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    Determining event causality including employment of causal chains
    2.
    发明申请
    Determining event causality including employment of causal chains 审中-公开
    确定事件因果关系，包括因果链的使用

    公开(公告)号：US20050288915A1

    公开(公告)日：2005-12-29

    申请号：US11168202

    申请日：2005-06-27

    申请人： Ken Hines

    发明人： Ken Hines

    IPC分类号： G06F17/50 ,  H04L12/24

    CPC分类号： H04L41/0631

    摘要： A causal relationship between two events occurs when a first event meaningfully precedes a second event and is identified by a causality module. The causality module analyzes multiple network events to determine through an evaluation of available network traffic and predecessor events whether the events are causally related. Reductions in both required storage space and search operations are obtained by tracing interrelated causal chains of network events.

    摘要翻译： 当第一个事件有意义地在第二个事件之前并且由因果模块识别时，发生两个事件之间的因果关系。 因果模块通过评估可用的网络流量和前导事件来分析多个网络事件，以确定事件是否与因果关联。 通过跟踪网络事件的相关因果链，可以减少所需的存储空间和搜索操作。

    Determining event causality including employment of partitioned event space
    3.
    发明授权
    Determining event causality including employment of partitioned event space 失效
    确定事件因果关系，包括使用分区事件空间

    公开(公告)号：US07363203B2

    公开(公告)日：2008-04-22

    申请号：US11168258

    申请日：2005-06-27

    申请人： Ken Hines

    发明人： Ken Hines

    IPC分类号： G06F17/50 ,  H04L29/00 ,  G06F11/30

    CPC分类号： H04L41/0631

    摘要： Causal relationships between events in a plurality of interrelated causal chains are maintained in a network event space through the partitioning of the event space into event subspaces. In this manner, events sharing the same event subspace stay constant so long as the partitioned subspace is substantially causally consistent. The causality of events from different neighboring subspaces may be determined through the individual subspace determination on each query event until a joining of shared boundary events is possible.

    摘要翻译： 通过将事件空间划分为事件子空间，在网络事件空间中维护多个相互关联的因果链中的事件之间的因果关系。 以这种方式，共享相同事件子空间的事件保持恒定，只要分割的子空间基本上是因果一致的。 来自不同相邻子空间的事件的因果关系可以通过每个查询事件的单个子空间确定来确定，直到共享边界事件的加入成为可能。

    Performing efficient insertions in wavefront table based causal graphs
    4.
    发明申请
    Performing efficient insertions in wavefront table based causal graphs 失效
    在基于波阵面的因果图中执行高效插入

    公开(公告)号：US20070032987A1

    公开(公告)日：2007-02-08

    申请号：US11499619

    申请日：2006-08-03

    申请人： Ken Hines

    发明人： Ken Hines

    IPC分类号： G06F11/30

    CPC分类号： H04L41/0631

    摘要： A causal relationship between two events occurs when a first event meaningfully precedes a second event and is identified by a causality module. The causality module analyzes multiple events to determine whether the events are causally related. Reductions in both required storage space and search operations are obtained by tracing interrelated causal chains of events. Further improvement is achieved by reducing re-computation of wavefront tables through annotating causality chain with information that facilitates determination of validity of a wavefront table.

    摘要翻译： 当第一个事件有意义地在第二个事件之前并且由因果模块识别时，发生两个事件之间的因果关系。 因果模块分析多个事件以确定事件是否与因果关联。 通过追踪事件的相关因果链，可以减少所需的存储空间和搜索操作。 通过利用有助于确定波前表的有效性的信息来注释因果链，减少波前表的重新计算，从而实现进一步的改进。

    Performing efficient insertions in wavefront table based causal graphs
    5.
    发明授权
    Performing efficient insertions in wavefront table based causal graphs 失效
    在基于波阵面的因果图中执行高效插入

    公开(公告)号：US07487241B2

    公开(公告)日：2009-02-03

    申请号：US11499619

    申请日：2006-08-03

    申请人： Ken Hines

    发明人： Ken Hines

    IPC分类号： G06F15/173

    CPC分类号： H04L41/0631

    摘要： A causal relationship between two events occurs when a first event meaningfully precedes a second event and is identified by a causality module. The causality module analyzes multiple events to determine whether the events are causally related. Reductions in both required storage space and search operations are obtained by tracing interrelated causal chains of events. Further improvement is achieved by reducing re-computation of wavefront tables through annotating causality chain with information that facilitates determination of validity of a wavefront table.

    摘要翻译： 当第一个事件有意义地在第二个事件之前并且由因果模块识别时，发生两个事件之间的因果关系。 因果模块分析多个事件以确定事件是否与因果关联。 通过追踪事件的相关因果链，可以减少所需的存储空间和搜索操作。 通过利用有助于确定波前表的有效性的信息来注释因果链，减少波前表的重新计算，从而实现进一步的改进。

    Efficient filtered causal graph edge detection in a causal wavefront environment
    6.
    发明申请
    Efficient filtered causal graph edge detection in a causal wavefront environment 审中-公开
    在因果波前环境中有效的过滤因果图边缘检测

    公开(公告)号：US20070032986A1

    公开(公告)日：2007-02-08

    申请号：US11499306

    申请日：2006-08-03

    申请人： Ken Hines ,  Chris Klassen

    发明人： Ken Hines ,  Chris Klassen

    IPC分类号： G06F15/00

    CPC分类号： H04L41/0631 ,  H04L41/22

    摘要： A causal relationship between two events occurs when a first event meaningfully precedes a second event and is identified by a causality module. The causality module analyzes causality of a selected subset of significant events of multiple events using efficient filtered causal graph edge detection in a causal wavefront environment. In various embodiments, efficient filtered causal graph edge detection includes derivation of an inserted event's maximal predecessor set and minimal successor set. As a resultant, reductions in both required storage space and search operations are achieved.

    摘要翻译： 当第一个事件有意义地在第二个事件之前并且由因果模块识别时，发生两个事件之间的因果关系。 因果模块使用有效的过滤因果图边缘检测在因果波前环境中分析了多个事件的选定的重要事件子集的因果关系。 在各种实施例中，有效的过滤因果图边缘检测包括插入事件的最大前导集合和最小后继集合的推导。 因此，实现了所需的存储空间和搜索操作的减少。

    Determining event causality including employment of partitioned event space
    7.
    发明申请
    Determining event causality including employment of partitioned event space 失效
    确定事件因果关系，包括使用分区事件空间

    公开(公告)号：US20050288916A1

    公开(公告)日：2005-12-29

    申请号：US11168258

    申请日：2005-06-27

    申请人： Ken Hines

    发明人： Ken Hines

    IPC分类号： G06F17/50 ,  H04L12/24

    CPC分类号： H04L41/0631

    摘要： Causal relationships between events in a plurality of interrelated causal chains are maintained in a network event space through the partitioning of the event space into event subspaces. In this manner, events sharing the same event subspace stay constant so long as the partitioned subspace is substantially causally consistent. The causality of events from different neighboring subspaces may be determined through the individual subspace determination on each query event until a joining of shared boundary events is possible.

    摘要翻译： 通过将事件空间划分为事件子空间，在网络事件空间中维护多个相互关联的因果链中的事件之间的因果关系。 以这种方式，共享相同事件子空间的事件保持恒定，只要分割的子空间基本上是因果关系一致的。 来自不同相邻子空间的事件的因果关系可以通过每个查询事件的单个子空间确定来确定，直到共享边界事件的加入成为可能。