Abstract
Autonomic computing when first introduced, there was apprehension whether it would become a reality. It is a concept that merges many fields of computing area to give a system which is easily manageable and thus reduce the complexities faced by IT industry today. The term Autonomic Level gives the quantification measurement about the autonomic features, a system has. This paper starts by brief introduction to autonomic systems. It proposes a framework for assessing the Level of Autonomic features of the system and also presents some of the quality metrics that may be used in future to evaluate the proposed framework. The evaluation section contains the mathematical model of the framework and case study shows the implementation of the model using fuzzy- AHP soft computing technique.
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Sharma, A., Sharma, D., Singh, M. (2018). Assessing Autonomic Level for Self-managed Systems – FAHP Based Approach. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-13-1810-8_12
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DOI: https://doi.org/10.1007/978-981-13-1810-8_12
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