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    • 53. 发明授权
    • Dynamically expanding computing resources in a networked computing environment
    • 在网络计算环境中动态扩展计算资源
    • US08898291B2
    • 2014-11-25
    • US13204905
    • 2011-08-08
    • Gregory J. BossChristopher J. DawsonRick A. Hamilton, IIBrian M. O'Connell
    • Gregory J. BossChristopher J. DawsonRick A. Hamilton, IIBrian M. O'Connell
    • G06F15/173G06F9/50
    • H04L47/823G06F9/5011H04L43/0876
    • Embodiments of the present invention provide an approach for dynamically expanding cloud capacity (e.g., computing resources), based on infrastructure needs. In a typical embodiment, an available capacity of a set (e.g., at least one) of computing resources in the networked computing environment will be determined. Then, a future capacity needed for processing a set of workloads in the networked computing environment will be forecasted. Such a forecast can be made based on multiple factors/approaches. For example, the forecast can be made based upon at least one of the following: an average consumption of the set of computing resources over a predetermined period of time, a periodic estimation of consumption of the set of computing resources, a scheduled consumption of the set of computing resources, and/or a potential capacity of the set of computing resources. In general, the scheduled consumption can be determined based on at least one resource consumption schedule stored in a computer data structure, while the potential capacity can be determined based upon a set of application events associated with the set of workloads. Regardless of the approach utilized, once the future capacity has been forecasted, it will be determined whether the future capacity exceeds the available capacity. If so, the available capacity of the set of computing resources will be expanded (e.g., hardware and/or software elements will be added to the networked computing infrastructure and/or made available) until the available capacity at least meets the future capacity.
    • 本发明的实施例提供了一种基于基础设施需求动态扩展云容量(例如,计算资源)的方法。 在典型的实施例中,将确定网络计算环境中的一组(例如,至少一个)计算资源的可用容量。 然后,将预测在网络化计算环境中处理一组工作负载所需的未来容量。 这样的预测可以基于多种因素/方法。 例如,可以基于以下中的至少一个进行预测:在预定时间段内该组计算资源的平均消耗,该组计算资源的消耗的周期性估计, 一组计算资源,和/或一组计算资源的潜在容量。 通常,可以基于存储在计算机数据结构中的至少一个资源消耗调度来确定调度消耗,同时可以基于与该组工作负载相关联的一组应用事件来确定潜在容量。 无论采用何种方法,一旦预测未来能力,将确定未来能力是否超过可用容量。 如果是这样,则将扩展该组计算资源的可用容量(例如,硬件和/或软件元素将被添加到联网计算基础设施和/或可用),直到可用容量至少满足将来容量。
    • 56. 发明授权
    • Emergency routing within a controllable transit system
    • 可控转接系统内的紧急路由
    • US08406986B2
    • 2013-03-26
    • US12767869
    • 2010-04-27
    • Gregory J. BossChristopher J. DawsonRick A. Hamilton, IIBenjamin G. Morris
    • Gregory J. BossChristopher J. DawsonRick A. Hamilton, IIBenjamin G. Morris
    • G06F19/00
    • B61L27/00B61L27/04G01C21/3415G06Q50/26G06Q50/30G08G1/127G08G1/207G08G5/065
    • Embodiments of the present invention provide a solution for an orderly and well-considered evacuation of a Personal Rapid Transit (PRT) system in the event of declared emergency. It describes the mapping of evacuation points and subsequent routing of PRT vehicles according to both the nature/location of the emergency and outflow capacity at each evacuation point. A PRT is defined as an automatic method by which personal transport vehicles (a/k/a “pods”) can be used to efficiently and rapidly move people between various points within a closed area (for example, a city center). In an ideal world, these pods can be thought of as intelligent automated vehicles (similar to driverless taxis) that can adapt to changing demand to optimize the movement of people. For example, an emergency may be declared within a PRT system which does not cause widespread power loss, but which does require an orderly evacuation (e.g., smoke or flooding). In such events, PRT vehicles will be routed through the means described here to an evacuation point capable of handling such outflow in an orderly manner.
    • 本发明的实施例提供了一种解决方案,用于在宣布紧急情况下,有秩序地,仔细考虑撤离个人快速公交(PRT)系统。 它描述了撤离点的映射和随后的PRT车辆的路由,根据每个撤离点的紧急和流出能力的性质/位置。 PRT被定义为可以使用个人运输车辆(a / k / a pod)来在封闭区域(例如,市中心)内的各个点之间有效地和快速地移动人的自动方法。 在理想的世界中,这些荚可以被认为是智能自动化车辆(类似于无人驾驶的出租车),可适应不断变化的需求,以优化人员的行动。 例如,紧急情况可以在PRT系统内宣布,不会导致广泛的功率损耗,但是需要有序撤离(例如,烟雾或淹水)。 在这种情况下,PRT车辆将通过这里描述的手段被路由到能够有秩序地处理这种流出的撤离点。