Tuning Adaptive Computations for Performance Improvement of Autonomic Middleware in PaaS Cloud

In a cloud platform belonging to the PaaS (Platform as a Service) category, autonomic middleware have become the fundamental part of a cloud node. An autonomic middleware can perform adaptive computations for self-management of the system. However, these adaptive computations consume resources such as CPU and memory, and can interfere with each other and also with normal business functions of the system due to resource competition, especially when the system is under heavy load. As a result, the adaptive computations should be tuned from the perspective of resource management. In this position paper, we propose an approach to tuning the autonomic levels and thus controlling the resource costs of the adaptive computations in an autonomic middleware of PaaS cloud, so as to guarantee the system´s performance when resources are competed.