Systems and methods for analyzing network traffic

Details Systems and methods for analyzing network traffic Systems and methods for analyzing network traffic

2000-03-21

2004-04-20

Maung, Zarni (Department: 2157)

Electrical computers and digital processing systems: multicomput

Computer network managing

C709S224000, C709S227000, C370S234000

Reexamination Certificate

active

06725263

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates generally to networks and, more particularly, to forecasting traffic flows on a network.
BACKGROUND OF THE INVENTION
Spurred by technological advances, the telecommunications industry has experienced tremendous growth over the last decade. This is especially true of networks that carry packetized data, such as those networks that make up the Internet. Within the Internet sector, various Internet Service Providers (ISPs) have reported a yearly quadrupling of traffic. As a result, the traffic on networks is rapidly exceeding system capacity. Network planners, therefore, are constantly faced with the issue of whether the network has adequate capacity to support future traffic requirements.
Traffic forecasts are a particularly important component of the capacity planning and budget modeling functions performed by network planners. Given a particular network topology, a network planner uses a traffic forecast to evaluate anticipated circuit utilizations. These circuit utilizations may then be translated into circuit requirements. The network planner may also use a traffic forecast to evaluate various topologies and establish a network build-out plan according to this evaluation.
In general, a network planner is provided with traffic growth estimates. These growth estimates are then combined with actual collected traffic flow statistics to assemble a predictive traffic model.
Typically, the most time-consuming part of the capacity planning and budgeting process is the construction of a traffic matrix that represents the traffic forecasts. Most ISPs serve millions of sources and destinations of traffic, known as hosts. Consequently, a traffic matrix that captures enough information to be meaningful in a network planning context may be very large.
One drawback with conventional traffic forecasting methodology is that the mechanics involved in creating the traffic matrices are not systematic. As a result, the generated circuit utilization data is often unreliable.
Therefore, a need exists for a system and method that provide a systematic approach to traffic forecasting.
SUMMARY OF THE INVENTION
Systems and methods consistent with the present invention address this and other needs by combining observed traffic statistics and projected traffic data in a systematic manner to generate a traffic matrix. The traffic matrix may then be manipulated to generate expected flows to/from each of the nodes in a network.
In accordance with the purpose of the invention as embodied and broadly described herein, a method for analyzing traffic in a network having a plurality of nodes is provided. The method includes forecasting traffic transmitted to and from each of the plurality of nodes based on observed traffic statistics and an estimated growth. The method also includes generating a traffic matrix using the observed traffic statistics and the forecasted traffic associated with each of the plurality of nodes and determining projected traffic between each of the plurality of nodes using the generated traffic matrix.
In another aspect of the present invention, a system for analyzing traffic in a network comprising a plurality of nodes includes a memory configured to store observed traffic statistics. The system also includes a processor configured to forecast traffic transmitted to and from each of the plurality of nodes based on observed traffic statistics and an estimated growth. The processor is also configured to generate a traffic matrix using the observed traffic statistics and the forecasted amount of traffic associated with each of the plurality of nodes and determine projected traffic between each of the plurality of nodes using the generated traffic matrix.


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