5G Slice Pricing Function
A method for providing Radio Access Network (RAN) slice pricing is described. In one embodiment, the method includes capturing costs associated with a particular pairing of a particular user to a particular slice using weighted values configurable by an operator; and creating and deleting network slices in accordance with a pricing function associated with the captured costs for a particular user for a particular slice.
1 . A method for providing Radio Access Network (RAN) slice pricing, comprising:
capturing costs associated with a particular pairing of a particular user to a particular slice using weighted values configurable by an operator; and
creating and deleting network slices in accordance with a pricing function associated with the captured costs for a particular user for a particular slice.
2 . The method of claim 1 wherein a cost of a particular pairing is captured using weighted values.
3 . The method of claim 1 wherein using weighted values includes using weights given to performance slowdown for other users/slices, overhead required to create and service a slice, bandwidth and latency that are reserved or used up when a slice is paired, cloud service availability, core network service availability, and RAN backhaul availability,
4 . The method of claim 1 wherein the weights are configurable by the operator.
5 . The method of claim 1 wherein a creation and deletion of new slices and the associated overhead is accommodated in the pricing function.
6 . The method of claim 1 further comprising an operator assigning weights to enable rapid creation of new slices without assigning dedicated performance resources to the slices until needed.
7 . The method of claim 1 further comprising dedicating performance resources to each slice by heavily penalizing new slice creation/pairing.
8 . The method of claim 1 further comprising assigning different RATs different slice pricing.
9 . The method of claim 1 further comprising using different pricing algorithms for the pricing function.
10 . The method of claim 1 further comprising performing dynamic price optimization by performing analysis of slice pricing data over time.
11 . The method of claim 10 wherein performing dynamic price optimization includes at least one of by using experimentation and active learning, optimization with and without pricing policy constraints, and demand modeling.
12 . The method of claim 1 further comprising configuring the pricing function to operate where the slice pairing takes place, in order to enable the pricing function to have as much information as possible regarding at least one of availability of overhead for slice creation; available CPU and band width resources; available RAN resources; available spectrum resources.
13 . The method of claim 1 further comprising configuring automated bidding by individuals, agents, and software policies.
14 . The method of claim 1 further comprising integrating QoS/QCI into the slice pairing and slice pricing functions.