Autonomic system (computing)

Autonomic system (computing)

:"See also autonomic nervous system".

An autonomic system is a system that operates and serves its purpose bymanaging its own self without external intervention even in case of environmentalchanges.

Conceptual model

A conceptual model of an autonomic system is shown here:

A fundamental building block of an autonomic system is the sensing capability ("Sensors Si"), which enables the system to observe its externaloperational context. Inherent to an autonomic system is the knowledge of the"Purpose" (intension) and the "Know-how" to operate itself (e.g., boot-strapping,configuration knowledge, interpretation of sensory data, etc.) without externalintervention. The actual operation of the autonomic system is dictated by the"Logic", which is responsible for making the right decisions to serve its "Purpose",and influence by the observation of the operational context (based onthe sensor input).

This definition/model highlights the fact that the operation of an autonomic system is purpose-driven. This includes its mission (e.g., the service it is supposed to offer), the policies (e.g., that define the basic behaviour), and the “survival instinct”. If seen as a control system this would be encoded as a feedback error function or in a heuristically assisted system as an algorithm combined with set of heuristics bounding its operational space.

Characteristics

Even though the purpose and thus the behaviour of autonomic systems vary from system to system, every autonomic system should be able to exhibit a minimum set of properties to achieve its purpose:

1. Automatic

This essentially means being able to self-control its internal functions and operations. As such, an autonomic system must be self-contained and able to start-up and operate without any manual intervention or external help. Again, the knowledge required to bootstrap the system ("Know-how") must be inherent to the system.

2. Adaptive

An autonomic system must be able to change its operation (i.e., its configuration, state and functions). This will allow the system to cope with temporal & spatial changes in its operational context either long term (environ-ment customisation/optimisation) or short term (exceptional conditions such as malicious attacks, faults, etc.).

3. Aware

An autonomic system must be able to monitor (sense) its operational context as well as its internal state in order to be able to assess if its current operation serves its purpose. Awareness will control adaptation of its operational behaviour in response to context or state changes.

Relation to other definitions

The above definition is still inline with IBM’s basic vision of Autonomic Computing. However, in contrast to the herein proposed definition, which defines the properties that characterise an autonomic system, IBM’s four “autonomic self-properties”, namely self-healing, self-configuration, self-optimisation and self-protection, define a set of functionalities or features that an autonomic system must provide. For example, according to our definition a system that can operate on its own while serving its purpose is autonomic, irrespective of whether it implements those functionalities.

However, it should be the nature and purpose of an autonomic system that defines which functions are required! As a result, it can be argued that the above definition is more precise (in describing a system) and at the same time more general.

The above model is also consistent with the definition of a control system as well that of an AI agent. This is reasonable since practically a control system or an AI agent may easily implement an autonomic system, if it exhibits the aforementioned properties.

Autonomicity and evolability

A short remark regarding the relation of autonomicity and evolvability: It has been often argued in discussions that an autonomic system ought to be evolvable (for example, through some type of artificial learning methods). However, similarly to the above discussion regarding IBM’s autonomic computing features, it can be argued that learning and evolvability may be a useful feature in an autonomic system, but whether it is required or not depends on the actual purpose of the autonomic system, and should thus not be considered an essential property of an autonomic system.

See also

* Autonomic Computing
* Autonomic Networking
* Perceptual Control Theory

External links

* [http://www.ibm.com/autonomic IBM Autonomic Computing website]
* [http://www.ana-project.org/ ANA Project: Autonomic Network Architecture Research Project] , funded by the European Commission
* [http://dssg.cs.umb.edu/wiki/index.php/BiSNET/e BiSNET/e: A Cognitive Sensor Networking Architecture with Evolutionary Multiobjective Optimization]


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