Autonomic Computing Research Issues and Challenges

By reading this paper you can gain the knowledge about Autonomic Computing. I detailed it under the following sub topics.

 1.0 Introduction
 2.0 Why need Autonomic?
 3.0 Major Researches 
           3.1 Research projects in Autonomic computing.
           3.2 University research projects in autonomic computing
4.0 Four basic elements of autonomic computing
           4.1self-configuring
           4.2self-healing
           4.3self-optimizing
           4.4 self-protecting
           AutonomicComputing Vs Current Computing
5.0 Autonomic computing architecture
6.0. Autonomic computing today
           6.1. Initiatives of autonomic computing 
           6.2. Benefits
           6.3. Applications
7.0 What happen if does not have autonomic in the future?
8.0 Autonomic Computing Research Issues and Challenges
9.0 Future direction of Autonomic computing
10.0 Conclusion

8.0 Autonomic Computing Research Issues and Challenges

Meeting the grand challenges of autonomic computing presents fundamental and significant research challenges that span all levels, from the conceptual level to architecture, middleware, and applications. [13] Key research issues and challenges are presented below.

Conceptual Challenges:
Conceptual research issues and challenges include;
-Defining appropriate abstractions and models for specifying, understanding, controlling, and implementing    autonomic behaviors.
-Adapting classical models and theories for machine learning, optimization and control to dynamic and multi agent system
-Providing effective models for negotiation that autonomic elements can use to establish multilateral relationships among themselves
-Designing statistical models of large networked systems that will let autonomic elements or systems detect or predict overall problems from a stream of sensor data from individual devices.

Architecture Challenges:
Autonomic applications and systems will be constructed from autonomic elements that manage their internal behavior and their relationships with other autonomic elements in accordance with policies that humans or other elements have established. As a result, system level self-managing behaviors will arise from the self-managing behaviors of constituent autonomic elements and their interactions. System and software architectures, in which local as well as global autonomic behaviors can be specified, implemented and controlled in a robust and predictable manner remains a key research challenge.

Middleware Challenges:
The primary middleware level research challenge is providing the core services required to realize autonomic behaviors in a robust, reliable and scalable manner, in spite of the dynamism and uncertainty of the system and the application.
These include discovery, messaging, security, privacy, trust, etc. Autonomic systems will require autonomic elements to identify themselves, discover and verify the identities of other entities of interest, dynamically establish relationships with these entities, and to interact in a secure manner. Further the middleware itself should be secure, reliable and robust against new and insidious forms of attack that use self-management based on high-level policies to their own advantage.

Application Challenges:
The key challenges at the application level are the formulation and development of systems and applications that are capable of managing themselves. This includes programming models, frameworks and middleware services that support the definition of autonomic elements, the development of autonomic applications as the dynamic and opportunistic composition of these autonomic elements, and the policy, content and context driven definition, execution and management of these applications.

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