System and Methods for Time Dependent Internet Pricing

Abstract

Apparatuses, systems and methods for implementing time-dependent pricing for Internet data traffic in wireless/broadband access networks are disclosed. Such systems may include: (i) A price-optimization computational module that takes in historical and current network congestion and historical and predicted user reactions to compute the best time-dependent prices to minimize the total cost incurred to the wireless network operator; (ii) A user profiling module that takes in user reaction data to characterize a model of how much traffic that may be defer to a later point in time under a given pricing incentive; (iii) A user interface module that displays the computed prices that vary over time, so that a user (or their agent) can choose which time it should use a certain amount of mobile data; and (iv) A network measurement module that collects the actual traffic coming from each application over each period of time.

What is claimed is: 
     
         1 . A system and methods of enabling, optimizing, and leveraging time-dependent pricing for mobile data traffic in wireless and wireline networks, wherein the system comprises:
 (i) a price-optimization computational module that takes in historical and current network congestion and historical and predicted user reactions to compute the best time-dependent prices for a plurality of upcoming timeslots so as to minimize the total cost incurred to the wireless network operator,   (ii) a user profiling module that takes in user reaction data to characterize a model of how much traffic each user s application will be willing to defer to a later point in time under a given pricing incentive,   (iii) a user interface module that displays the computed prices that vary over time, so that a user, or an automatic agent acting on behalf of the user, can choose which time it should use a certain amount of mobile data,   (iv) a network measurement module that collects the actual traffic coming from each application, or a group of applications, from each user and device, over each period of time.   
     
     
         2 . The method of  claim 1 , wherein the price optimization module solves a mathematical problem of optimization to compute the optimal or suboptimal prices. 
     
     
         3 . The method of  claim 1 , wherein the user profiling module computes delay tolerance, relative to price sensitivity, of each application on each mobile or fixed device in use by a consumer of an organization. 
     
     
         4 . The method of  claim 1 , wherein the user interface module allows an auto-pilot mode, where the end user does not need to make each decision on time-deferral but only needs to specify certain parameters and objectives of its user experience. 
     
     
         5 . The method of  claim 4 , wherein the auto-pilot decisions are made partially on end user devices and partially on network operators' devices, such as servers and gateways with processors, volatile and non-volatile memories, and a plurality of input and output interfaces, in cellular core networks, broadband access control networks, backbone networks, or data center networks. 
     
     
         6 . The method of  claim 1 , wherein the network traffic and user reaction data are collected on end user devices, or on network operator devices, or a combination of both types of devices. 
     
     
         7 . The system is further programmed to:
 Allow network operators to dynamically, over a plurality of possible timescales, adjust the price charged for each unit of data traffic based on user preferences, time of day, congestion conditions in historical records and current conditions, and application needs.   Allow users to see, understand, and respond with decisions of deferring an application or not, to the dynamically adjusted prices with the help of visualization, recommendation, prediction, and automatic agents that take into account both price sensitivity and delay tolerance of each application at each time.   
     
     
         8 . The system is further programmed to:
 Allow a feedback loop between the user reactions and the network operator's user profiling and price optimization.   
     
     
         9 . The methods of  claim 7  wherein the functionalities of network measurement, user profiling, price optimization, and user interface are divided among the end user devices, the network operator servers, and other network elements in a flexible and dynamic way.