What are autonomic systems? What is the basic concept behind autonomic system?

In this article we shall discuss about the autonomic systems, but before moving on to that we shall see a brief discussion regarding the autonomic computing. 

About Autonomic Computing

- Distributed computing resources have the ability of self–management. 

- This kind of computing is called autonomic computing and such systems are called autonomic systems. 

- Because of their unique capabilities, these systems are able to adapt to the changes that are both predictable and unpredictable. 

- At the same time, these systems keep the intrinsic complexities hidden from the users as well as the operators. 

- The concept of autonomic computing was initiated by IBM in the year of 2001. - This was started in order to keep a curb on the growing complexity of the management of the computer systems and also to remove any complexity barriers that prove to be a hindrance in development.

About Autonomic Systems

- Autonomic systems have the power to make decisions of their own. 

- They do this because of the high level policies. 

- These systems automatically check and optimize their status and adapt to the conditions that have changed. 

- The frame work of these computing systems is constituted of various autonomic components that are continuously interacting with each other. 

- Following are used to model an autonomic component:

1. 2 main control loops namely the global and the local.
2. Sensors (required self – monitoring)
3. Effectors (required for self-adjustment)
4. Knowledge
5. Adapter or planner

- The number of computing devices is increasing by a great margin every year. - Not only this, each device’s complexity is also increasing. 

- At present highly skilled humans are responsible for managing such huge volume of complexity. 

- The problem here is that the number of such skilled personnel is not much and this has led to a rise in the labor costs.

- It is true that the speed and automation of the computing systems have revolutionized the way world runs but now there is a need for a system that is capable of maintaining these systems without any human intervention. 

- Complexity is a major problem of the today’s distributed computing systems particularly concerning their management. 

- Large scale computer networks are employed by the organizations and institutions for their computation and communication purposes. 

- These systems run diverse distributed applications that are capable of dealing with a number of tasks. 

- These networks are being pervaded by the growing mobile computing. 

- This means that the employees have to be contact with their organizations outside office through devices such as PDAs, mobile phones and laptops that connect through wireless technologies. 

- All these things add to the complexity of the overall network that cannot be managed by human operators alone. 

- There are 3 main disadvantages of manual operating:

1. Consumes more time
2. Expensive
3. Prone to errors

- Autonomic systems are a solution to such problems since they are self – adjustable and do not require human intervention. 

- The inspiration or the concept behind the autonomic systems is the autonomic nervous system found in humans.

- This self – manageable system controls all the bodily functions unconsciously. - In autonomic systems, the human operator just has to specify the high level goals and rules and policies that would guide the management. 

- There are 4 functional areas of an autonomic system:

1. Self–configuration: Responsible for the automatic configuration of the network components.
2. Self–healing: Responsible for the automatic detection and correction of the errors.
3. Self–optimization: Monitors and controls the resources automatically.
4. Self–protection: Identifies the attacks and provides protection against them.

- Below mentioned are some characteristics of the autonomic systems:

1. Automatic
2. Adaptive
3. aware