Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2005-04-05
2005-04-05
Khatri, Anil (Department: 2124)
Data processing: artificial intelligence
Neural network
Learning task
C706S025000, C706S026000
Reexamination Certificate
active
06876988
ABSTRACT:
A method and system for computing a performance forecast for an e-business system or other computer architecture to proactively manage the system to prevent system failure or slow response time. The system is adapted to obtain measured input values from a plurality of internal data sources and external data sources to predict a system's performance especially under unpredictable and dramatically changing traffic levels in an effort to proactively manage the system to avert system malfunction or slowdown. The performance forecasting system can include both intrinsic and extrinsic variables as predictive inputs. Intrinsic variables include measurements of the systems own performance, such as component activity levels and system response time. Extrinsic variables include other factors, such as the time and date, whether an advertising campaign is underway, and other demographic factors that may effect or coincide with increased network traffic.
REFERENCES:
patent: 5491629 (1996-02-01), Fox et al.
patent: 5835902 (1998-11-01), Jannarone
patent: 6055519 (2000-04-01), Kennedy et al.
patent: 6216119 (2001-04-01), Jannarone
patent: 6289330 (2001-09-01), Jannarone
patent: 6327677 (2001-12-01), Garg et al.
patent: 6591255 (2003-07-01), Tatum et al.
patent: 6631360 (2003-10-01), Cook
patent: 6647377 (2003-11-01), Jannarone
patent: WO 9822885 (1998-05-01), None
patent: WO 0019320 (2000-04-01), None
Wu et al. “Combining artificial neural network and ststistic for stock market forecasting”, ACM pp 257-264, 1993.*
Faerman et al, “adaptive performance prediction for distributed data intensive applications”, ACM SC, pp 1-15, 1999.*
Wolters et al., “Limited area numerical weather forecasting on a massively parallel computer”, ACM ICS pp 289-296, 1994.*
Swany et al., “Multivariate resources performance forecasting in the network weather service”, IEEE, pp 1-10, NSF Grant ANI-0123911, 2002.
Harzog Bernd
Helsper David
Jannarone Robert J.
Tatum John T.
Wilkinson Clayton
Khatri Anil
Mehrman Michael J.
Mehrman Law Office P.C.
Netuitive, Inc.
LandOfFree
Enhanced computer performance forecasting system does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Enhanced computer performance forecasting system, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Enhanced computer performance forecasting system will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3376371