Processing event data streams to recognize event patterns, with conditional query instance shifting for load balancing
First Claim
1. A computer-implemented method for recognizing an event pattern for objects that belong to an event domain, the method comprising:
- activating a pattern query that corresponds to the event pattern and that has at least one state with a distinctive transition probability to reach a final query state, said distinctive transition probability representing a lower transition probability of said at least one state to reach said final state, said lower probability is lower compared to at least one other transition probability to reach said final state of at least one second state, other than said at least one state, the probability being derived from object observations in the event domain;
wherein an instance reaching said distinctive transition probability state uses a longer time interval than an instance not reaching said distinctive transition probability state;
continuously receiving event representations, that are related to the objects;
allocating the event representations to a first processing resource to initiate instances of the query;
monitoring the instances and, upon receiving event representations that cause an instance of said instances to reach the state with the distinctive transition probability, shifting the instance to a second processing resource that is more optimized for handling longer time interval than said first processing resource.
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Accused Products
Abstract
A computer (100) recognizes an event pattern (ABC) for objects (14, 24, 34, 44) that belong to an event domain (150). The computer activates a pattern query (110) that corresponds to the event pattern (ABC) and that has a least one state (S4) with an distinctive transition probability to a final state. The probability is derived from object observations in the event domain (150). The computer continuously receives event representations (*A14, *A24, *A44, *D44, . . . ) that are related to the objects (14, 24, 34, 44) and allocates the event representations to a first processing resource (101) to initiate instances (1.14, 1.24, 1.34, 1.44) of the query (110). It monitors the instances and, upon receiving event representations that cause the instances to reach the state (S4) with the distinct transition probability, it shifts the instances to a second processing resource (102).
9 Citations
17 Claims
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1. A computer-implemented method for recognizing an event pattern for objects that belong to an event domain, the method comprising:
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activating a pattern query that corresponds to the event pattern and that has at least one state with a distinctive transition probability to reach a final query state, said distinctive transition probability representing a lower transition probability of said at least one state to reach said final state, said lower probability is lower compared to at least one other transition probability to reach said final state of at least one second state, other than said at least one state, the probability being derived from object observations in the event domain;
wherein an instance reaching said distinctive transition probability state uses a longer time interval than an instance not reaching said distinctive transition probability state;continuously receiving event representations, that are related to the objects; allocating the event representations to a first processing resource to initiate instances of the query; monitoring the instances and, upon receiving event representations that cause an instance of said instances to reach the state with the distinctive transition probability, shifting the instance to a second processing resource that is more optimized for handling longer time interval than said first processing resource. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer for recognizing an event pattern for objects that belong to an event domain, the computer comprising:
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a pattern query activator that corresponds to the event pattern and that activates a pattern query that has at least one state with a distinctive transition probability to reach a final state of the query, said distinctive transition probability representing a lower transition probability of said at least one state to reach said final state, said lower probability is lower compared to at least one other transition probability to reach said final state of at least one second state, other than said at least one state, the probability being derived from object observations in the event domain, wherein an instance reaching said distinctive transition probability state uses a longer time interval than an instances not reaching said distinctive transition probability state; a receiver that continuously receives event representations that are related to the objects; an allocator that allocates the event representations to a first processing resource of the computer to initiate instances of the query; and a monitor that monitors the instances and, upon receiving event representations that causes an instance of said instances to reach the state with the distinctive transition probability, shifts the instance to a second processing resource of the computer that is more optimized for handling longer time interval than said first processing resource. - View Dependent Claims (14, 15, 16, 17)
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Specification