Intelligent realtime monitoring of data traffic

• US 5,974,457 A
• Filed: 12/23/1993
• Issued: 10/26/1999
• Est. Priority Date: 12/23/1993
• Status: Expired due to Term

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Daugherty, Raymond F., Waclawsky, John G., Hershey, Paul C.
• Primary Examiner(s): Voeltz, Emanuel T.
• Assistant Examiner(s): CHOI, KYLE JAEHUN
• Application Number:
  US08/172,701
• Time in Patent Office: 2,133 Days
• Field of Search: 364/550, 364/551.01, 364/579, 364/580, 364/489, 364/490, 364/514 C, 364/514 R, 371/27, 395/21, 395/51, 395/917
• US Class Current: 709/224
• CPC Class Codes: H04L 41/14 Network analysis or design
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/0852 Delays
• CPC Class Codes: H04L 43/0888 Throughput
• CPC Class Codes: Y10S 706/917 Communication

Abstract

The invention features a system and method to enable real-time establishment and maintenance of a standard of operation for a data communications network. The standard is a data set which includes network activity which is historically categorized by traffic type and by activity. The process begins with monitoring the network media or some network component over some period of time. The monitoring information is used to build benchmark data sets. The benchmark data sets contain a standard of operation for the network, which are historically categorized by either traffic type or activity. This standard of operation is constantly built by the intelligent monitoring facilities. After some period of time which is referred to as the benchmark data set refresh interval, the benchmark that was created is employed in a fashion to allow a determination as to whether the data that is taken from the current monitoring activity indicates normal network behavior. If the current network operating characteristics are outside the bounds or normal behavior, then alerts and logs of information can be sent to the expert system. The expert system can then effect some network control. In this manner, auto benchmarking is accomplished with self customization.

Claims

1. In a system for intelligent real time monitoring of a data communications network which communicates using a serial stream of binary bits having characteristic patterns, a method for outputting monitoring and controlling signals which are customized by classes of traffic on the network, comprising:

inputting one or more event vectors from an Event Driven Interface coupled to a data communications network;

storing a first criteria of rules in said system for a first class of traffic in said network with a standard for said first class of traffic in said network;

storing in said system a first benchmark data set as said standard for said first class of traffic, said first benchmark data set being derived from previously monitored events of said first class of traffic in said network;

accessing said first criteria of rules and comparing information derived from said inputted event vectors with said standard for said first class of traffic, using said first criteria of rules;

outputting an inference signal in response said comparison to manage and control said first class of traffic on said network;

displaying a graphical representation of the behavior of the first class traffic using the inference signal for said first class of traffic.

2. The method of claim 1 which further comprises:

accessing a second criteria of rules to compare information derived from an event vector for a second class of traffic in said network with a standard for a second class of traffic in said network, in response to said inference signal.

3. The method of claim 1 which further comprises the step of:

logging said inference signals and information derived from said event vector.

4. The method of claim 1 wherein said first class of traffic is batch traffic and said graphical representation shows the throughput characteristics of said first class of traffic.

5. The method of claim 1 wherein said first class of traffic is video traffic and said graphical representation shows the delay characteristics of said first class of traffic.

6. The method of claim 1 which further comprises:

substituting a second benchmark data set for said first benchmark data set as said standard to be used by said first criteria of rules, after a predetermined period of time.

7. The method of claim 6 wherein said predetermined period of time is determined by a second criteria of rules in said system.

8. The method of claim 1 which further comprises:

outputting criteria modification signals to said expert system by said intelligent monitor in response to said inference signals.

9. The method of claim 1 which further comprises:

generating one or more alerts by said intelligent monitor in response to said inference signals.

10. The method of claim 1 which further comprises:

modifying the first criteria or rules by an operator.

11. A system for intelligent real-time monitoring using an event driven interface for analyzing the output of a data communications network which communicates using a serial stream of binary bits having characteristic patterns, comprising:

an event vector register coupled to the event driven interface, for receiving event vectors that characterize the behavior of the data communications network, each event vector descriptive of one or more classes of traffic occurring on the data communications network;

an expert system, having an input coupled to said event vector register, for receiving information from said event vectors, said expert system having one or more criteria modules, each criteria module associated with a class of traffic and a standard for said associated class of traffic, each criteria module having rules for characterizing the traffic on the network by comparing information represented by the event vectors with a standard of behavior associated with the class of traffic associated with the criteria module;

said expert system outputting one or more inference signals, each inference signal associated with a class of traffic on the network; and

an intelligent real-time monitor that outputs signals to said data communications network in response to said inference signals to mange and control said classes of traffic in said data communications network and displaying a specific graphical representation of each inference signal based upon the associated class of traffic.

12. The system of claim 11 having a batch class of traffic wherein said specific graphical representation shows throughput characteristics of said batch class of traffic.

13. The system of claim 11 shaving a video class of traffic and wherein said specific graphical representation shows delay characteristics of said video class of traffic.

14. The system of claim 11 having an interactive class of traffic and wherein said specific graphical representation shows response time characteristics of said interactive class of traffic.

15. The system of claim 11 having a batch class of traffic, a video class of traffic, an interactive class of traffic wherein said specific graphical representation shows throughput characteristics of said batch class of traffic, shows delay characteristics of said video class of traffic and shows response time characteristics of said interactive class of traffic.

16. The system of claim 11 wherein said intelligent monitor outputs criteria module modification signals to said expert system in response to said inference signals.

17. The system of claim 11 wherein said intelligent generates one or more alerts in response to said inference signals.

18. The system of claim 11 wherein said intelligent monitor permits an operator to modify the criteria modules.