API to obtain the information about host characteristics and current VM placement. If necessary, it can also query the central database to obtain the historical information about the resource usage by the VMs.</p>
<h4 id="rest-api."><a href="#TOC"><span class="header-section-number">6.1.1.2</span> REST API.</a></h4>
<p>The global manager exposes a REST web service (REST API) for accepting VM migration requests from local managers. The service URL is defined according to configuration options defined in <code>/etc/neat/neat.conf</code>, which is discussed further in the paper. The two relevant options are:</p>
<ul>
<li><code>global_manager_host</code> – the name of the host running the global manager;</li>
<li><code>global_manager_port</code> – the port of the REST web service exposed by the global manager.</li>
</ul>
<p>The service URL is composed as follows:</p>
<pre><code>http://&lt;global_manager_host&gt;:&lt;global_manager_port&gt;/</code></pre>
<p>Since the global manager processes only a single type of requests, it exposes only one resource: <code>/</code>. The resource is accessed using the <code>PUT</code> method, which initiates a VM reallocation process. This service requires the following parameters:</p>
<ul>
<li><code>admin_tenant_name</code> – the admin tenant name of Neat’s admin user registered in Keystone. In this context, this parameter is not used to authenticate in any OpenStack service, rather it is used to authenticate the client making a request as being allowed to access the web service.</li>
<li><code>admin_user</code> – the admin user name of Neat’s admin user registered in Keystone. In this context, this parameter is not used to authenticate in any OpenStack service, rather it is used to authenticate the client making a request as being allowed to access the web service.</li>
<li><code>admin_password</code> – the admin password of Neat’s admin user registered in Keystone. In this context, this parameter is not used to authenticate in any OpenStack service, rather it is used to authenticate the client making a request as being allowed to access the web service.</li>
<li><code>vm_uuids</code> – a coma-separated list of UUIDs of the VMs required to be migrated.</li>
<li><code>reason</code> – an integer specifying the resource for migration: 0 – underload, 1 – overload.</li>
</ul>
<p>If the provided credentials are correct and the <code>vm_uuids</code> parameter includes a list of UUIDs of existing VMs in the correct format, the service responses with the HTTP status code <code>200 OK</code>.</p>
<p>The service uses standard HTTP error codes to response in cases of errors detected. The following error codes are used:</p>
<ul>
<li><code>400</code> – bad input parameter: incorrect or missing parameters;</li>
<li><code>401</code> – unauthorized: user credentials are missing;</li>
<li><code>403</code> – forbidden: user credentials do not much the ones specified in the configuration file;</li>
<li><code>405</code> – method not allowed: the request is made with a method other than the only supported <code>PUT</code>;</li>
<li><code>422</code> – unprocessable entity: one or more VMs could not be found using the list of UUIDs specified in the <code>vm_uuids</code> parameter.</li>
</ul>
<h4 id="switching-hosts-on-and-off."><a href="#TOC"><span class="header-section-number">6.1.1.3</span> Switching Hosts On and Off.</a></h4>
<p>One of the main features required to be supported by the hardware in order to take advantage of dynamic VM consolidation to save energy is <a href="http://en.wikipedia.org/wiki/Wake-on-LAN">Wake-on-LAN</a>. This technology allows a computer being in the sleep (Suspend to RAM) mode to be re-activated by sending a special packet over network. This technology has been introduced in 1997 by the Advanced Manageability Alliance (AMA) formed by Intel and IBM, and is currently supported by most of the modern hardware.</p>
<p>Once the required VM migrations are completed, the global manager connects to the source host and switches into in the Suspend to RAM mode. Switching to the Suspend to RAM mode can be done, for example, using programs included in the <code>pm-utils</code> package. To check whether the Suspend to RAM mode is supported, the following command can be used:</p>
<pre class="sourceCode Bash"><code class="sourceCode bash">pm-is-supported --suspend</code></pre>
<p>The Suspend to RAM mode is supported if the command returns 0, otherwise it is not supported. In this case, the Suspend to RAM mode can be replaced with the Standby or Suspend to Disk (Hibernate) modes. The following command can be used to switch the host into the Suspend to RAM mode:</p>
<pre class="sourceCode Bash"><code class="sourceCode bash">pm-suspend</code></pre>
<p>To re-activate a host using the Wake-on-LAN technology, it is necessary to send a special packet, called the <em>magic packet</em>. This can be done using the <code>ether-wake</code> program as follows:</p>
<pre class="sourceCode Bash"><code class="sourceCode bash">ether-wake <span class="kw">&lt;</span>mac address<span class="kw">&gt;</span></code></pre>
<p>Where <code>&lt;mac address&gt;</code> is replaced with the actual MAC address of the host.</p>
<h3 id="local-manager"><a href="#TOC"><span class="header-section-number">6.1.2</span> Local Manager</a></h3>
<div class="figure">
<img 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" alt="The local manager: an activity diagram" /><p class="caption">The local manager: an activity diagram</p>
</div>
<p>The local manager component is deployed on every compute host and is invoked periodically to determine when it necessary to reallocate VM instances from the host. A high-level view of the workflow performed by the local manager is shown in Figure 3. First of all, it reads from the local storage the historical data on the resource usage by VMs stored by the data collector described in the next section. Then, the local manager invokes the specified in the configuration underload detection algorithm to determine whether the host is underloaded. If the host is underloaded, the local manager sends a request to the global manager’s REST API to migrate all the VMs from the host and switch the host to the sleep mode.</p>
<p>If the host is not underloaded, the local manager proceeds to invoking the specified in the configuration overload detection algorithm. If the host is overloaded, the local manager invokes the configured VM selection algorithm to select the VMs to migrate from the host. Once the VMs to migrate from the host are selected, the local manager sends a request to the global manager’s REST API to migrate the selected VMs from the host.</p>
<p>Similarly to the global manager, the local manager can be configured to use specific underload detection, overload detection, and VM selection algorithm using the configuration file discussed further in the paper.</p>
<h4 id="underload-detection."><a href="#TOC"><span class="header-section-number">6.1.2.1</span> Underload Detection.</a></h4>
<p>Underload detection is done by a specified in the configuration underload detection algorithm (<code>algorithm_underload_detection</code>). The algorithm has a pre-defined interface, which allows substituting different implementations of the algorithm. The configured algorithm is invoked by the local manager and accepts historical data on the resource usage by VMs running on the host as an input. An underload detection algorithm returns a decision of whether the host is underloaded.</p>
<h4 id="overload-detection."><a href="#TOC"><span class="header-section-number">6.1.2.2</span> Overload Detection.</a></h4>
<p>Overload detection is done by a specified in the configuration overload detection algorithm (<code>algorithm_overload_detection</code>). Similarly to underload detection, all overload detection algorithms implement a pre-defined interface to enable configuration-driven substitution of difference implementations. The configured algorithm is invoked by the local manager and accepts historical data on the resource usage by VMs running on the host as an input. An overload detection algorithm returns a decision of whether the host is overloaded.</p>
<h4 id="vm-selection."><a href="#TOC"><span class="header-section-number">6.1.2.3</span> VM Selection.</a></h4>
<p>If a host is overloaded, it is necessary to select VMs to migrate from the host to avoid performance degradation. This is done by a specified in the configuration VM selection algorithm (<code>algorithm_vm_selection</code>). Similarly to underload and overload detection algorithms, different VM selection algorithm can by plugged in according to the configuration. A VM selection algorithm accepts historical data on the resource usage by VMs running on the host and returns a set of VMs to migrate from the host.</p>
<h3 id="data-collector"><a href="#TOC"><span class="header-section-number">6.1.3</span> Data Collector</a></h3>
<p>The data collector is deployed on every compute host and is executed periodically to collect the CPU utilization data for each VM running on the host and stores the data in the local file-based data store. The data is stored as the average number of MHz consumed by a VM during the last measurement interval. The CPU usage data are stored as integers. This data format is portable: the stored values can be converted to the CPU utilization for any host or VM type, supporting heterogeneous hosts and VMs.</p>
<p>The actual data is obtained from Libvirt in the form of the CPU time consumed by a VM to date. Using the CPU time collected at the previous time frame, the CPU time for the past time interval is calculated. According to the CPU frequency of the host and the length of the time interval, the CPU time is converted into the required average MHz consumed by the VM over the last time interval. The collected data are stored both locally and submitted to the central database. The number of the latest data values stored locally and passed to the underload / overload detection and VM selection algorithms is defined using the <code>data_collector_data_length</code> option in the configuration file.</p>
<p>At the beginning of every execution, the data collector obtains the set of VMs currently running on the host using the Nova API and compares them to the VMs running on the host at the previous time step. If new VMs have been found, the data collector fetches the historical data about them from the central database and stores the data in the local file-based data store. If some VMs have been removed, the data collector removes the data about these VMs from the local data store.</p>
<h2 id="data-stores"><a href="#TOC"><span class="header-section-number">6.2</span> Data Stores</a></h2>
<p>As shown in Figure 1, the system contains two types of data stores:</p>
<ul>
<li><em>Central database</em> – a database deployed on the management host.</li>
<li><em>Local file-based data storage</em> – a data store deployed on every compute host and used for storing resource usage data to use by local managers.</li>
</ul>
<p>The details about the data stores are given in the following subsections.</p>
<h3 id="central-database"><a href="#TOC"><span class="header-section-number">6.2.1</span> Central Database</a></h3>
<p>The central database is used for storing historical data on the resource usage by VMs running on all the compute hosts. The database is populated by data collectors deployed on the compute hosts. The data are consumed by VM placement algorithms. The database contains two tables: <code>vms</code> and <code>vm_resource_usage</code>.</p>
<p>The <code>vms</code> table is used for storing the mapping between UUIDs of VMs and the internal database IDs:</p>
<pre><code>CREATE TABLE vms (
# the internal ID of a VM
id BIGINT UNSIGNED NOT NULL AUTO_INCREMENT,
# the UUID of the VM
uuid CHAR(36) NOT NULL,
PRIMARY KEY (id)
) ENGINE=MyISAM;</code></pre>
<p>The <code>vm_resource_usage</code> table is used for storing the data about the resource usage by VMs:</p>
<pre><code>CREATE TABLE vm_resource_usage (
# the ID of the record
id BIGINT UNSIGNED NOT NULL AUTO_INCREMENT,
# the id of the corresponding VM
vm_id BIGINT UNSIGNED NOT NULL,
# the time of the data collection
timestamp TIMESTAMP NOT NULL,
# the average CPU usage in MHz
cpu_mhz MEDIUMINT UNSIGNED NOT NULL,
PRIMARY KEY (id)
) ENGINE=MyISAM;</code></pre>
<h3 id="local-file-based-data-store"><a href="#TOC"><span class="header-section-number">6.2.2</span> Local File-Based Data Store</a></h3>
<p>The data collector stores the resource usage information locally in files in the <code>&lt;local_data_directory&gt;/vm</code> directory, where <code>&lt;local_data_directory&gt;</code> is defined in the configuration file using the <code>local_data_directory</code> option. The data for each VM are stored in a separate file named according to the UUID of the corresponding VM. The format of the files is a new line separated list of integers representing the average CPU consumption by the VMs in MHz during the last measurement interval.</p>
<h2 id="configuration-file"><a href="#TOC"><span class="header-section-number">6.3</span> Configuration File</a></h2>
<p>The configuration of OpenStack Neat is stored in <code>/etc/neat/neat.conf</code> in the standard INI format using the <code>#</code> character for denoting comments. The configuration includes the following options:</p>
<ul>
<li><code>sql_connection</code> – the host name and credentials for connecting to the MySQL database specified in the format supported by SQLAlchemy;</li>
<li><code>admin_tenant_name</code> – the admin tenant name for authentication with Nova using Keystone;</li>
<li><code>admin_user</code> – the admin user name for authentication with Nova using Keystone;</li>
<li><code>admin_password</code> – the admin password for authentication with Nova using Keystone;</li>
<li><code>global_manager_host</code> – the name of the host running the global manager;</li>
<li><code>global_manager_port</code> – the port of the REST web service exposed by the global manager;</li>
<li><code>local_data_directory</code> – the directory used by the data collector to store the data on the resource usage by the VMs running on the host (the default value is <code>/var/lib/neat</code>);</li>
<li><code>local_manager_interval</code> – the time interval between subsequent invocations of the local manager in seconds;</li>
<li><code>data_collector_interval</code> – the time interval between subsequent invocations of the data collector in seconds;</li>
<li><code>data_collector_data_length</code> – the number of the latest data values stored locally by the data collector and passed to the underload / overload detection and VM placement algorithms;</li>
<li><code>compute_user</code> – the user name for connecting to the compute hosts to switch them into the sleep mode;</li>
<li><code>compute_password</code> – the password of the user account used for connecting to the compute hosts to switch them into the sleep mode;</li>
<li><code>sleep_command</code> – a shell command used to switch a host into the sleep mode, the <code>compute_user</code> must have permissions to execute this command (the default value is <code>pm-suspend</code>);</li>
<li><code>algorithm_underload_detection</code> – the fully qualified name of a Python function to use as an underload detection algorithm;</li>
<li><code>algorithm_overload_detection</code> – the fully qualified name of a Python function to use as an overload detection algorithm;</li>
<li><code>algorithm_vm_selection</code> – the fully qualified name of a Python function to use as a VM selection algorithm;</li>
<li><code>algorithm_vm_placement</code> – the fully qualified name of a Python function to use as a VM placement algorithm.</li>
</ul>
<h1 id="implementation"><a href="#TOC"><span class="header-section-number">7</span> Implementation</a></h1>
<p>This section describes a plan of how the components described above are going to be implemented.</p>
<h2 id="libraries"><a href="#TOC"><span class="header-section-number">7.1</span> Libraries</a></h2>
<p>The following third party libraries are planned to be used to implement the required components:</p>
<ol style="list-style-type: decimal">
<li><a href="https://bitbucket.org/tarek/distribute">distribute</a> – a library for working with Python module distributions, released under the Python Software Foundation License.</li>
<li><a href="https://github.com/Xion/pyqcy">pyqcy</a> – a QuickCheck-like testing framework for Python, released under the FreeBSD License.</li>
<li><a href="https://github.com/gfxmonk/mocktest">mocktest</a> – a mocking library for Python, released under the LGPL License.</li>
<li><a href="https://github.com/AndreaCensi/contracts">PyContracts</a> – a Python library for Design by Contract (DbC), released under the GNU Lesser General Public License.</li>
<li><a href="http://www.sqlalchemy.org/">SQLAlchemy</a> – a Python SQL toolkit and Object Relational Mapper (used by the core OpenStack service), released under the MIT License.</li>
<li><a href="http://bottlepy.org/">Bottle</a> – a micro web-framework for Python, authentication using the same credentials used to authenticate in the Nova API, released under the MIT License.</li>
<li><a href="http://python-requests.org/">Requests</a> – a Python HTTP client library, released under the ISC License.</li>
<li><a href="https://github.com/openstack/python-novaclient">python-novaclient</a> – a Python Nova API client implementation, released under the Apache 2.0 License.</li>
<li><a href="http://sphinx.pocoo.org/">Sphinx</a> – a documentation generator for Python, released under the BSD License.</li>
</ol>
<h2 id="global-manager-1"><a href="#TOC"><span class="header-section-number">7.2</span> Global Manager</a></h2>
<p>The global manager component will provide a REST web service implemented using the Bottle framework. The authentication is going to be done using the admin credentials specified in the configuration file. Upon receiving a request from a local manager, the following steps will be performed:</p>
<ol style="list-style-type: decimal">
<li>Parse the <code>vm_uuids</code> parameter and transform it into a list of UUIDs of the VMs to migrate.</li>
<li>Call the Nova API to obtain the current placement of VMs on the hosts.</li>
<li>Call the function specified in the <code>algorithm_vm_placement</code> configuration option and pass the UUIDs of the VMs to migrate and the current VM placement as arguments.</li>
<li>Call the Nova API to migrate the VMs according to the placement determined by the <code>algorithm_vm_placement</code> algorithm.</li>
</ol>
<p>When a host needs to be switched to the sleep mode, the global manager will use the account credentials from the <code>compute_user</code> and <code>compute_password</code> configuration options to open an SSH connection with the target host and then invoke the command specified in the <code>sleep_command</code>, which defaults to <code>pm-suspend</code>.</p>
<p>When a host needs to be re-activated from the sleep mode, the global manager will leverage the Wake-on-LAN technology and send a magic packet to the target host using the <code>ether-wake</code> program and passing the corresponding MAC address as an argument. The mapping between the IP addresses of the hosts and their MAC addresses is initialized in the beginning of the global manager’s execution.</p>
<h2 id="local-manager-1"><a href="#TOC"><span class="header-section-number">7.3</span> Local Manager</a></h2>
<p>The local manager will be implemented as a Linux daemon running in the background and every <code>local_manager_interval</code> seconds checking whether some VMs should be migrated from the host. Every time interval, the local manager performs the following steps:</p>
<ol style="list-style-type: decimal">
<li>Read the data on resource usage by the VMs running on the host from the <code>&lt;local_data_directory&gt;/vm</code> directory.</li>
<li>Call the function specified in the <code>algorithm_underload_detection</code> configuration option and pass the data on the resource usage by the VMs, as well as the frequency of the CPU as arguments.</li>
<li>If the host is underloaded, send a request to the REST API of the global manager and pass a list of the UUIDs of all the VMs currently running on the host in the <code>vm_uuids</code> parameter, as well as the <code>reason</code> for migration as being 0.</li>
<li>If the host is not underloaded, call the function specified in the <code>algorithm_overload_detection</code> configuration option and pass the data on the resource usage by the VMs, as well as the frequency of the host’s CPU as arguments.</li>
<li>If the host is overloaded, call the function specified in the <code>algorithm_vm_selection</code> configuration option and pass the data on the resource usage by the VMs, as well as the frequency of the host’s CPU as arguments</li>
<li>If the host is overloaded, send a request to the REST API of the global manager and pass a list of the UUIDs of the VMs selected by the VM selection algorithm in the <code>vm_uuids</code> parameter, as well as the <code>reason</code> for migration as being 1.</li>
<li>Schedule the next execution after <code>local_manager_interval</code> seconds.</li>
</ol>
<h2 id="data-collector-1"><a href="#TOC"><span class="header-section-number">7.4</span> Data Collector</a></h2>
<p>The data collector will be implemented as a Linux daemon running in the background and collecting data on the resource usage by VMs every <code>data_collector_interval</code> seconds. When the data collection phase is invoked, the component performs the following steps:</p>
<ol style="list-style-type: decimal">
<li>Read the names of the files from the <code>&lt;local_data_directory&gt;/vm</code> directory to determine the list of VMs running on the host at the last data collection.</li>
<li>Call the Nova API to obtain the list of VMs that are currently active on the host.</li>
<li>Compare the old and new lists of VMs and determine the newly added or removed VMs.</li>
<li>Delete the files from the <code>&lt;local_data_directory&gt;/vm</code> directory corresponding to the VMs that have been removed from the host.</li>
<li>Fetch the latest <code>data_collector_data_length</code> data values from the central database for each newly added VM using the database connection information specified in the <code>sql_connection</code> option and save the data in the <code>&lt;local_data_directory&gt;/vm</code> directory.</li>
<li>Call the Libvirt API to obtain the CPU time for each VM active on the host.</li>
<li>Transform the data obtained from the Libvirt API into the average MHz according to the frequency of the host’s CPU and time interval from the previous data collection.</li>
<li>Store the converted data in the <code>&lt;local_data_directory&gt;/vm</code> directory in separate files for each VM, and submit the data to the central database.</li>
<li>Schedule the next execution after <code>data_collector_interval</code> seconds.</li>
</ol>
<h1 id="testdemo-plan"><a href="#TOC"><span class="header-section-number">8</span> Test/Demo Plan</a></h1>
<p>This need not be added or completed until the specification is nearing beta.</p>
<h1 id="unresolved-issues"><a href="#TOC"><span class="header-section-number">9</span> Unresolved issues</a></h1>
<p>This should highlight any issues that should be addressed in further specifications, and not problems with the specification itself; since any specification with problems cannot be approved.</p>
<h1 id="bof-agenda-and-discussion"><a href="#TOC"><span class="header-section-number">10</span> BoF agenda and discussion</a></h1>
<p>Use this section to take notes during the BoF; if you keep it in the approved spec, use it for summarising what was discussed and note any options that were rejected.</p>
<h1 id="references"><a href="#TOC"><span class="header-section-number">11</span> References</a></h1>
<p>[1] A. Beloglazov and R. Buyya, “Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers,” <em>Concurrency and Computation: Practice and Experience (CCPE)</em>, vol. 24, pp. 1397–1420, 2012.</p>
<p>[2] A. Beloglazov and R. Buyya, “Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers Under Quality of Service Constraints,” <em>IEEE Transactions on Parallel and Distributed Systems (TPDS)</em>, 2012 (in press, accepted on August 2, 2012).</p>
<p>[3] J. Koomey, <em>Growth in data center electricity use 2005 to 2010</em>. Oakland, CA: Analytics Press, 2011.</p>
<p>[4] Gartner Inc., <em>Gartner estimates ICT industry accounts for 2 percent of global CO2 emissions</em>. Gartner Press Release (April 2007).</p>
<p>[5] R. Nathuji and K. Schwan, “VirtualPower: Coordinated power management in virtualized enterprise systems,” <em>ACM SIGOPS Operating Systems Review</em>, vol. 41, pp. 265–278, 2007.</p>
<p>[6] A. Verma, P. Ahuja, and A. Neogi, “pMapper: Power and migration cost aware application placement in virtualized systems,” in <em>Proc. of the 9th ACM/IFIP/USENIX Intl. Conf. on Middleware</em>, 2008, pp. 243–264.</p>
<p>[7] X. Zhu, D. Young, B. J. Watson, Z. Wang, J. Rolia, S. Singhal, B. McKee, C. Hyser, and others, “1000 Islands: Integrated capacity and workload management for the next generation data center,” in <em>Proc. of the 5th Intl. Conf. on Autonomic Computing (ICAC)</em>, 2008, pp. 172–181.</p>
<p>[8] D. Gmach, J. Rolia, L. Cherkasova, G. Belrose, T. Turicchi, and A. Kemper, “An integrated approach to resource pool management: Policies, efficiency and quality metrics,” in <em>Proc. of the 38th IEEE Intl. Conf. on Dependable Systems and Networks (DSN)</em>, 2008, pp. 326–335.</p>
<p>[9] D. Gmach, J. Rolia, L. Cherkasova, and A. Kemper, “Resource pool management: Reactive versus proactive or lets be friends,” <em>Computer Networks</em>, vol. 53, pp. 2905–2922, 2009.</p>
<p>[10] VMware Inc., “VMware Distributed Power Management Concepts and Use,” <em>Information Guide</em>, 2010.</p>
<p>[11] G. Jung, M. A. Hiltunen, K. R. Joshi, R. D. Schlichting, and C. Pu, “Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures,” in <em>Proc. of the 30th Intl. Conf. on Distributed Computing Systems (ICDCS)</em>, 2010, pp. 62–73.</p>
<p>[12] W. Zheng, R. Bianchini, G. J. Janakiraman, J. R. Santos, and Y. Turner, “JustRunIt: Experiment-based management of virtualized data centers,” in <em>Proc. of the 2009 USENIX Annual Technical Conf.</em>, 2009, pp. 18–33.</p>
<p>[13] S. Kumar, V. Talwar, V. Kumar, P. Ranganathan, and K. Schwan, “vManage: Loosely coupled platform and virtualization management in data centers,” in <em>Proc. of the 6th Intl. Conf. on Autonomic Computing (ICAC)</em>, 2009, pp. 127–136.</p>
<p>[14] B. Guenter, N. Jain, and C. Williams, “Managing Cost, Performance, and Reliability Tradeoffs for Energy-Aware Server Provisioning,” in <em>Proc. of the 30st Annual IEEE Intl. Conf. on Computer Communications (INFOCOM)</em>, 2011, pp. 1332–1340.</p>
<p>[15] N. Bobroff, A. Kochut, and K. Beaty, “Dynamic placement of virtual machines for managing SLA violations,” in <em>Proc. of the 10th IFIP/IEEE Intl. Symp. on Integrated Network Management (IM)</em>, 2007, pp. 119–128.</p>
<p>[16] A. Beloglazov, R. Buyya, Y. C. Lee, and A. Zomaya, “A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems,” <em>Advances in Computers, M. Zelkowitz (ed.)</em>, vol. 82, pp. 47–111, 2011.</p>
<p>[17] A. Beloglazov, S. F. Piraghaj, M. Alrokayan, and R. Buyya, “Deploying OpenStack on CentOS Using the KVM Hypervisor and GlusterFS Distributed File System,” <em>Technical Report CLOUDS-TR-2012-3, Cloud Computing and Distributed Systems Laboratory, The University of Melbourne</em>, Aug. 2012.</p>
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