What are principles of autonomic networking?

The complexity, dynamism, heterogeneity and so on are on ever rise. All these factors are making the infrastructure of our network insecure, brittle and un – manageable. Today’s world is so dependent on networking that its security and management cannot be risked. In terms of networking, we call this the ‘autonomic networking’. 

The goal of building such systems is to realize such network systems that have capability of managing themselves as per the high level guidance provided by the humans. But meeting this goal calls for a number of scientific advances and newer technologies.

Principles of Autonomic Networking

A number of principles, paradigms and application designs need to be considered.

Compartmentalization: This is a structure having extensive flexibility. The makers of autonomic systems prefer this instead of a layering approach. This is the first target of the autonomic networking.

Function re–composition: An architectural design has been envisioned that would provide highly dynamic, autonomic and flexible formation of the networks on a large – scale. In such architecture, the functionality would be composed in a fashion that is autonomic.

Atomization: The functionality are broken down in to smaller atomic units. Maximum re - composition freedom is made possible by these atomic units.

Closed control loop: This is one of the fundamental concepts of the control theory. It is now also counted among the fundamental principles of the autonomic networking. This loop is known for controlling and maintaining the properties of the controlled system as per the desired bounds. The target parameters are constantly monitored within the desired bounds.

The human autonomic nervous system is what that inspires the autonomic computing paradigm. An autonomic computing paradigm must then have a mechanism by virtue of which it can change its behavior according to the change in various essential variables in the environment and bring it back itself in to the state of equilibrium. 

Survivability can be viewed in the terms of following in case of autonomic networking:

1. Ability to protect itself
2. Ability to recover from the faults
3. Ability to reconfigure itself as per the environment changes.
4. Ability to carry out its operation at an optimal limit.

The following two factors affect the equilibrium state of an autonomic network:

1. The internal environment: This includes factors such as CPU utilization, excessive memory and so on.
2. The external environment: This includes factors such as safety against external attacks etc.

There are 2 major requirements of an autonomic system:

1. Sensor channels: These sensors are required for sensing the changes.
2. Motor channels: These channels would help the system in reacting and overcoming the effects of the changes.

The changes that are sensed by the sensor are analyzed for determining the viability limits of the variables. If the variables are detected out of this limit, then the system plans what changes it should introduce in to the system to bring them in their limit, thus bringing back the system in to its equilibrium state.