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Learning To Detect and Avoid Run-Time Feature Interactions in Intelligent Networks
October 1998 (vol. 24 no. 10)
pp. 818-830

Abstract—The Intelligent Network (IN) allows rapid changes in the services provisioned and their functionality. Services may be supplied by different service providers, making it unlikely that all service specifications will be available for examination by any single agency. Approaches to handle feature interaction problems must be able to operate within these constraints. Work by the authors has produced a generic run-time feature interaction manager (FIM) concept to manage feature interactions in a live network. It monitors features as black-boxes, learns their "correct" behavior and uses this to determine when feature interactions have occurred. This paper describes and compares experiences using three different techniques to realize the proposed approach. These are: states sequence monitoring, artificial neural networks (ANN), and rule-based monitoring which also includes integrated generic resolution approaches. The paper explores the design alternatives with the various techniques, and reports on the results obtained from experimentation.

[1] S. Tsang and E.H. Magill, "Detecting Feature Interactions in the Intelligent Network," Proc. Second Int'l Workshop Feature Interactions in Telecommunications Systems, L.G. Bouma and H. Velthuijsen, eds., ISBN 90 5199 165 7, pp. 236-248, IOS Press, 1994.
[2] D. Marples, S. Tsang, E.H. Magill, and D.G. Smith, "A Platform for Modelling Feature Interaction Detection and Resolution Techniques," Proc. Third Int'l Workshop Feature Interactions in Telecommunications Systems, K.E. Cheng and T. Ohta, eds., ISBN 90 5199 238 6, pp. 185-199, IOS Press, 1995.
[3] S. Tsang and E.H. Magill, "Behaviour Based Run-Time Feature Interaction Detection and Resolution Approaches for Intelligent Networks," Proc. Fourth Int'l Workshop Feature Interactions in Telecommunications Systems, P. Dini, R. Boutaba, and L. Logrippo, eds., ISBN 90 5199 347 1, pp. 254-270, IOS Press, 1997.
[4] A.J. Maren, C.T. Harston, and R.M. Pap, Handbook of Neural Computing Applications, ISBN 0-12-546090-2. Academic Press, 1990.
[5] I. Aleksander and H. Morton, Neurons and Symbols, ISBN 0 412 46090 4. Chapman and Hall, 1993.
[6] K. Najim and A.S. Poznyak, Learning Automata Theory and Applications, ISBN 0 08 942024 9. Pergamon, 1994.
[7] J.M. Tazelaar, "Neural Networks In Depth," Byte, p. 214, Aug. 1989.
[8] T. Frisch, M. Mittler, and P. Tran-Gia, "Artificial Neural Net Applications in Telecommunication Systems," Neural Computing and Applications, pp. 124-146, 1993.
[9] W.P. Jones and J. Hoskins, "Back-Propagation," Byte, pp. 155-162, Oct. 1987.
[10] J. Alspector, "Neural-Style Microsystems that Learn," IEEE Comm., vol. 27, no. 11, pp. 29-36, Nov. 1989.
[11] R.P. Lippmann, "Pattern Classification Using Neural Networks," IEEE Communications Magazine, pp. 47-64, Nov. 1989.
[12] Y. Le Cun, L.D. Jackel, B. Boser, J.S. Denker, H.P. Graf, I. Guyon, D. Henderson, R.E. Howard, and W. Hubbard, "Handwritten digit recognition: Applications of neural network chips and automatic learning," IEEE Comm. Magazine. Nov. 1989.
[13] A. Waibel and J. Hampshire, "Building Blocks for Speech," Byte, pp. 235-242, Aug. 1989.
[14] R. Leighton, "Aspirin/MIGRAINES v5.0 User Manual," obtained by anonymous FTP from the following site: ftp.cs.cmu.edu, 1993.
[15] S. Tsang, "Analysis and Control of Service Behavior for Run-Time Feature Interaction Management in Intelligent Network," PhD thesis, Dept. of Electronic and Electrical Engineering, Univ. of Strathclyde, Glasgow, Scotland, 1997.
[16] S. Homayoon and H. Singh, "Methods of Addressing the Interactions of Intelligent Network Services with Embedded Switch Services," IEEE Comm., vol. 26, no. 12, pp. 42-70, Dec. 1988.
[17] M. Cain, "Managing Run-Time Interactions Between Call-Processing Features," IEEE Comm., vol. 30, no. 2, pp. 44-50, Feb. 1992.
[18] L. Schessel, "Administrable Feature Interaction Concept," ISS'92, vol. 2, no. B6.3, pp. 122-126, Oct. 1992.
[19] N. Fritsche, "Runtime Resolution of Feature Interactions in Architectures with Separated Call and Feature Control," Proc. Third Int'l Workshop Feature Interactions in Telecommunications Systems, K.E. Cheng and T. Ohta, eds., ISBN 90 5199 238 6, pp. 43-64, IOS Press, 1995.
[20] D. Marples, E.H. Magill, and D.G. Smith, "An Infrastructure for Feature Interaction Resolution in a Multiple Service Environment, the Application of Transaction Processing Techniques to the Feature Interaction Problem," Proc. TINA'95, vol. 1, pp. 231-242, Feb. 1995.
[21] A.M. Lister and R.D. Eager, Fundamentals of Operating Systems, ISBN 0-333-46986-0. Maxmillan Press, fourth edition, 1988.
[22] R.H. Campbell and B. Randell, “Error Recovery in Asynchronous Systems,” IEEE Trans. Software Eng., vol. 12, no. 8, pp. 811-826, Aug. 1986.
[23] S. Tsang et al., "The Feature Interaction Problem in Networked Multimedia Service—Present and Future," BT Technology J., Vol. 15, No. 1, Jan. 1997, pp. 235-246.
[24] N.D. Griffeth and H. Velthuijsen, "The Negotiating Agents Approach to Runtime Feature Interaction Resolution," Proc. Second Int'l Workshop Feature Interactions in Telecommunications Systems, L.G. Bouma and H. Velthuijsen, eds., pp. 217-235, ISBN 90 5199 165 7, IOS Press, 1994.
[25] B. Kelly, M. Crowther, J. King, R. Masson, and J. DeLaypeyre, "Service Validation and Testing," Proc. Third Int'l Workshop Feature Interactions in Telecommunications Systems, K.E. Cheng and T. Ohta, eds., pp. 173-184, ISBN 90 5199 238 6, IOS Press, 1995.

Index Terms:
Feature interaction management, intelligent networks, artificial neural networks.
Citation:
Simon Tsang, Evan H. Magill, "Learning To Detect and Avoid Run-Time Feature Interactions in Intelligent Networks," IEEE Transactions on Software Engineering, vol. 24, no. 10, pp. 818-830, Oct. 1998, doi:10.1109/32.729682
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