Trustworthy autonomic architecture implementations

Abstract

This chapter has presented an implementation and empirical investigation of the proposed trustworthy architecture. Two case examples have been used to demonstrate an implementation of the TrAArch. Experiments are based on different scenarios that replicate real-life systems and operating conditions. The experiments investigate performance differences between the traditional autonomic architecture and the proposed TrAArch. Results show that the proposed architecture has significant performance improvement over the existing architectures and can be relied upon to operate (or manage) almost all levels of autonomic system scale and complexity. The traditional architecture has a narrow envelope of operational conditions in which it is both self-managing and returns satisfactory behaviour, while TrAArch is sufficiently sophisticated to operate efficiently and yield satisfactory results under almost all perceivable operating circumstances. This chapter has also shown the importance of trustworthiness, also referred to as dependability, to autonomic computing and how this can significantly improve the performance of autonomic systems.The TrAArch simulator has also been presented in Section 5.2.1 with a detailed explanation of how to use it. This is particularly important if the reader wants to recreate the experiments presented in this book or design new ones. To help the reader further understand or demonstrate the effect of trustworthiness, it is advisable to design new simulations of different scenarios and analyse the results following the examples presented here. For the self-adapting resource allocation case example, only three scenarios are used in this book. The reader can study more scenarios for this same case example. This can also help as a guide for studying other case studies of choice.