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:
- 2 main control loops namely the global and the
local.
- Sensors (required self – monitoring)
- Effectors (required for self-adjustment)
- Knowledge
- 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:
- Consumes more time
- Expensive
- 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:
- Self–configuration: Responsible for the automatic configuration of the
network components.
- Self–healing: Responsible for the automatic detection and correction of the
errors.
- Self–optimization: Monitors and controls the resources automatically.
- Self–protection: Identifies the attacks and provides protection against them.
- Below mentioned are some
characteristics of the autonomic systems:
- Automatic
- Adaptive
- aware
