Applications monitoring for self-optimization in GridGain

Monitoring process offer a quantitative and qualitative measurement of performance by collecting information relevant to environment and applications. Monitoring allows the obtaining of valuable parameters about performance, resource usage and availability, the efficiency of scheduling and used algorithms and represents a mechanism for analyzing and adapting an application's behavior, particularly useful for optimization of complex applications. Self-* properties of different applications are the answer to the complexity and large scale of distributed systems. The purpose of this paper is to analyze the requirements and to build such a tool destined for computational grids using the Grid Gain middleware platform (an Enterprise middleware for Grids, dedicated both to researcher environments and to industry). The optimization process is very important for QoS assurance, so multi-criteria approach could be adopted. The self-* behavior consider bio-inspired techniques for optimization (genetic algorithms, immune algorithms, swarm intelligence).