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    • 44. 发明授权
    • Resource adaptive spectrum estimation of streaming data
    • 流数据资源自适应频谱估计
    • US08494036B2
    • 2013-07-23
    • US12177300
    • 2008-07-22
    • Deepak Srinivac TuragaMichail VlachosPhilip S. Yu
    • Deepak Srinivac TuragaMichail VlachosPhilip S. Yu
    • H04B3/46
    • G06F17/141
    • Streaming environments typically dictate incomplete or approximate algorithm execution, in order to cope with sudden surges in the data rate. Such limitations are even more accentuated in mobile environments (such as sensor networks) where computational and memory resources are typically limited. Introduced herein is a novel “resource adaptive” algorithm for spectrum and periodicity estimation on a continuous stream of data. The formulation is based on the derivation of a closed-form incremental computation of the spectrum, augmented by an intelligent load-shedding scheme that can adapt to available CPU resources. Experimentation indicates that the proposed technique can be a viable and resource efficient solution for real-time spectrum estimation.
    • 流环境通常会指示不完整或近似算法执行,以应对数据速率的突然增加。 在计算和存储资源通常受限制的移动环境(如传感器网络)中,这种限制更加突出。 这里介绍的是一种用于连续数据流的频谱和周期估计的新型“资源自适应”算法。 该公式基于频谱的闭合增量计算的推导,通过可以适应可用CPU资源的智能加载开放方案来增强。 实验表明,提出的技术可以成为实时频谱估计的可行且资源有效的解决方案。
    • 46. 发明授权
    • Systems and methods for optimal component composition in a stream processing system
    • 流处理系统中最佳组件组成的系统和方法
    • US08286153B2
    • 2012-10-09
    • US12061284
    • 2008-04-02
    • Xiaohui GuPhilip S. Yu
    • Xiaohui GuPhilip S. Yu
    • G06F9/45
    • H04L12/4641
    • A system and method are provided for optimizing component composition in a distributed stream-processing environment having a plurality of nodes capable of being associated with one or more of a plurality of stream processing components. The system includes an adaptive composition probing (ACP) module and a hierarchical state manager. The ACP module probes a subset of the plurality of stream processing components to determine the optimal component composition in response to a stream processing request. The hierarchical state manager manages local and global information for use by said ACP module in determining the optimal component composition.
    • 提供了一种用于在分布式流处理环境中优化组件组成的系统和方法,其具有能够与多个流处理组件中的一个或多个相关联的多个节点。 该系统包括自适应组合探测(ACP)模块和分级状态管理器。 ACP模块探测多个流处理组件的子集,以响应于流处理请求来确定最佳组件组成。 层级状态管理器管理本地和全局信息,供所述ACP模块在确定最佳组件组成时使用。
    • 47. 发明授权
    • Identifying optimal multi-scale patterns in time-series streams
    • 确定时间序列流中的最优多尺度模式
    • US07945570B2
    • 2011-05-17
    • US12551033
    • 2009-08-31
    • Spyridon PapadimitriouPhilip S. Yu
    • Spyridon PapadimitriouPhilip S. Yu
    • G06F17/30
    • G06K9/00496
    • A computer-implemented method, system, and a computer readable article of manufacture identify local patterns in at least one time series data stream. A data stream is received that comprises at least one set of time series data. The at least one set of time series data is formed into a set of multiple ordered levels of time series data. Multiple ordered levels of hierarchical approximation functions are generated directly from the multiple ordered levels of time series data. A set of approximating functions are created for each level. A current window with a current window length is selected from a set of varying window lengths. The set of approximating functions created at one level in the multiple ordered levels is passed to a subsequent level as a set of time series data. The multiple ordered levels of hierarchical approximation functions are stored into memory after being generated.
    • 计算机实现的方法,系统和计算机可读制造商标识至少一个时间序列数据流中的局部模式。 接收包括至少一组时间序列数据的数据流。 至少一组时间序列数据被形成为一组时间序列数据的多个有序级别。 分层近似函数的多个有序级别直接从多个有序级别的时间序列数据生成。 为每个级别创建一组近似函数。 从一组变化的窗口长度中选择具有当前窗口长度的当前窗口。 在多个有序等级中在一个级别创建的一组近似函数作为一组时间序列数据传递到后续级别。 分层近似函数的多个有序等级在生成后被存储到存储器中。
    • 48. 发明申请
    • IDENTIFYING OPTIMAL MULTI-SCALE PATTERNS IN TIME-SERIES STREAMS
    • 识别时间序列中的最佳多尺度模式
    • US20100063974A1
    • 2010-03-11
    • US12551033
    • 2009-08-31
    • SPYRIDON PAPADIMITRIOUPhilip S. Yu
    • SPYRIDON PAPADIMITRIOUPhilip S. Yu
    • G06F17/30
    • G06K9/00496
    • A computer-implemented method, system, and a computer readable article of manufacture identify local patterns in at least one time series data stream. A data stream is received that comprises at least one set of time series data. The at least one set of time series data is formed into a set of multiple ordered levels of time series data. Multiple ordered levels of hierarchical approximation functions are generated directly from the multiple ordered levels of time series data. A set of approximating functions are created for each level. A current window with a current window length is selected from a set of varying window lengths. The set of approximating functions created at one level in the multiple ordered levels is passed to a subsequent level as a set of time series data. The multiple ordered levels of hierarchical approximation functions are stored into memory after being generated.
    • 计算机实现的方法,系统和计算机可读制造商标识至少一个时间序列数据流中的局部模式。 接收包括至少一组时间序列数据的数据流。 至少一组时间序列数据被形成为一组时间序列数据的多个有序级别。 分层近似函数的多个有序级别直接从多个有序级别的时间序列数据生成。 为每个级别创建一组近似函数。 从一组变化的窗口长度中选择具有当前窗口长度的当前窗口。 在多个有序等级中在一个级别创建的一组近似函数作为一组时间序列数据传递到后续级别。 分层近似函数的多个有序等级在生成后被存储到存储器中。
    • 49. 发明授权
    • System and method for historical diagnosis of sensor networks
    • 传感器网络历史诊断系统及方法
    • US07676458B2
    • 2010-03-09
    • US11846397
    • 2007-08-28
    • Charu Chandra AggarwalPhilip S. Yu
    • Charu Chandra AggarwalPhilip S. Yu
    • G06F7/00G06F17/30G06F15/173G06F15/177
    • G06K9/00979
    • A method of querying a hierarchically organized sensor network, said network being sensor network with a global coordinator node at a top level which receives data from lower level intermediate nodes which are either leader nodes for lower level nodes or sensor nodes, wherein a sensor node i at a lowest level receives a signal Y(i,t) at time t, said method including constructing a sketch Swkt=(Swkt1, . . . , Swktn) for an internal node k from S wkt j = ∑ i ∈ LeafDescendents ⁡ ( k ) ⁢ ∑ q = 1 i ⁢ b wiq · r iq j , wherein component Swktj is a sketch of a descendent of node k, ritj is a random variable associated with each sensor node i and time instant t wherein index j refers to independently drawn instantiations of the random variable, bit bwit represents a state of sensor node i for signal value w=Y(i,t) at time t, and LeafDescendents(k) are the lowest level sensor nodes under node k, wherein said sketch is adapted for responding to queries regarding a state of said network.
    • 一种查询分级组织的传感器网络的方法,所述网络是具有在顶层的全局协调器节点的传感器网络,其从作为下级节点或传感器节点的前导节点的较低级中间节点接收数据,其中传感器节点i 在最低级别,在时间t接收信号Y(i,t),所述方法包括从S wkt j =Σi∈LeafDescendents including(...)构建内部节点k的草图Swkt =(Swkt1,...,Swktn) k)Σq = 1 i b wiq·r iq j,其中分量Swktj是节点k的后代的草图,ritj是与每个传感器节点i和时刻t相关联的随机变量,其中索引j独立地指 随机变量的抽取实例,位bwit表示在时间t处信号值w = Y(i,t)的传感器节点i的状态,LeafDescendents(k)是节点k处的最低级传感器节点,其中所述草图是 适于响应关于所述网络的状态的查询 k。
    • 50. 发明授权
    • Systems and methods for optimal component composition in a stream processing system
    • 流处理系统中最佳组件组成的系统和方法
    • US07562355B2
    • 2009-07-14
    • US11068785
    • 2005-03-01
    • Xiaohui GuPhilip S. Yu
    • Xiaohui GuPhilip S. Yu
    • G06F9/45
    • H04L12/4641
    • A system and method are provided for optimizing component composition in a distributed stream-processing environment having a plurality of nodes capable of being associated with one or more of a plurality of stream processing components. The system includes an adaptive composition probing (ACP) module and a hierarchical state manager. The ACP module probes a subset of the plurality of stream processing components to determine the optimal component composition in response to a stream processing request. The hierarchical state manager manages local and global information for use by said ACP module in determining the optimal component composition.
    • 提供了一种用于在分布式流处理环境中优化组件组成的系统和方法,其具有能够与多个流处理组件中的一个或多个相关联的多个节点。 该系统包括自适应组合探测(ACP)模块和分级状态管理器。 ACP模块探测多个流处理组件的子集,以响应于流处理请求来确定最佳组件组成。 层级状态管理器管理本地和全局信息,供所述ACP模块在确定最佳组件组成时使用。