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公开(公告)号：US08510745B2
公开(公告)日：2013-08-13
申请号：US13415034
申请日：2012-03-08
IPC分类号： G06F9/46 , G06F15/173
CPC分类号： G06F9/5066 , G06F9/5083
摘要： An optimization problem models the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.
摘要翻译： 优化问题模拟服务器上应用程序在两种类型的同时资源需求下的动态放置，即依赖于应用程序上的负载和独立的负载。 应用程序的需求（负载）随时间而变化，目标是尽可能少地改变解决方案（将应用程序分配给服务器）来满足所有需求。
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公开(公告)号：US08230438B2
公开(公告)日：2012-07-24
申请号：US12062569
申请日：2008-04-04
IPC分类号： G06F9/46 , G06F15/173
CPC分类号： G06F9/5066 , G06F9/5083
摘要： An optimization problem models the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.
摘要翻译： 优化问题模拟服务器上应用程序在两种类型的同时资源需求下的动态放置，即依赖于应用程序上的负载和独立的负载。 应用程序的需求（负载）随时间而变化，目标是尽可能少地改变解决方案（将应用程序分配给服务器）来满足所有需求。
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公开(公告)号：US20080189418A1
公开(公告)日：2008-08-07
申请号：US12062569
申请日：2008-04-04
IPC分类号： G06F15/173
CPC分类号： G06F9/5066 , G06F9/5083
摘要： An optimization problem models the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.
摘要翻译： 优化问题模拟服务器上应用程序在两种类型的同时资源需求下的动态放置，即依赖于应用程序上的负载和独立的负载。 应用程序的需求（负载）随时间而变化，目标是尽可能少地改变解决方案（将应用程序分配给服务器）来满足所有需求。
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公开(公告)号：US20060242647A1
公开(公告)日：2006-10-26
申请号：US11110766
申请日：2005-04-21
IPC分类号： G06F9/46
CPC分类号： G06F9/5066 , G06F9/5083
摘要： An optimization problem models the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.
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公开(公告)号：US20110246994A1
公开(公告)日：2011-10-06
申请号：US12755089
申请日：2010-04-06
申请人： Tracy J. Kimbrel , Tarun Kumar , Kevin D. McKenzie , Richard D. Prewitt, JR. , Maxim Sviridenko , Debra Tomkowid
发明人： Tracy J. Kimbrel , Tarun Kumar , Kevin D. McKenzie , Richard D. Prewitt, JR. , Maxim Sviridenko , Debra Tomkowid
IPC分类号： G06F9/46
CPC分类号： G06Q10/06 , G06F9/5027 , G06F9/5077 , G06F2209/5021 , G06F2209/506 , G06Q10/10
摘要： A system and method that provides an automated solution to obtaining quality scheduling for users of computing resources. The system, implemented in an enterprise software test center, collects information from test-shop personnel about test machine features and availability, test jobs, and tester preferences and constraints. The system reformulates this testing information as a system of constraints. An optimizing scheduling engine computes efficient schedules whereby all the jobs are feasibly scheduled while satisfying the users' time preferences to the greatest extent possible. The method and system achieves fairness: if all preferences can not be meet, it is attempted to evenly distribute violations of preferences across the users. The test scheduling is generated according to a first application of a greedy algorithm that finds an initial feasible assignment of jobs. The second is a local search algorithm that improves the initial greedy solution.
摘要翻译： 提供自动解决方案以获得计算资源用户的质量调度的系统和方法。 在企业软件测试中心实施的系统从测试人员收集关于测试机特性和可用性，测试作业以及测试者偏好和限制的信息。 该系统将这个测试信息重新定义为一个约束系统。 优化调度引擎计算有效的时间表，其中所有作业都被可行地调度，同时最大限度地满足用户的时间偏好。 该方法和系统实现公平性：如果所有偏好都不能满足，则尝试在用户之间均匀分布违反偏好的行为。 测试调度是根据找到作业的初始可行分配的贪心算法的第一应用产生的。 第二个是本地搜索算法，改进了初始的贪心解决方案。
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公开(公告)号：US20080033774A1
公开(公告)日：2008-02-07
申请号：US11861663
申请日：2007-09-26
IPC分类号： G06Q10/00
CPC分类号： G06F9/50 , G06Q10/0631 , G06Q10/06312 , G06Q10/06315 , H04L67/1002 , H04L67/1008 , H04L67/1023
摘要： A method for server allocation in a Web server “farm” is based on limited information regarding future loads to achieve close to the greatest possible revenue based on the assumption that revenue is proportional to the utilization of servers and differentiated by customer class. The method of server allocation uses an approach of “discounting the future”. Specifically, when the policy faces the choice between a guaranteed benefit immediately and a potential benefit in the future, the decision is made by comparing the guaranteed benefit value with a discounted value of the potential future benefit. This discount factor is exponential in the number of time units that it would take a potential benefit to be materialized. The future benefits are discounted because by the time a benefit will be materialized, things might change and the algorithm might decide to make another choice for a potential (even greater) benefit.
摘要翻译： Web服务器“farm”中的服务器分配方法基于有限的关于未来负载的信息，以实现接近最大可能收入的假设，即假设收入与服务器的利用率成正比，并根据客户类别区分。 服务器分配的方法采用“贴现未来”的方法。 具体来说，当政策面临保证收益立即与潜在利益之间的选择时，通过将担保收益值与潜在未来收益的折扣价值进行比较来做出决策。 这个折扣因子是要实现潜在收益的时间单位数量的指数。 未来的利益是折扣的，因为在实现利益的时候，事情可能会改变，算法可能决定为潜力（甚至更大）的利益作出另一个选择。
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公开(公告)号：US08392926B2
公开(公告)日：2013-03-05
申请号：US12755089
申请日：2010-04-06
申请人： Tracy J. Kimbrel , Tarun Kumar , Kevin D. McKenzie , Richard D. Prewitt, Jr. , Maxim Sviridenko , Debra Tomkowid
发明人： Tracy J. Kimbrel , Tarun Kumar , Kevin D. McKenzie , Richard D. Prewitt, Jr. , Maxim Sviridenko , Debra Tomkowid
IPC分类号： G06F9/46
CPC分类号： G06Q10/06 , G06F9/5027 , G06F9/5077 , G06F2209/5021 , G06F2209/506 , G06Q10/10
摘要： A system and method that provides an automated solution to obtaining quality scheduling for users of computing resources. The system, implemented in an enterprise software test center, collects information from test-shop personnel about test machine features and availability, test jobs, and tester preferences and constraints. The system reformulates this testing information as a system of constraints. An optimizing scheduling engine computes efficient schedules whereby all the jobs are feasibly scheduled while satisfying the users' time preferences to the greatest extent possible. The method and system achieves fairness: if all preferences can not be meet, it is attempted to evenly distribute violations of preferences across the users. The test scheduling is generated according to a first application of a greedy algorithm that finds an initial feasible assignment of jobs. The second is a local search algorithm that improves the initial greedy solution.
摘要翻译： 提供自动解决方案以获得计算资源用户的质量调度的系统和方法。 在企业软件测试中心实施的系统从测试人员收集关于测试机特性和可用性，测试作业以及测试者偏好和限制的信息。 该系统将这个测试信息重新定义为一个约束系统。 优化调度引擎计算有效的时间表，其中所有作业都被可行地调度，同时最大限度地满足用户的时间偏好。 该方法和系统实现公平性：如果所有偏好都不能满足，则尝试在用户之间均匀分布违反偏好的行为。 测试调度是根据找到作业的初始可行分配的贪心算法的第一应用产生的。 第二个是本地搜索算法，改进了初始的贪心解决方案。
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