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autonomic computing
The goal of autonomic computing is to reduce the configuration, operational, and maintenance costs of distributed applications by enabling them to self-manage, self-heal, and self-optimize.
      
This paper provides two contributions to the Model-Driven Engineering (MDE) of autonomic computing systems using Enterprise Java Beans (EJBs).
      
Autonomic computing (AC) has as its vision the creation of self-managing systems to address today's concerns of complexity and total cost of ownership while meeting tomorrow's needs for pervasive and ubiquitous computation and communication.
      
Seven software engineering principles for autonomic computing development
      
Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators.
      
GRAPHIC illustrations of autonomic computing concepts
      
The purpose of this paper is to clarify the requirements for standard exemplars, propose an autonomic computing exemplar for consideration, and assess it against the criteria identified.
      
Autonomic Computing, self-management based on high level guidance from humans, is increasingly being accepted as a means forward in designing reliable systems that both hide complexity from the user and control IT management costs.
      
An important goal of autonomic computing is the development of computing systems that are capable of self healing with a minimum of human intervention.
      
Autonomic Computing for Pervasive ICT - A Whole-System Perspective
      
Our goal is to retrofit autonomic computing onto such systems, externally, without any need to understand, modify or even recompile the target system's code.
      
On-line self-checking of replication consistency for autonomic computing
      
Furthermore, we relate our architecture to a general autonomic computing architecture based on self-managing resources and patterns of inter-resource collaboration, and to emerging standards in the area of distributed manageability.
      
Although autonomic computing reduces traditional operational cost, it introduces another cost factor related to operation knowledge.
      
Much recent research has focused on applying Autonomic Computing principles to achieve constrained self-management in adaptive systems, through self-monitoring and analysis, strategy planning, and self adjustment.
      
Autonomic computing and communication has become a new paradigm for dynamic service integration and resource sharing in today's ambient networks.
      
Autonomic computing focuses on the specification and construction of components that interoperate well for management tasks.
      
Autonomic computing research aims to reduce the costs of managing deployed systems.
      
Autonomic computing is emerging as a significant new strategic and holistic approach to the design of complex distributed computer systems.
      
Autonomic Computing is then introduced in terms of its biological metaphor.
      
 

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