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    • 3. 发明公开
    • LOAD BALANCING SCALABLE STORAGE UTILIZING OPTIMIZATION MODULES
    • SKALIERBARER LASTAUSGLEICHSPEICHER MIT VERWENDUNG VON OPTIMIERUNGSMODULEN
    • EP3138005A1
    • 2017-03-08
    • EP15724827.9
    • 2015-04-29
    • Microsoft Technology Licensing, LLC
    • WANG, JuSKJOLSVOLD, Arild E.CALDER, Bradley GeneSONG, HosungJI, XinhuaHARRIS, Ralph Burton, III
    • G06F9/50G06F3/06
    • H04L67/1025G06F3/0683G06F9/5077G06F9/5083H04L47/783H04L67/1097
    • A method includes determining that a trigger condition of a triggered optimization module of a plurality of optimization modules is met and optimizing scalable storage based on an optimization routine. The optimization routine includes providing a plurality of candidate operations and for a selected optimization module of the plurality of optimization modules that has a higher priority than the triggered optimization module, removing a candidate operation from the plurality of candidate operations that would diminish a modeled state of the scalable storage for the selected optimization module. The optimization routine also includes determining at least one operation of the plurality of candidate operations that would improve the modeled state of the scalable storage for the triggered optimization module and updating the modeled state of the scalable storage to model executing the at least one operation. The method further includes executing the at least one operation.
    • 一种方法包括确定满足多个优化模块的触发优化模块的触发条件,并且基于优化程序来优化可扩展存储。 所述优化程序包括提供多个候选操作以及对于具有比所触发的优化模块更高优先级的多个优化模块的选定优化模块,从多个候选操作中移除将会减少模拟状态的模拟状态的候选操作 所选优化模块的可扩展存储。 所述优化例程还包括确定所述多个候选操作中的至少一个操作,所述操作将改善所述触发的优化模块的所述可伸缩存储器的建模状态,并且将所述可伸缩存储器的建模状态更新为执行所述至少一个操作的模型。 该方法还包括执行该至少一个操作。
    • 6. 发明公开
    • EFFECTIVE RANGE PARTITION SPLITTING IN SCALABLE STORAGE
    • 可扩展存储中的有效范围分区分割
    • EP3161608A1
    • 2017-05-03
    • EP15739115.2
    • 2015-06-29
    • Microsoft Technology Licensing, LLC
    • SKJOLSVOLD, ArildWANG, JuCALDER, Bradley Gene
    • G06F3/06G06F9/50
    • G06F5/065G06F3/061G06F3/0635G06F3/067G06F9/5061G06F9/5077G06F9/5083G06F2206/1012
    • A method for load balancing includes determining a reference key within a partition key range of a partition of scalable storage, the partition key range being divided into buckets that have boundaries defining sub ranges of the partition key range. The reference key is determined based on traffic values that correspond to tracked traffic within the buckets. The traffic values are updated based on additional traffic within the buckets and the boundaries are adjusted based on the updated traffic values. A reference key speed is determined that corresponds to a rate of change of a distribution of the tracked traffic with respect to the reference key. Reference key drop-off time may be determined for reference keys. Reference keys can be utilized to determine where to split the partition and reference key speed and reference key drop-off time can be utilized to determine whether or not to split the partition.
    • 一种用于负载平衡的方法包括确定可伸缩存储器的分区的分区键范围内的参考键,所述分区键范围被划分为具有界定分区键范围的子范围的边界的桶。 参考密钥基于对应于桶内的跟踪业务量的流量值来确定。 流量值基于桶内的附加流量而更新,并且边界根据更新的流量值进行调整。 确定参考关键速度,该参考关键速度对应于跟踪的业务相对于参考关键的分布的改变速率。 可以为参考键确定参考关键点落下时间。 可以利用参考关键字来确定在哪里分割分区,并且可以利用参考关键词速度和参考关键词落选时间来确定是否分割分区。
    • 8. 发明公开
    • INTEGRATED GLOBAL RESOURCE ALLOCATION AND LOAD BALANCING
    • 集成的全球资源分配和负载平衡
    • EP3161632A1
    • 2017-05-03
    • EP15734042.3
    • 2015-06-29
    • Microsoft Technology Licensing, LLC
    • SKJOLSVOLD, ArildCALDER, Bradley GeneWANG, Ju
    • G06F9/50
    • H04L43/0876G06F9/505H04L47/828
    • In various embodiments, methods and systems for integrated resource allocation and loading balancing are provided. A global resource allocator receives usage information of resources in a cloud computing system. The usage information is associated with a plurality of accounts and consumer operations pairs on servers of the cloud computing system. For selected account and consumer operation pairs associated with a particular resource, allocation targets are determined and communicated to the corresponding server of the selected account and consumer operation pairs. The servers use the resource based on the allocation targets. A load balancer receives the usage information the resource and the allocation targets. The allocation targets indicate a load by the selected account and consumer operation pairs on their corresponding servers. The load balancer performs a load balancing operation to locate a server with a capacity to process the allocated target of the selected account and consumer operation pairs.
    • 在各种实施例中,提供了用于集成资源分配和负载平衡的方法和系统。 全球资源分配器接收云计算系统中资源的使用信息。 使用信息与云计算系统的服务器上的多个账户和消费者操作对相关联。 对于与特定资源相关联的选定帐户和消费者操作对,确定分配目标并将其传送到所选帐户和消费者操作对的相应服务器。 服务器使用基于分配目标的资源。 负载均衡器接收资源和分配目标的使用信息。 分配目标指示所选帐户和消费者操作对在其相应服务器上的负载。 负载均衡器执行负载平衡操作以找到具有处理所选帐户和消费者操作对的分配目标的容量的服务器。