Currently, it has been a research hotspot in the areas of distributed systems to enable the process of sharing and integration of heterogeneous web applications to realize self-management (autonomic computing), with the guidance of dynamic business requirements and strategies.
Meanwhile, traditional BDI-based agents only concern with their own desires, and can't reflect external motivations, so they are unsuitable for acting autonomic elements of autonomic computing systems.
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.
Autonomy oriented computation is a computational system centering on autonomy. It aims to characterize a complex systems behavior and solve hard computation problems. Web users surfing behavior characteristics are studied based on autonomy oriented computation in this paper, and web users surfing patterns are revealed: power law distribution for surfing depth and link clicking frequency. The reason for the patterns is explored and the influence of user autonomy on surfing patterns is discussed.