Autonomic Computing: Principles, Design and Implementation (Undergraduate Topics in Computer Science)
Philippe Lalanda, Ada Diaconescu
Language: English
Pages: 288
ISBN: 1447150066
Format: PDF / Kindle (mobi) / ePub
This textbook provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of th
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model-based approach to planning is that, under the assumption that the model correctly mirrors the managed system, the architectural model can be used to verify that system integrity is preserved when applying an adaptation, that is, we can guarantee that the system will continue to operate correctly after the planned adaptation has been executed. This is because changes are planned and applied to the model first, which will show the resulting system state including any violations of constraints
under widely different lighting conditions and sensor data may become faulty or incomplete. High radiation levels and widely varying temperatures raise further difficulties by limiting available computational resources. The significance of autonomy for the success of this type of space missions was highlighted in one of NASA’s 50th anniversary articles (2008) [31], in the context of Mars exploration programs: The vehicles used to explore the Martian surface require a high degree of autonomy to
charge of implementing rapid actions in response to some well-defined conditions in the environment. The proactive part, which can be executed on remote, more suitable resources, deals with state conservation and complex reasoning. Based on its findings, this deliberative part can update the reactive part. For instance, it can change some parameters, change reflex rules or even add or remove rules. This approach retains advantages of both worlds but is difficult to realise. 4.3 Autonomic Manager
later transmitted to the autonomic managers’ monitor components. Preprocessing is optional and may be executed either by sensors (before communication), by monitors (after communication) or by both. On the sensor side, some analysis code can be added to enable the preprocessing of the information gathered by the probes to reduce sensing communication costs. For example, the sensing function may obtain response times every 5 s but only report the average response time per minute to the autonomic
knowledge to produce the data that feeds the published stream of notifications, in this instance. The assumption thus far has been that the code to monitor the autonomic system is placed on the same hardware as the autonomic system itself (Fig. 5.2a). However if economic costs are not prohibitive, there is nothing to prevent the system’s architecture being composed of nodes dedicated solely to the monitoring and management of the system, while the remaining nodes are the nodes that run the
