International Journal of Computer Applications (0975 – 8887) Volume 94 – No 4, May 2014 A Review of the Autonomic Computing Models and Applications

Leandro Zambrano Alejandro Rosete Suárez Humberto Díaz Pando Méndez Facultad Ingeniería Facultad Ingeniería Facultad Ingeniería Informática. ISPJAE, Cuba Informática. ISPJAE, Cuba Informática. ISPJAE, Cuba

ABSTRACT alternative paradigm for the system and application design, Todaymore and morebusiness processesof companiesrely on which is based on strategies used by biological systems to theirinfrastructureICT (Information Technology and deal with challenges similar scale, complexity, heterogeneity Communications).Along with thisbusiness evolution andthe and uncertainty, a view that has been referred to as autonomic broader economicenvironment, these computing computing [2]. infrastructureshave grown exponentiallyinthe The autonomic computing paradigm[1] has been inspired by storagecapacityandeaseand accessibilityfromanywhere in the the autonomy of the human nervous system.Its main objective worldusing multiple devices. However, thisdevelopment has is to detect computer systems and applications that can be notbeen accomplished bysimilar advancesin the operationof handled themselves in accordance with high level guidance these infrastructures, on the contrary way; infrastructures have from humans.The fulfillment of the great challenges of becomeincreasingly complexto manage.The complexitythat autonomic computing requires scientific and technological has achieved the systems and communicationsinfrastructureof advances in a wide variety of fields, as well as a new anycompany makestheir management isvery complicated programming paradigm, and that the software and systems andresource intensive, which ultimately impactingnegatively architectures give a support effective integration of the the bottom lineof the companyand thereforeits abilityto constituent technologies [2]. develop the expected business. This paper presents a brief introduction to autonomic Autonomic Computingis a conceptthat brings togethermany computing and current state of the art is presented. First fieldsof computer science,in order tocreatecomputing overviews of the architecture of the nervous system are systemsthat are selfmanaged. In this study, a preview of the displayed and how it is used to motivate the paradigm of state of the art on this topic shows.To this end, offers first an autonomic computing.The following summarizes the main introduction to the motivation and concepts of autonomic challenges of autonomic computing and an overview is computing.This study raises somebenefits and features ofthis presentedautonomic computing systems and existing proposal, as well as some properties oftheself. In addition applications. present some of the main applications of autonomic computing. 2. CONCEPTUAL ISSUES 2.1 The human nervous system General Terms The human nervous system is probably the most complex Autonomic Computing. system known and organized. Autonomy is an example of behavior or existing in nature. He is the captain of the body, Keywords the controller monitors changes inside and outside the Autonomic Computing, Self Management. organism, integrates sensory stimuli and the effects of the 1. INTRODUCTION appropriate response. In conjunction with the endocrine system, the nervous system is able to regulate and maintain it As with the birth of the Internet, one of the most notable constantly as a principle of regulation [2]. projects by self-management was initiated DARPA for military use in 1997 [1]. 2.2 The autonomic computing paradigm Advances in network technology and computingplus software An autonomic computing paradigm, following the model of tools have enabled an explosive growth in network the autonomic nervous system, must have a mechanism by applications and information services and covers done which changes in essential variables can trigger changes in the allaspects of our lives. Such applications and services are very behavior of the computer system so that the system is restored complex, heterogeneous and dynamics.Moreover, the back into balance with regard to the environment.This state of underlying information infrastructureglobally adds a lot of stable equilibrium is a necessary condition for the survival of independent computing. Communication resources, data the organism.For a system of autonomic computing, you stores, are themselves equally large s,heterogeneous, dynamic cannot think of survival as the system's ability to protect, and complex.The combination has resulted in the recover from failures, reconfigured as required by changes in implementation, development, configuration and the environment, and always keep your s functions almost administration of complexities breaking paradigms, behaviors, optimum performance.Your balance is affected by both and interactions and compositions. Consequently, applications, the internal environment (for example, memory usage / programming environments and infrastructures have excessive CPU) as the external environment (for example, information have become rapidly in fragile aspects is difficult protection against external attack) [2]. to handle and is unsure.This has led to the investigation of an

14 International Journal of Computer Applications (0975 – 8887) Volume 94 – No 4, May 2014

An autonomic computing system requires: consuming and seamlessly. more error prone. -Channels sensor to detect the change in the internal and external environment. - Channels engine to react and counter the effects of changes in the environment to maintain balance. Self- Systems have Components and optimization hundreds of systems continually 2.3 Self-Management manually set, seek opportunities The essence of autonomic computing systems is self- nonlinear tuning to improve their management, purpose is the free system administrators, from parameters and their own performance the details ofas system operations, maintenance, and to number increases and efficiency. provide users with anoperating at maximum infrastructure l of with each release. the 24-hour yield by 7 days of the week. Self-healing Problem System determination in automatically Like their biological counterparts, the autonomic systems or large, complex detects, diagnoses, sAngels maintain and adjust their operation to the evolution of systems can take a and repairs the component is, workloads, demands and to external team of localized software hardware or software failures whether accidental conditionsor programmer’s and hardware malicious. weeks. problems. An autonomous system can continuously monitortheir own Self- The detection and The system use, and check the actualizations component, for example. If protection recovery from automatically you think that improvements are worth it, the system will be attacks and defends attacks or installed, reconfiguring as needed, and run a regression test s cascading failures is cascading failures. to make sure all is well.When it detects errors or performed and Use early warning modifications, the system returns to the previous version, resolved manually. to anticipate and while it’s automatic algorithms for determining problems prevent system trying to isolate the source of the error [3]. Frequently cited failures. IBM four aspects of the self, which in table 1 are summarized. 2.4 Architecture of an autonomous element An autonomous element (see Figure 1) is the smallest of an Table 1. Four aspects of self-management as they are now application or system autonomic. This is a system of and would be with autonomic computing [3]. independent software modules or input / output specified interfaces and explicit context dependencies. Mechanisms for Concept Current Autonomic self-management, which are responsible for the execution of Computing Computing its functions, export limitations, management of behavior, Self- Corporate data Automated according to the context and policies, and interaction with configuration centers have configuration of other elements are also incorporated. T