Method and apparatus for subscription adaptation
First Claim
1. A method for performing subscription adaptation based on network utilization in a network at a Subscription Adaptation Engine, SAE, the method comprising:
- computing a network utilization metric for a plurality of resource bins of the network, wherein;
each resource bin corresponds to a respective network location and a respective time slot; and
the network utilization metric comprises network utilization data corresponding to at least one of the plurality of resource bins;
computing a subscriber utilization metric for a subscriber of the network, wherein the subscriber utilization metric comprises subscriber utilization data based on activities by the subscriber within the at least one of the plurality of resource bins;
computing a subscriber predictability metric for the subscriber based on the subscriber utilization metric and the network utilization metric;
performing subscriber profiling for the subscriber based on the subscriber utilization metric and the subscriber predictability metric; and
adapting a subscription profile for the subscriber based on the subscriber profiling, thereby enabling service charging based on the adapted subscription profile.
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Abstract
A subscription adaptation engine computes a network utilization metric for a plurality of resource bins, each resource bin representing the network utilization at a network location within a time slot. A subscriber utilization metric is computed for activities by a subscriber within the resource bins and a subscriber predictability metric is computed for the subscriber based on the subscriber utilization metric and network utilization metric. Subscriber profiling is performed for the subscriber based on the subscriber utilization metrics and subscriber predictability metric and a subscription profile for the subscriber is adapted, thereby enabling service charging based on the adapted subscription profile. The amount of real-time or near real-time signaling needed to show a different price for each location and/or time of a user may thereby be reduced.
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Citations
28 Claims
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1. A method for performing subscription adaptation based on network utilization in a network at a Subscription Adaptation Engine, SAE, the method comprising:
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computing a network utilization metric for a plurality of resource bins of the network, wherein; each resource bin corresponds to a respective network location and a respective time slot; and the network utilization metric comprises network utilization data corresponding to at least one of the plurality of resource bins; computing a subscriber utilization metric for a subscriber of the network, wherein the subscriber utilization metric comprises subscriber utilization data based on activities by the subscriber within the at least one of the plurality of resource bins; computing a subscriber predictability metric for the subscriber based on the subscriber utilization metric and the network utilization metric; performing subscriber profiling for the subscriber based on the subscriber utilization metric and the subscriber predictability metric; and adapting a subscription profile for the subscriber based on the subscriber profiling, thereby enabling service charging based on the adapted subscription profile. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A Subscription Adaptation Engine, SAE, for subscription adaptation based on network utilization in a network, comprising:
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a processor; and a memory comprising program code executed by the processor to; compute a network utilization metric for a plurality of resource bins of the network, wherein; each resource bin corresponds to a respective network location and a respective time slot; and the network utilization metric comprises network utilization data corresponding to at least one of the plurality of resource bins; compute a subscriber utilization metric for a subscriber of the network, wherein the subscriber utilization metric comprises subscriber utilization data based on activities by the subscriber within the at least one of the plurality of resource bins; compute a subscriber predictability metric for the subscriber based on the subscriber utilization metric and the network utilization metric; perform subscriber profiling for the subscriber based on the subscriber utilization metric and the subscriber predictability metric; and adapt a subscription profile for the subscriber based on the subscriber profiling, thereby enabling service charging based on the adapted subscription profile. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. A Subscription Adaptation Engine, SAE, for subscription adaptation, the SAE comprising:
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a processor circuitry; a memory containing instructions that, when executed by the processor circuitry, cause the Subscription Adaptation Engine to; compute a network utilization metric for a plurality of resource bins, wherein; each resource bin corresponds to a respective network location and a respective time slot; and the network utilization metric comprises network utilization data corresponding to at least one of the plurality of resource bins; compute a subscriber utilization metric for a subscriber, wherein the subscriber utilization metric comprises subscriber utilization data based on activities by the subscriber within the at least one of the plurality of resource bins; compute a subscriber predictability metric for the subscriber based on the subscriber utilization metric and the network utilization metric; perform subscriber profiling for the subscriber based on the subscriber utilization metric and the subscriber predictability metric; and adapt a subscription profile for the subscriber based on the subscriber profiling, thereby enabling service charging based on the adapted subscription profile.
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28. A computer program product comprising a non-transitory computer readable storage medium storing program code, which when run in a computer being configured as a Subscription Adaption Engine, the program code causes the computer to perform the following steps:
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computing a network utilization metric for a plurality of resource bins, wherein; each resource bin corresponds to a respective network location and a respective time slot; and the network utilization metric comprises network utilization data corresponding to at least one of the plurality of resource bins; computing a subscriber utilization metric for a subscriber, wherein the subscriber utilization metric comprises subscriber utilization data based on activities by the subscriber within the at least one of the plurality of resource bins; computing a subscriber predictability metric for the subscriber based on the subscriber utilization metric and the network utilization metric; performing subscriber profiling for the subscriber based on the subscriber utilization metric and the subscriber predictability metric; and adapting a subscription profile for the subscriber based on the subscriber profiling, thereby enabling service charging based on the adapted subscription profile.
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Specification