Autonomic computing is a computer’s ability to manage itself automatically through adaptive technologies that further computing capabilities and cut down on the time required by computer professionals to resolve system difficulties and other maintenance such as software updates.
The move toward autonomic computing is driven by a desire for cost reduction and the need to lift the obstacles presented by computer system complexities to allow for more advanced computing technology.
The autonomic computing initiative (ACI), which was developed by IBM, demonstrates and advocates networking computer systems that do not involve a lot of human intervention other than defining input rules. The ACI is derived from the autonomic nervous system of the human body.
IBM has defined the four areas of automatic computing:
- Self-Healing (error correction).
- Self-Optimization (automatic resource control for optimal functioning).
- Self-Protection (identification and protection from attacks in a proactive manner).
Characteristics that every autonomic computing system should have include automation, adaptivity and awareness.
AC was designed to mimic the human body’s nervous system-in that the autonomic nervous system acts and reacts to stimuli independent of the individual’s conscious input-an autonomic computing environment functions with a high level of artificial intelligence while remaining invisible to the users. Just as the human body acts and responds without the individual controlling functions (e.g., internal temperature rises and falls, breathing rate fluctuates, glands secrete hormones in response to stimulus), the autonomic computing environment operates organically in response to the input it collects.
IBM has set forth eight conditions that define an autonomic system:
- The system must know itself in terms of what resources it has access to, what its capabilities and limitations are and how and why it is connected to other systems.
- The system must be able to automatically configure and reconfigure itself depending on the changing computing environment.
- The system must be able to optimize its performance to ensure the most efficient computing process.
- The system must be able to work around encountered problems by either repairing itself or routing functions away from the trouble.
- The system must detect, identify and protect itself against various types of attacks to maintain overall system security and integrity.
- The system must be able to adapt to its environment as it changes, interacting with neighboring systems and establishing communication protocols.
- The system must rely on open standards and cannot exist in a proprietary environment.
- The system must anticipate the demand on its resources while keeping transparent to users.
Autonomic computing is one of the building blocks of pervasive computing, an anticipated future computing model in which tiny – even invisible – computers will be all around us, communicating through increasingly interconnected networks leading to the concept of The Internet of Everything (IoE). Many industry leaders are researching various components of autonomic computing.
The main benefit of autonomic computing is reduced TCO (Total Cost of Ownership). Breakdowns will be less frequent, thereby drastically reducing maintenance costs. Fewer personnel will be required to manage the systems. “The most immediate benefit of autonomic computing will be reduced deployment and maintenance cost, time and increased stability of IT systems through automation,” says Dr Kumar of IBM.
“Higher order benefits will include allowing companies to better manage their business through IT systems that are able to adopt and implement directives based on business policy, and are able to make modifications based on changing environments.”
Another benefit of this technology is that it provides server consolidation to maximize system availability, and minimizes cost and human effort to manage large server farms.
Future of Autonomic Computing
Autonomic computing promises to simplify the management of computing systems. But that capability will provide the basis for much more effective Cloud Computing. Other applications include server load balancing, process allocation, monitoring power supply, automatic updating of software and drivers, pre-failure warning, memory error-correction, automated system backup and recovery, etc.
Read the original text published in Ahmed Banafa’s LinkedIn profile
IoT Expert | Faculty | Author | Speaker