What are characteristics of autonomic system?

Autonomic systems bring both challenges as well as opportunities for the future networking. The increasing numbers of users have had a negative impact on the complexity of the networks; it has also increased by multiple folds. Autonomic systems provide a solution for this problem. 

Characteristics of Autonomic System

1. High intelligence: These systems have more intelligence incorporated in to them which lets them tackle this increasing complexity easily.
2. Business Goal: They are driven by the business goal that the quality of experience of the user must be high. Even with the changing environment, there goals remain the same. But there are changes that take place in the low – level configurations. For example, when a user switches over to a low bandwidth network, the bit rate of the video has to be reduced in order to satisfy the goals of the business.
3. Complex operations: All the operations carried out in an autonomic system are complex in nature even for the simplest of the services. For example, authentication, video encoding, billing, routing, shaping, QoS prioritizing, admission control.
4. High level objectives: The human operator just has to specify the high – level objectives and it is left to the system whether it chooses to optimize one or more of the goals. In order to achieve this, the system has to translate these objectives in to low – level configurations.
5. Adaptability: The system has the ability to adapt itself to the current environment.
6. Policy continuum: There are a number of perspectives to this as mentioned below:

Ø  Business view: Includes guidelines, processes and goals.

Ø  System view: The service should be independent of the technology as well as the device that is being used.

Ø  Network view: It should be specific to technology but independent of the device.

Ø  Device view: Both technology and device specific.

Ø  Instance view: Operation should be specific to an instance.

7. Elements: The elements of the network are assumed to be heterogeneous by the autonomic communication systems whereas in plain autonomic computing the elements are taken to be as the homogeneous.
8. Distributed: These systems work up on a distributed environment.
9. Complexity: The complexity in autonomic systems is more because of the complex autonomic loop that includes the following operations:

Ø  Interaction between the context  and the business goals

Ø  The MAPE (monitor, analyze, plan and execute) loop.

10. Reliability: In autonomic systems, the network has the authority to decide for itself focusing on high level objectives. Autonomic systems rely heavily up on artificial intelligence. However, there are issues associated with artificial intelligence like it becomes difficult to intervene in between when the things go wrong.It is quite difficult to know whether the system is doing the things it is supposed to do or not.

11. Scalability: This is another major characteristic of autonomic systems. It is required to keep track of the large amounts of knowledge and information. Autonomic systems have three tools to take care of this:

Ø Distributed ontologies

Ø Distributed large – scale reasoning

Ø Exchanging only the useful information

ØDistributing information among the different components of the autonomic network.

But in these cases, detection of the conflicts is a difficult task. For handling the various interactions taking place the various autonomic components efficient protocols are required. 

Currently two approaches have been suggested for developing the autonomic networking systems namely:

1. Evolutionary Approach: Incorporating the autonomic behavior in to the pre – existing infrastructure. This approach will consist of updates in increments till a fully autonomic system is developed. This approach is more likely to be adopted even though it requires a lot of patchwork.

2.  Clean slate approach: This approach is focused up on re – designing of the internet.