Method and system for adapting a network application based on classifying types of communication links using fuzzy logic

• US 6,766,309 B1
• Filed: 07/12/2000
• Issued: 07/20/2004
• Est. Priority Date: 07/14/1999
• Status: Expired due to Fees

• Current Assignee: Rutgers University
• Original Assignee: Ivan Marsic, Liang Cheng
• Inventors: Cheng, Liang, Marsic, Ivan
• Primary Examiner(s): Starks, Jr., Wilbert L.
• Assistant Examiner(s): Booker, Kelvin
• Application Number:
  US09/614,294
• Time in Patent Office: 1,469 Days
• Field of Search: 706/1, 706/3, 706/4, 706/8, 706/52, 706/900, 370/230, 370/235, 700/50, 455/436, 455/438
• US Class Current: 706/3
• CPC Class Codes: H04L 12/1827 Network arrangements for conference optimisation or adaptation
• CPC Class Codes: H04L 12/185 with management of multicast group membership
• CPC Class Codes: H04L 12/5692 Selection among different networks
• CPC Class Codes: H04L 41/00 Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
• CPC Class Codes: H04W 24/00 Supervisory, monitoring or testing arrangements

Abstract

In hybrid communication environments, in which both the wired and wireless communication links in a communication channel can exist in a communication channel, performance of a quality-of-service (QoS) provision can be enhanced if the application knows whether there exist wireless links in the communication channel and adapts its behavior accordingly. The system of the present invention includes a fuzzy reasoning engine which uses quality of service parameters of a communication channel relating to network statistical patterns as fuzzy inputs, and determines a confidence about the existence of wireless links in the communication channel as the output. The quality of service parameters can include a mean value and variance of round trip time of packets communicating between two communication entities over the comunication channel. Based on the determination of the type of link, the application can be adapted in order to provide a predetermined quality of service.

Claims

1. A computer implemented method for adapting a network based application comprising the steps of:

determining input data as numeric data representative of at least one network statistical parameter of an intermediate communication link in an end-to-end communication channel;

determining fuzzy rules to determine the degree of membership of said input data in fuzzy input data using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for said fuzzy input data;

determining fuzzy output data from said input data and said fuzzy input data according to said determined fuzzy rules;

processing said fuzzy output data for determining a confidence of a type of said communication link as either a wired or wireless communication link; and

adapting said network based application based on said confidence of a determined type of said communication link as either a wired or wireless communication link.

2. The method of claim 1 wherein said fuzzy input data comprises at least one fuzzy linguistic variable.

3. The method of claim 1 wherein a singleton fuzzifier is used to determine said membership function.

4. The method of claim 1 wherein a nonsingleton fuzzifier is used to determine said membership function.

5. The method of claim 1 wherein said network statistical parameter is a mean of a round trip time of a packet sent from a first entity and received by a second entity over said communication channel.

6. The method of claim 1 wherein said network statistical parameter is a variance of a round trip time of a packet sent from a first entity and received by a second entity over said communication channel.

7. The method of claim 1 wherein said application is adapted to provide a predetermined quality of service.

8. A system for adapting a network based application comprising:

means for determining input data as numeric data representative of at least one network statistical parameter of an intermediate communication link in an end-to-end communications channel;

a fuzzifier module using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for at least one fuzzy rule for determining fuzzy input data from said input data;

means for determining fuzzy output data coupled to said fuzzifier module for processing said input data and said fuzzy input data according to said at least one fuzzy rule to provide said fuzzy output data to determine the degree of membership of said input data in fuzzy input data; and

a defuzzifier module for converting said fuzzy output data into a confidence of a type of said communication link as either a wired or wireless communication link; and

means for adapting said network based application based on said determined type of said communication link.

9. The method of claim 8 wherein said fuzzy input data comprises at least one linguistic variable.

10. The system of claim 8 wherein a singleton fuzzifier is used to determine said membership function.

11. The system of claim 8 wherein a nonsingleton fuzzifier is used to determine said membership function.

12. The system of claim 8 wherein said network statistical parameter is a mean of a round trip time of a packet sent from a first entity and received by a second entity over said communication channel.

13. The system of claim 8 wherein said network statistical parameter is a variance of a round trip time of a packet sent from a first entity and received by a second entity over said communication channel.

14. The system of claim 8 wherein said application is adapted to provide a predetermined quality of service.

15. A computer implemented method of determining the existence of at least one wireless link in an end-to-end communication channel comprising the steps of:

determining input data as numeric data representative of at least one network statistical parameter of an intermediate communication link in an end-to-end communication channel; and

determining fuzzy rules to determine the degree of membership of said input data in fuzzy input data using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for said fuzzy input data;

determining fuzzy output data from said input data and said fuzzy input data according to said determined fuzzy rules; and

processing said fuzzy output data for determining a confidence,

wherein said fuzzy output data is a confidence of the existence of said wireless link in said communication channel; and

determining the existence of at least one wireless link in said communication channel based on said confidence.

16. The method of claim 15 wherein said step of determining input data comprises the steps of:

assigning an identification to a handshake packet transmitted from a first communication entity over said communication channel to a second communication entity;

recording a sending time instant at said first communication entity when said handshake packet is sent;

transmitting said handshake packet to said second communication entity;

returning said handshake packet from said second communication entity to said first communication entity;

computing a roundtrip time as the difference between a receiving time instant of when the said transmitted handshake packet is received at said first communication entity and said sending time instant; and

determining a mean value and a variance of said computed round trip time as said input data.

17. The method of claim 15 wherein said fuzzy input data comprises at least one fuzzy linguistic variable.

18. The method of claim 15 wherein a singleton fuzzifier is used to determine said membership function.

19. The method of claim 15 wherein a nonsingleton fuzzifier is used to determine said membership function.

20. A computer implemented method for unicast communication between a first communication entity and a second communication entity over an end-to-end communication channel comprising the steps of:

requesting at said first communication entity a service to be performed at said second communication entity, by sending a request over said communication channel;

determining input data as numeric data representative of at least one network statistical parameter of one or more communication links in said communication channel;

determining fuzzy rules to determine the degree of membership of said input data in fuzzy input data using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for said fuzzy input data;

determining fuzzy output data from said input data and said fuzzy input data according to said determined fuzzy rules;

processing said fuzzy output data for determining a confidence of a type of said communication link as either a wired or wireless communication link; and

providing a predetermined quality of service at said second communication entity based on the determination of said confidence of said type of communication link as either a wired or wireless communication link.

21. A system for unicast communication between a first communication entity and a second communication entity comprising:

a communication channel having one or more communication links connecting said first communication entity to said second communication entity;

a proxy gateway in communication with said second communication entity;

said proxy gateway determining input data as numeric data representative of at least one network statistical parameter of a communication link in said communication channel;

a fuzzifier module using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for at least one fuzzy rule for determining fuzzy input data from said input data;

means for determining fuzzy output data coupled to said fuzzifier module for processing said input data and said fuzzy input data according to said at least one fuzzy rule to provide said fuzzy output data to determine the degree of membership of said input data in fuzzy input data; and

a defuzzifier module for converting said fuzzy output data into a confidence of a type of communication link as either a wired or wireless communication link;

providing a predetermined quality of service at said second communication entity based on the confidence of said type of communication link as either a wired or wireless communication link.

22. A computer implemented method for multicast communication between a plurality of communication entities comprising the steps of:

requesting at each of said plurality of communication entities a connection to a multicast session over a communication channel;

determining input data as numeric data representative of at least one network statistical parameter of one or more communication links in said communication channel;

determining fuzzy rules to determine the degree of membership of said input data in fuzzy input data using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for said fuzzy input data;

determining fuzzy output data from said input data and said fuzzy input data according to said determined fuzzy rules;

processing said fuzzy output data for determining a confidence of a type of said communication link as either a wired or wireless communication link;

connecting said communication links determined to have said confidence of said type of communication link as a wired link to a first session;

connecting said communication links determined to have said confidence of said type of communication link as a wireless link to a second session; and

converting communication data being sent to said first session to communicate data useable in said second session.

23. A system for multicast communication between a plurality of communication entities each said communication entity connecting over an end-to-end communication channel comprising:

a session manager determining input data as numeric data representative of at least one network statistical parameter of a communication link in a communications channel, a fuzzifier module using a singleton fuzzifier or a nonsingleton fuzzifier to determine a membership function for determining fuzzy input data from said input data;

means for determining fuzzy output data coupled to said fuzzifier module for processing said input data and said fuzzy input data according to at least one fuzzy rule to provide said fuzzy output data to determine the degree of membership of said input data in fuzzy input data; and

a defuzzifier module for converting said fuzzy output data into said confidence;

means for providing a predetermined quality of service at said second entity based on the determination of said confidence of said type of communication link, connecting said communication links determined to have said confidence of said type of communication link as a wired link to a first session, connecting said communication links determined to have said confidence of said type of communication link as a wireless link to a second session; and

converting communication data being sent to said first session to communicate data useable in said second session.