An Autonomic computing system is a solution to circumvent the overhead associated with the usual network setup, manual updates, and continual general maintenance. In this research an in-depth analysis of the benefits of a novel Autonomic University Administration System (AUAS) is presented. An Autonomic Manager (AM) is responsible for the autonomic activities of self-configuration, self-healing and diagnosis, and optimization. A Policy Guided Self-Configuration Module (PGSCM) handles any new software or hardware to the proposed autonomic network (AN). The Self-Healing & Diagnosis Module (SHDM) handles much of the testing of the AUAS for the AM. The Optimization Module (OM) handles self-optimization activities of the AUAS for the AM. A theoretical analysis is provided for cost, quality of service, failure avoidance, adaptivity, and response time.
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