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    • 2. 发明申请
    • LOAD BALANCING SCALABLE STORAGE UTILIZING OPTIMIZATION MODULES
    • 使用优化模块的负载平衡存储
    • US20150319234A1
    • 2015-11-05
    • US14267659
    • 2014-05-01
    • MICROSOFT CORPORATION
    • JU WANGARILD E. SKJOLSVOLDBRADLEY GENE CALDERHOSUNG SONGXINHUA JIRALPH BURTON HARRIS, III
    • H04L29/08H04L12/911
    • 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优化可扩展存储。 所述优化程序包括提供多个候选操作,并且对于具有比触发的优化模块更高的优先级的多个优化模块中的选定的优化模块,从多个候选操作中移除将会削弱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,以及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。 所述方法还包括执行所述至少一个操作。
    • 3. 发明申请
    • DIMENSION BASED LOAD BALANCING
    • 基于尺寸的负载平衡
    • US20150319230A1
    • 2015-11-05
    • US14305987
    • 2014-06-16
    • MICROSOFT CORPORATION
    • ARILD SKJOLSVOLDXINHUA JIJU WANGBRADLEY GENE CALDERRALPH BURTON HARRIS, IIIHOSUNG SONG
    • H04L29/08H04L12/26
    • G06F3/0604G06F3/0611G06F3/0614G06F9/5077G06F9/5083G06F17/30929H04L43/04H04L67/101H04L67/1097
    • One method includes receiving partitions, generating assignment plans for assignment of the partitions to servers based on dimensional values of dimensions as determined by different assignment heuristics, selecting one of the assignment plans for execution based on analyzing the dimensional values in accordance with the assignment plans, and executing the selected assignment plan on scalable storage. Another method includes determining, for a triggered optimization module that a server is over utilized on a dimension, selecting candidate operations for partitions assigned to the server, for a higher priority optimization module than the triggered optimization module, removing a candidate operation from the candidate operations that would diminish a modeled state of scalable storage, determining an operation of the candidate operations that would improve the modeled state of the scalable storage with respect to a metric of the dimension on the server, and executing the operation on the scalable storage.
    • 一种方法包括接收分区,根据由不同的分配启发式确定的尺寸的维度值,生成用于将分区分配给服务器的分配计划,基于分配计划分析尺寸值来选择执行分配计划之一, 以及在可扩展存储器上执行所选择的分配计划。 另一种方法包括针对触发的优化模块确定服务器在维度上被过度使用的选择,为分配给服务器的分区选择候选操作,对于比所触发的优化模块更高优先级的优化模块,从候选操作中移除候选操作 这将减少可扩展存储器的建模状态,确定候选操作的操作,其将相对于服务器上的维度的度量改善可伸缩存储器的建模状态,以及对可伸缩存储器执行操作。
    • 6. 发明申请
    • BLOB MANIPULATION IN AN INTEGRATED STRUCTURED STORAGE SYSTEM
    • 一体化结构化存储系统中的BLOB操作
    • US20130311521A1
    • 2013-11-21
    • US13947794
    • 2013-07-22
    • MICROSOFT CORPORATION
    • BRADLEY GENE CALDERJU WANGXINRAN WUNIRANJAN NILAKANTANDEEPALI BHARDWAJSHASHWAT SRIVASTAVALEXANDER FELSOBUKI NAGY
    • G06F17/30
    • G06F17/30303G06F17/30011G06F17/30017
    • Embodiments of the present invention relate to systems, methods and computer storage media for facilitating the structured storage of binary large objects (Blobs) to be accessed by an application program being executed by a computing device. Generally, the manipulation of Blobs in a structured storage system includes receiving a request for a Blob, which may be located by way of a Blob pointer. The Blob pointer allows for the data, such as properties, of the Blob to be identified and located. Expired properties are garbage collected as a manipulation of the Blob data within a structured storage system. In an embodiment, the Blob is identified by a key that is utilized within a primary structured index to located the requested Blob. In another embodiment, the requested Blob is located utilizing a secondary hash index. In an additional embodiment, the Blob is locate utilizing a file table.
    • 本发明的实施例涉及用于促进由计算设备执行的应用程序访问的二进制大对象(Blob)的结构化存储的系统,方法和计算机存储介质。 通常,结构化存储系统中Blob的操作包括接收对可以通过Blob指针定位的Blob的请求。 Blob指针允许识别和定位Blob的数据,例如属性。 过期属性作为在结构化存储系统中操纵Blob数据而被垃圾回收。 在一个实施例中,Blob由在主要结构化索引中使用的密钥来标识以定位所请求的Blob。 在另一个实施例中,使用辅助散列索引定位所请求的Blob。 在另外的实施例中,使用文件表定位Blob。
    • 8. 发明申请
    • EFFECTIVE RANGE PARTITION SPLITTING IN SCALABLE STORAGE
    • 有效的范围划分在可扩展存储中
    • US20150378635A1
    • 2015-12-31
    • US14319758
    • 2014-06-30
    • MICROSOFT CORPORATION
    • ARILD SKJOLSVOLDJU WANGBRADLEY GENE CALDER
    • 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关键字范围内的参考密钥,所述分区密钥范围被划分为具有限定分区密钥范围的子范围的边界的桶。 基于对应于桶内的跟踪流量的流量值确定参考密钥。 基于桶内的附加流量来更新流量值,并且基于更新的流量值来调整边界。 确定对应于跟踪的业务相对于参考密钥的分布的变化率的参考密钥速度。 可以为参考键确定参考键下降时间。 参考键可用于确定分割分区的位置和参考键速度,并且可以利用参考键下降时间来确定是否分割分区。
    • 9. 发明申请
    • INTEGRATED GLOBAL RESOURCE ALLOCATION AND LOAD BALANCING
    • 综合全球资源分配和负荷平衡
    • US20150381453A1
    • 2015-12-31
    • US14319553
    • 2014-06-30
    • MICROSOFT CORPORATION
    • ARILD SKJOLSVOLDBRADLEY GENE CALDERJU WANG
    • H04L12/26H04L12/911
    • 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。 全局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帐户和消费者操作对相关联。 对于与特定资源相关联的所选择的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。 服务器根据分配目标使用资源。 负载平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其相应服务器上的消费者操作对的负载。 负载平衡器执行负载平衡操作,以定位具有处理所选帐户和消费者操作对的分配目标的能力的服务器。