Autonomic Computing: A Revolutionary Paradigm for Implementing Self-managing Systems Pradeep Kumar Singh, Arun Sharma, Amit Kumar, Ayush Saxena Department of Computer Science & Engineering Krishna Institute of Engineering & Technology Ghaziabad, India arunsharma@ieee.org , pksingh@kiet.edu Abstract—Recent developments in the field of Information & Communication Technology (ICT) have led to a large scale installation of computing devices connected to each other via different networking technologies. But the scale, complexity, dynamism and heterogeneity of these devices have rendered networks, systems & applications insecure, unmanageable & brittle. Soon the number of these devices will outnumber the humans using them, which makes managing them a cumbersome task. The level of expertise needed to handle these complex systems will also raise. Hence there is a need of alternate system and application design paradigm based on strategies used by biological systems, especially Autonomic Nervous System (ANS). Based on ANS, self-managing computer systems and software tools are being realized. Various subsystems of ANS such as immune system may also motivate growth in developing self- protecting systems. This paper presents a study on autonomic computing along with its architecture, metrics, design issues and some applications. Keywords: Autonomic Nervous System. I. INTRODUCTION The recent developments in computing, communication and information infrastructure have resulted in an explosive growth in computer systems and applications that pervade every aspect of our life. Soon the number of these devices will outnumber the humans using them, which makes managing them a cumbersome task. Therefore scale, complexity, dynamism and heterogeneity of these devices have rendered networks, systems & applications insecure, unmanageable & brittle. The level of expertise needed to handle these complex systems will also raise. Even IBM cited that applications and environments that weigh in tens millions lines of code will require skilled IT professionals to install, configure, tune, and maintain the system [1]. Two solutions to this are either use a large number of intermediate managing devices or use intelligent devices capable of making decisions and managing themselves according to workload. Out of these the former will attribute to increase in complexity but the latter is a fine solution. One such way is to take inspiration from the biological systems. A closer look at the autonomic nervous system (ANS) in humans has revealed that it frees our conscious brain by controlling our heart rate and body temperature. This methodology can be incorporated in distributed systems so that the main controllers (human) need not to worry about the small bugs and problems. System must be capable of sorting out as many problems as possible itself. Thus we require a system which could ease the management of operations autonomously. Autonomic Computing is a big step in this direction. Like ANS, Autonomic Computing also hides the inner complexity providing view of an autonomic, ubiquitous computing environment that provides a level of abstraction and an interface which satisfy user needs. The interaction mechanism between the physical layers of hardware is not known to the user. The system can make decisions spontaneously on its own, using its knowledge base and high level guidance from human user. This system will constantly monitor the environment that affect it and adapt accordingly so as to optimize the performance and also protect as well as recover from problems. Current computing paradigms are based on static requirements, behaviors, interactions and composition. But autonomic computing paradigm can effectively manage dynamic nature of growing ICT infrastructure. When, operating systems came into existence they provided a platform to run application programs thus making user free of inner complexity of memory management, inter-process communication, resource allocation, file management, etc. Autonomic systems will thus make advancement over operating systems. They will create an extra functionality layer over network connected devices each running their own OS. Thus as OS manages and coordinates individual components, Autonomic systems will manage and coordinate distributed, heterogeneous systems. Autonomic computing requires scientific and technological advances in many fields in order to meet its objectives. Thus, new architectures are required to support effective integration of constituent technologies. However journey towards fully autonomic system is quite distant in terms of time and technology. II. AUTONOMIC NERVOUS SYSTEM Autonomic Nervous System (ANS) is the body’s master controller. ANS is subdivided into sympathetic and parasympathetic which counteracts their effects. ANS works without any control from human. Some functions of ANS are regulation of blood circulation, maintenance of blood-glucose concentration, protective reflex on heat contact, sweating to maintain body’s temperature, hormone secretion etc. Using Ashby’s ultra stable system, it can be seen that there may be 2011 International Conference on Recent Trends in Information Systems 7 978-1-4577-0792-6/11/$26.00 ©2011 IEEE