By Manish Parashar, Salim Hariri
The complexity of contemporary desktop networks and platforms, mixed with the super dynamic environments within which they function, is starting to outpace our skill to control them. Taking yet one more web page from the biomimetics playbook, the autonomic computing paradigm mimics the human autonomic fearful method to unfastened process builders and directors from appearing and overseeing low-level initiatives. Surveying the present course towards this paradigm, Autonomic Computing: options, Infrastructure, and Applications deals a accomplished review of cutting-edge study and implementations during this rising area.
This booklet starts by means of introducing the strategies and standards of autonomic computing and exploring the architectures required to enforce any such approach. the focal point then shifts to the techniques and infrastructures, together with control-based and recipe-based ideas, through permitting structures, applied sciences, and prone proposed for attaining a suite of "self-*" homes, together with self-configuration, self-healing, self-optimization, and self-protection. within the ultimate part, examples of real-world implementations replicate the possibility of rising autonomic structures, similar to dynamic server allocation and runtime reconfiguration and repair.
Collecting state-of-the-art paintings and views from top specialists, Autonomic Computing: thoughts, Infrastructure, and Applications unearths the development made and descriptions the longer term demanding situations nonetheless dealing with this fascinating and dynamic box.
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Extra resources for Autonomic Computing: Concepts, Infrastructure, and Applications
This model allows both IT vendors and customers to approach the introduction of autonomic computing capabilities in a flexible way. For example, one could evaluate the value of introducing a high level of autonomic behavior to a small scope of IT resources in the context of a specific IT process. In another case, one could consider a less aggressive level of self-managing behavior with respect to a broader set of components or processes. The IT process dimension enables a focus on the tasks and best practices for managing IT resources that are discussed next.
Adapted from IBM, An architectural blueprint for autonomic computing. pdf. 1: 1. 1 along the y-axis). 2. Increasing autonomic functionality within one or more components, moving from a position where tasks are completed manually to an autonomic level where components of the infrastructure work in concert to dynamically manage processes based on business policy. 1, increasing levels of automation, correlation, analysis, and adaptation are implemented. 3. Coordinating and integrating functions across IT processes such as incident, change, performance, and security management to enable P1: Binaya Dash September 29, 2006 20:41 9367 9367˙C001 Overview of Autonomic Computing: Origins, Evolution, Direction 9 the system to autonomically address a service requirement that traverses multiple IT processes.
Databases can automatically tune themselves as workload fluctuates and optimize performance as data organization changes. Networking components can intelligently route traffic. Blade servers can automatically populate new blades with the required software as they’re plugged in. The list goes on. However, as described earlier, this is only one aspect of a self-managing autonomic infrastructure. Regardless of the autonomic capabilities built into individual products, unless these components can communicate and effect change in an orchestrated fashion across the infrastructure and across IT processes, the promise of autonomic computing cannot be realized.
Autonomic Computing: Concepts, Infrastructure, and Applications by Manish Parashar, Salim Hariri