Electrical computers and digital processing systems: multicomput – Computer-to-computer data addressing
Reexamination Certificate
2000-05-24
2004-11-02
Dharia, Rupal (Department: 2141)
Electrical computers and digital processing systems: multicomput
Computer-to-computer data addressing
C709S238000, C370S392000
Reexamination Certificate
active
06813645
ABSTRACT:
THE FIELD OF THE INVENTION
The present invention relates to a network usage data recording system and method, and more particularly, to a network usage data recording system and method employing a configurable rule engine with IP address range matching for the processing and correlation of network data.
BACKGROUND OF THE INVENTION
Network systems are utilized as communication links for everyday personal and business purposes. With the growth of network systems, particularly the Internet, and the advancement of computer hardware and software technology, network use ranges from simple communication exchanges such as electronic mail to more complex and data intensive communication sessions such as web browsing, electronic commerce, and numerous other electronic network services such as Internet voice, and Internet video-on-demand.
Network usage information does not include the actual information exchanged in a communications session between parties, but rather includes metadata (data about data) information about the communication sessions and consists of numerous usage detail records (UDRs). The types of metadata included in each UDR will vary by the type of service and network involved, but will often contain detailed pertinent information about a particular event or communications session between parties such as the session start time and stop time, source or originator of the session, destination of the session, responsible party for accounting purposes, type of data transferred, amount of data transferred, quality of service delivered, etc. In telephony networks, the UDRs that make up the usage information are referred to as a call detail records or CDRs. In Internet networks, usage detail records do not yet have a standardized name, but in this application they will be referred to as internet detail records or IDRs. Although the term IDR is specifically used throughout this application in an Internet example context, the term IDR is defined to represent a UDR of any network.
Network usage information is useful for many important business functions such as subscriber billing, marketing & customer care, and operations management. Examples of these computer business systems include billing systems, marketing and customer relationship management systems, customer churn analysis systems, and data mining systems.
Several important technological changes are key drivers in creating increasing demand for timely and cost-effective collection of Internet usage information. One technological change is the dramatically increasing Internet access bandwidth at moderate subscriber cost. Most consumers today have only limited access bandwidth to the Internet via an analog telephony modem, which has a practical data transfer rate upper limit of about 56 thousand bits per second. When a network service provider's subscribers are limited to these slow rates there is an effective upper bound to potential congestion and overloading of the service provider's network. However, the increasing wide scale deployments of broadband Internet access through digital cable modems, digital subscriber line, microwave, and satellite services are increasing the Internet access bandwidth by several orders of magnitude. As such, this higher access bandwidth significantly increases the potential for network congestion and bandwidth abuse by heavy users. With this much higher bandwidth available, the usage difference between a heavy user and light user can be quite large, which makes a fixed-price, all-you-can-use pricing plan difficult to sustain; if the service provider charges too much for the service, the light users will be subsidizing the heavy users; if the service provider charges too little, the heavy users will abuse the available network bandwidth, which will be costly for the service provider.
Another technological change is the rapid growth of applications and services that require high bandwidth. Examples include Internet telephony, video-on-demand, and complex multiplayer multimedia games. These types of services increase the duration of time that a user is connected to the network as well as requiring significantly more bandwidth to be supplied by the service provider.
Another technological change is the transition of the Internet from “best effort” to “mission critical”. As many businesses are moving to the Internet, they are increasingly relying on this medium for their daily success. This transitions the Internet from a casual, best-effort delivery service into the mainstream of commerce. Business managers will need to have quality of service guarantees from their service provider and will be willing to pay for these higher quality services.
Due to the above driving forces, Internet service providers are moving from current, fixed-rate, all-you-can-use Internet access billing plans to more complex billing plans that charge by metrics, such as volume of data transferred, bandwidth utilized, service used, time-of-day, and subscriber class, which defines a similar group of subscribers by their usage profile, organizational affiliation, or other attributes. An example of such a rate structure might include a fixed monthly rate portion, a usage allocation to be included as part of the fixed monthly rate (a threshold), plus a variable rate portion for usage beyond the allocation (or threshold). For a given service provider there will be many such rate structures for the many possible combinations of services and subscriber classes.
Network usage data recording systems are utilized for collecting, correlating, and aggregating network usage information as it occurs (in real time or near real time) and creating UDRs as output that can be consumed by computer business systems that support the above business functions. It may be necessary to correlate different types of network usage data obtained from independent network data sources to obtain information required by certain usage applications.
For billing applications, network usage data is correlated with network session information. Network usage data for a given usage event typically includes a source IP address, a destination IP address, byte count or packet counts (i.e., amount of data transferred across a given connection) and a time stamp. Network usage data does not identify whom the user or billing party was that actually performed the action or usage event. Network session information typically includes a source IP address, a time stamp (e.g., start time and end time) and a user name. A usage application for billing purposes requires user names and byte counts. As such, network usage data must be correlated with network session information in order to create a usage record having an association between a billable account and the usage event.
In known usage data recording systems, network usage data received from a network usage data metering source and network session information received from a network session data metering source are fed directly into a central processing system for correlation of the network usage data and network session information. The network usage data and network session information are fed into the central processing system in real time or near real time, as the usage events occur. The network usage data metering source is independent from the network session metering source. The network usage data and network session information is collected and transferred at different rates (i.e., different speeds) and in different data formats, which must be compensated for at the central processing system. It is necessary to provide a queuing process at the central processing system in order to link up the network usage event with the correct network session event. Such queuing often creates a bottleneck at the central processing system. Also, if an error occurs at the central processing system (e.g., loss of power; data fault or other error), data which has not yet been correlated and persistently stored, such as queue data, may be lost.
A range of IP addresses may be allocated to a single customer. It is desirable to
Dharia Rupal
Hewlett--Packard Development Company, L.P.
Nguyen Quang N.
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