Abstract
The foundation for network process evolution research is the modeling of network structure and behavior complexity. With such a model, network systems can be directed toward acquiring good maintainability attributes according to the principles of engineering. In this paper, a Process Management Network (PMN) model is developed to acquire directly from the target process codes the knowledge hidden among and within components of network systems. With the knowledge acquired by the PMN model, network structure and behavior complexity measures in terms of partitioning, restructuring and rewriting criteria are developed; a systematic process re-modularization schema is derived, and algorithms for scheduling network changes are presented. These criteria and mechanisms are used to guide the network evolution.
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