Autonomic Computing: Principles, Design and Implementation by Philippe Lalanda, Julie A. McCann, Ada Diaconescu

By Philippe Lalanda, Julie A. McCann, Ada Diaconescu

Autonomic computing is altering the way in which software program platforms are being constructed, introducing the aim of self-managed computing structures with minimum want for human input.

This easy-to-follow, classroom-tested textbook/reference offers a pragmatic standpoint on autonomic computing. during the mixed use of examples and hands-on tasks, the e-book permits the reader to speedily achieve an knowing of the theories, versions, layout ideas and demanding situations of this topic whereas construction upon their present wisdom; therefore reinforcing the recommendations of autonomic computing and self-management.

Topics and features:

* offers a based and entire creation to autonomic computing with a software program engineering perspective
* Supported by means of a downloadable studying atmosphere and resource code that permits scholars to strengthen, execute, and attempt autonomic purposes at an linked website
* offers the newest info on recommendations imposing self-monitoring, self-knowledge, decision-making and self-adaptation
* Discusses the demanding situations to comparing an autonomic approach, helping the reader in designing exams and metrics that may be used to check autonomic computing systems
* studies the main correct resources of proposal for autonomic computing, with tips in the direction of extra huge forte literature
* excellent for a 10-week lecture programme

This concise primer and useful advisor might be of significant use to scholars, researchers and practitioners alike, demonstrating the right way to greater architect strong but versatile software program platforms able to assembly the computing calls for for at the present time and sooner or later.

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Additional resources for Autonomic Computing: Principles, Design and Implementation (Undergraduate Topics in Computer Science)

Example text

Self-configuration must not be concerned with autonomic elements in isolation but the integrated system as a whole. Similarly to the way a new cell is integrated into a body, a new autonomic element must be able to integrate itself into a system’s infrastructure, and the existing system must be able to adapt to the new element. From this perspective, self-configuration becomes an important enabler for the other self-* objectives, such as self-optimisation, self-healing and self-protection. Self-healing: an autonomic system detects, diagnoses and recovers from routine or extraordinary problems while trying to minimise service disruption.

Further relevant fields are discussed in the following chapter highlighting the inspiration that autonomic computing has and can draw from existing domains. P. 1 Definitions Autonomic Systems Autonomic computing (AC) seeks to render computing systems as self-managed. In other words, its objective is to enable computer systems to manage themselves so as to minimise the need for human intervention. In the autonomic computing vision, human administrators merely specify the computer system’s high-level business goals.

They relate to the ability to map the administration function to a process executable by the machine and how easy it is to implant that function into the system. That is, some administration tasks are difficult to define so automating them is correspondingly difficult. Further, it may also be difficult to inject such automation code into some legacy systems where the source code is obscure or non-existent. As we will see later on, different levels of autonomy can thus be targeted. The expected benefits of autonomic computing are numerous and obviously include the decrease of maintenance expenditure and risk.

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