Abstract
Self configuration is one of the major properties of self-managing systems that requires the real time processing while adding or removing any existing file or component to maintain the proper working state of the system. In order to achieve self configuration capability, artificial neural networks based self-management technique is proposed in this paper. Artificial Neural Networks (ANN) are capable to solve real-time complex problems that may not be resolved trivially by other learning techniques. In this paper, we propose a self-managing algorithm for autonomic system based on ANN. A prototype of self-configuration using ANN is implemented using autonomic forest fire application. The performance results show that ANN is an effective technique in case of dynamic learning in general and autonomic computing in special.
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References
Parashar, M., Hariri, S.: Autonomic Computing: An Overview. In: Banâtre, J.-P., Fradet, P., Giavitto, J.-L., Michel, O. (eds.) UPP 2004. LNCS, vol. 3566, pp. 247–259. Springer, Heidelberg (2005)
Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing. IEEE Computer, 41–50 (January 2003)
White, S.R., Hanson, J.E., Whalley, I., Chess, D.M., Kephart, J.O.: An Architectural Approach to Autonomic Computing. In: Proc. of International Conference on Autonomic Computing (ICAC). IEEE Computer Society, Los Alamitos (2004)
Xue, T., Feng, B.: An Efficient and Self-Configurable Publish-Subscribe System. In: Li, M., Sun, X.-H., Deng, Q.-n., Ni, J. (eds.) GCC 2003. LNCS, vol. 3032, pp. 159–163. Springer, Heidelberg (2004)
Khan, M.J., Awais, M.M., Shamail, S.: Achieving Self-configuration Capability in Autonomic Systems Using Case-Based Reasoning with a New Similarity Measure. Communication in Computer and Information Science 2, 97–106 (2007)
Sung, H., Han, S., Joo, B., Ang, C., Cheng, W., Wong, K.: A Self-configuration Mechanism for High-Availability Clusters. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3994, pp. 260–263. Springer, Heidelberg (2006)
Kıcıman, E., Wang, Y.: Discovering Correctness Constraints for Self-Management of System Configuration. In: Proc. of International Conference on Autonomic Computing (ICAC). IEEE Computer Society, Los Alamitos (2004)
Aggarwal, G., Datar, M., Mishra, N., Motwani, R.: On Identifying Stable Ways to Configure Systems. In: Proc. of the International Conference on Autonomic Computing (ICAC). IEEE Computer Society, Los Alamitos (2004)
Appleby, K., Fakhouri, S., Fong, L., Goldszmidt, G., Kalantar, M., Pazel, D., Pershing, J., Rochwerger, B.: Oceano - SLA based Management of a Computing Utility. In: Proc. of Integrated Network Management. IEEE, Los Alamitos (2001)
Artificial Neural Networks, http://www.learnartificialneuralnetworks.com (accessed on: November 2, 2009)
Gershenson, C.: Artificial Neural Networks for Beginners, http://arxiv.org/ftp/cs/papers/0308/0308031.pdf (accessed on June 5, 2010)
Yao, X.: Evolving Artificial Neural Networks. Proceedings of The IEEE 87(9), 1423–1447 (1999)
Appavoo, J., Hui, K., Soules, C.A.N., Wisniewski, R.W., Silva, D.M., Da, K.O., Auslander, M.A., Edelsohn, D.J., Gamsa, B., Ganger, G.R., McKenney, P., Ostrowski, M., Rosenburg, B., Stumm, M., Xenidis, J.: Enabling Autonomic Behavior in Systems Software with Hot Swapping. IBM Systems Journal (2003)
Ramdane-Cherif, A.: Toward Autonomic Computing: Adaptive Neural Network for Trajec-tory Planning. International Journal of Cognitive Informatics and Natural Intelligence 1, 16–33 (2007)
Benardos, P.G., Vosniakos, G.C.: Optimizing Feed Forward Artificial Neural Network Architecture. Engineering Applications of Artificial Intelligence 20, 365–382 (2007)
Khan, M.J., Shamail, S., Awais, M.M.: Decision Making in Autonomic Manager using Fuzzy Inference System. In: Proc. of International Conference on Autonomous Systems (ICAS). IEEE Computer Society, Los Alamitos (2009)
Ganek, A.G., Corbi, T.A.: The Dawning of the Autonomic Computing Era. IBM Systems Journal 42, 5–17 (2003)
Fuad, M.M., Oudshoorn, M.J.: An Autonomic Architecture for Legacy Systems. In: Proc. of International Workshop on Engineering of Autonomic and Autonomous System. IEEE, Los Alamitos (2007)
Yoon, B.L.: Artificial Neural Network Technology. ACM SIG SMALL/PC Notes 15, 3–16 (1989)
Paya, A.S., Fernandez, D.R., Mendez, D.G., Hernandez, C.A.M.: Development of an Artificial Neural Network for Helping to Diagnose Diseases in Urology. In: Proc. of International Conference on Bio-Inspired Models of Network, Information and Computing Systems. ACM, New York (2006)
Al-Masri, E., Mahmoud, Q.H.: A Context-Aware Mobile Service Discovery and Selection Mechanism using Artificial Neural Networks. In: Proc. of International Conference on Electronic Commerce. ACM, New York (2006)
Yoon, Y., Peterson, L.L.: Artificial Neural Networks: An Emerging New Technique. In: Proc. of SIGBDP Conference on Trends and Directions in Expert Systems. ACM, New York (1990)
Sondak, N.E., Sondak, V.K.: Neural Networks and Artificial Intelligence. ACM SIGCSE Bulletin 21, 241–245 (1989)
Liu, H., Parashar, M.: A Component Based Programming Framework for Autonomic Applications. In: Proc. of International Conference on Autonomic Computing (ICAC). IEEE Computer Society Press, Los Alamitos (2004)
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Ather, M., Khan, M.J. (2010). Self-configuration Using Artificial Neural Networks. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_3
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DOI: https://doi.org/10.1007/978-3-642-14831-6_3
Publisher Name: Springer, Berlin, Heidelberg
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