Comparison of Self-Aware and Organic Computing Systems

TL;DR

This paper compares self-awareness and organic computing systems, highlighting their definitions, properties, and architectures to understand their roles in autonomous, adaptive, and complex computing environments.

Contribution

It provides a comprehensive comparison of self-awareness and organic computing, clarifying their similarities, differences, and potential integration for autonomous system design.

Findings

Self-awareness is crucial for adaptive autonomous systems.

Organic computing emphasizes self-* properties for robustness.

The paper clarifies the architectures of both approaches.

Abstract

With increasing complexity and heterogeneity of computing devices, it has become crucial for system to be autonomous, adaptive to dynamic environment, robust, flexible, and having so called self-*properties. These autonomous systems are called organic computing(OC) systems. OC system was proposed as a solution to tackle complex systems. Design time decisions have been shifted to run time in highly complex and interconnected systems as it is very hard to consider all scenarios and their appropriate actions in advance. Consequently, Self-awareness becomes crucial for these adaptive autonomous systems. To cope with evolving environment and changing user needs, system need to have knowledge about itself and its surroundings. Literature review shows that for autonomous and intelligent systems, researchers are concerned about knowledge acquisition, representation and learning which is necessary for a system to adapt. This paper is written to compare self-awareness and organic computing by discussing their definitions, properties and architecture.