1-3hit |
Malik Jahan KHAN Mian Muhammad AWAIS Shafay SHAMAIL
Inspired from natural self-managing behavior of the human body, autonomic systems promise to inject self-managing behavior in software systems. Such behavior enables self-configuration, self-healing, self-optimization and self-protection capabilities in software systems. Self-configuration is required in systems where efficiency is the key issue, such as real time execution environments. To solve self-configuration problems in autonomic systems, the use of various problem-solving techniques has been reported in the literature including case-based reasoning. The case-based reasoning approach exploits past experience that can be helpful in achieving autonomic capabilities. The learning process improves as more experience is added in the case-base in the form of cases. This results in a larger case-base. A larger case-base reduces the efficiency in terms of computational cost. To overcome this efficiency problem, this paper suggests to cluster the case-base, subsequent to find the solution of the reported problem. This approach reduces the search complexity by confining a new case to a relevant cluster in the case-base. Clustering the case-base is a one-time process and does not need to be repeated regularly. The proposed approach presented in this paper has been outlined in the form of a new clustered CBR framework. The proposed framework has been evaluated on a simulation of Autonomic Forest Fire Application (AFFA). This paper presents an outline of the simulated AFFA and results on three different clustering algorithms for clustering the case-base in the proposed framework. The comparison of performance of the conventional CBR approach and clustered CBR approach has been presented in terms of their Accuracy, Recall and Precision (ARP) and computational efficiency.
Daekeun MOON Jinho PARK Hagbae KIM
In large-scale industrial plants, the process control system has multiple system servers to provide seamless services to plant operators irrespective of any system server's failure. In this paper, we present an autonomic connection scheme between the system server and the Human-Machine Interface application (HMI) without additional configuration. The proposed scheme is based on the concept of autonomic computing, supporting the fault-tolerant and/or load-balancing features. Finally, the mathematical analysis shows that the proposed scheme can provide high availability of services to users.
Since the characteristic to current information systems is the dynamic and concurrent change of their configurations and scales with non-stop provision of their services, the system management should inevitably rely on autonomic computing. Since fault tolerance is the one of important system management issues, it should also be incorporated in autonomic computing environment. This paper argues what should be taken into consideration and what approach could be available to realize the fault tolerance in such environments.