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autonomic computing : ウィキペディア英語版
autonomic computing

Autonomic computing refers to the self-managing characteristics of distributed computing resources, adapting to unpredictable changes while hiding intrinsic complexity to operators and users. Started by IBM in 2001, this initiative ultimately aims to develop computer systems capable of self-management, to overcome the rapidly growing complexity of computing systems management, and to reduce the barrier that complexity poses to further growth. 〔

The system makes decisions on its own, using high-level policies; it will constantly check and optimize its status and automatically adapt itself to changing conditions. An autonomic computing framework is composed of autonomic components (AC) interacting with each other. An AC can be modeled in terms of two main control loops (local and global) with sensors (for self-monitoring), effectors (for self-adjustment), knowledge and planner/adapter for exploiting policies based on self- and environment awareness.
Driven by such vision, a variety of architectural frameworks based on “self-regulating” autonomic components has been recently proposed. A very similar trend has recently characterized significant research in the area of multi-agent systems. However, most of these approaches are typically conceived with centralized or cluster-based server architectures in mind and mostly address the need of reducing management costs rather than the need of enabling complex software systems or providing innovative services. Some autonomic systems involve mobile agents interacting via loosely coupled communication mechanisms.
''Autonomy-oriented computation'' is a paradigm proposed by Jiming Liu in 2001 that uses artificial systems imitating social animals' collective behaviours to solve difficult computational problems. For example, ant colony optimization could be studied in this paradigm.
== Problem of growing complexity ==
Forecasts suggest that the number of computing devices in use will grow at 38% per year〔(【引用サイトリンク】title=Autonomic Computing:IBM’s Perspective on the State of Information Technology )〕 and the average complexity of each device is increasing.〔 Currently, this volume and complexity is managed by highly skilled humans; but the demand for skilled IT personnel is already outstripping supply, with labour costs exceeding equipment costs by a ratio of up to 18:1.〔‘Trends in technology’, survey, Berkeley University of California, USA, March 2002〕 Computing systems have brought great benefits of speed and automation but there is now an overwhelming economic need to automate their maintenance.
In a 2003 IEEE ''Computer Magazine'' article, Kephart and Chess 〔
warn that the dream of interconnectivity of computing systems and devices could become the “nightmare of pervasive computing” in which architects are unable to anticipate, design and maintain the complexity of interactions. They state the essence of autonomic computing is system self-management, freeing administrators from low-level task management while delivering better system behavior.
A general problem of modern distributed computing systems is that their complexity, and in particular the complexity of their management, is becoming a significant limiting factor in their further development. Large companies and institutions are employing large-scale computer networks for communication and computation. The distributed applications running on these computer networks are diverse and deal with many tasks, ranging from internal control processes to presenting web content to customer support.
Additionally, mobile computing is pervading these networks at an increasing speed: employees need to communicate with their companies while they are not in their office. They do so by using laptops, personal digital assistants, or mobile phones with diverse forms of wireless technologies to access their companies' data.
This creates an enormous complexity in the overall computer network which is hard to control manually by human operators. Manual control is time-consuming, expensive, and error-prone. The manual effort needed to control a growing networked computer-system tends to increase very quickly.
80% of such problems in infrastructure happen at the client specific application and database layer. Most 'autonomic' service providers guarantee only up to the basic plumbing layer (power, hardware, operating system, network and basic database parameters).

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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