Multiplex communications – Network configuration determination
Reexamination Certificate
1999-12-15
2003-10-28
Olms, Douglas (Department: 2661)
Multiplex communications
Network configuration determination
C370S255000, C706S015000
Reexamination Certificate
active
06639900
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Technical Field
The present invention generally relates to determining physical network topology of heterogeneous networks and in particular to determining physical network topology without employing vendor-dependent information for network devices. Still more particularly, the present invention relates to employing neural networks to generically classify and physically group network devices based on communications parameters from a selected network device including round trip time, bottleneck link speed and hop count.
2. Description of the Related Art
Computer networks are essential features of contemporary computing, providing the framework for exchange of data and execution of distributed applications, either through client-server interaction such as HyperText Transmission Protocol clients and servers or collaborative operation such as failover redundancy in highly available networks. In order to efficiently perform tasks, most networking and system management applications today require a knowledge of the underlying physical network topology. However, existing topology applications provide, at best, only an approximation of the actual physical topology.
A variety of different reasons contribute to the use of approximations for network physical topologies in contemporary applications. The primary reason, however, is that a substantial number of network devices (e.g., network interface cards or adapters) do not implement any functions or variables which would allow those network devices to be “discovered” or automatically identified and/or classified by a topology application. Even when functions or variables are implemented by a network device to provide information to topology applications, the information is provided in a manufacturer-dependent, and often private, manner.
Currently, the most common technique utilized by topology applications to discover physical topology involves extracting topology information from each individual network device within the network utilizing the Simple Network Management Protocol (SNMP). This is not a simple task because, as noted above, no standard exists across different manufacturers or vendors for organizing or classifying physical network topology information. For example, Cisco Systems may employ a particular data structure to describe the connection to their devices while 3COM Corporation employs an entirely different data structure, which may or may not include all of the same variables as the Cisco data structure, to describe their connection.
It would be desirable, therefore, to be able to determine physical network topology without knowing or utilizing any vendor-specific information. It would further be advantageous to employ physical topology information which relies only on information which is readily available within any heterogeneous network.
SUMMARY OF THE INVENTION
It is therefore one object of the present invention to provide an improved method, apparatus, and computer program product for determining physical network topology of heterogeneous networks.
It is another object of the present invention to provide a method, apparatus, and computer program product for determining physical network topology without employing vendor-dependent information for network devices.
It is yet another object of the present invention to employ neural networks to generically classify and physically group network devices based on communications parameters from a selected network device including round trip time, bottleneck link speed and hop count.
The foregoing objects are achieved as is now described. Round trip time, bottleneck link speed, and hop count information from one node to the remaining nodes within a network is collected and processed by an adaptive resonance theory (ART) neural network to classify the nodes by physical location or site group. For each site group, round trip time from one node to the remaining nodes is then collected and processed utilizing an ART neural network to classify the nodes into one or more physical groups. The resulting breakdown of site groups within the network and physical groups within the site groups forms a model which may be employed by networking and system management applications. No private or proprietary vendor specific information from communications devices within the network need be employed to develop the model, only publicly available information regarding communications parameters.
The above as well as additional objectives, features, and advantages of the present invention will become apparent in the following detailed written description.
REFERENCES:
patent: 5606664 (1997-02-01), Brown et al.
patent: 5684796 (1997-11-01), Abidi et al.
patent: 5710885 (1998-01-01), Bondi
patent: 5727157 (1998-03-01), Orr et al.
patent: 5751964 (1998-05-01), Ordanic et al.
patent: 5822535 (1998-10-01), Takase et al.
patent: 5845277 (1998-12-01), Pfeil et al.
patent: 5848243 (1998-12-01), Kulkarni et al.
patent: 5864862 (1999-01-01), Kriens et al.
patent: 5926463 (1999-07-01), Ahearn
patent: 6119235 (2000-09-01), Vaid
patent: 6125105 (2000-09-01), Edwards
patent: 6209033 (2001-03-01), Datta
patent: 6216163 (2001-04-01), Bharali
patent: 6260072 (2001-07-01), Rodriguez-Moral
patent: 6542468 (2003-04-01), Hatakeyama
James W. Hong, Michael A. Bauer and J. Michael Bennett,The Role of Directory Services in Network Management, Sep. 28, 1992, pp. 175-187.
Chung Sheng Li, Yoram Ofek and Moti Yung, “Time-Driven Priority ” Flow Control for Real-Time Heterogeneous Internetworking, Aug. 3, 1995.
U.S. patent application Ser. No. 09/465,182, Barillaud, filed Dec. 15, 1999.
U.S. patent application Ser. No. 09/465,183, Barillaud, filed Dec. 15,1999.
Anstey Kathy Alice
Barillaud Franck
Croft, Jr. Allen Jackson
Linton John Ferguson
Marinos Demetrios James
Bracewell & Patterson L.L.P.
Dawkins Marilyn Smith
Olms Douglas
Pizarro Ricardo M.
LandOfFree
Use of generic classifiers to determine physical topology in... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Use of generic classifiers to determine physical topology in..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Use of generic classifiers to determine physical topology in... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3124769