In this paper, the office supplies application process model based on Hierarchical Coloured Petri Nets(HCPN) is built. The CPN Tools is a tool which for modeling, simulation and analysis CPN. This model is build with CPN Tools, the model and its performance is simulated and analyzed. The Extend Resource Petri Nets (ERPN) is presented to build a new optimized model. In the end, a combination method of Genetic Algorithm(GA) and coloured Petri nets is presented to further optimize the model, the optimized results prove this method is feasible and effective.

Knowledge of the physical topology of an IP network is crucial to a number of network management tasks, including reactive and proactive resource management, root-cause analysis, and event correlation. Given the dynamic nature of IP networks, keeping track of network topology information manually is a daunting task. So, effective algorithms for automatically discovering physical topology of an IP network are necessary. Earlier topology discovery has mainly concentrated on discovering logical (i.e., layer-3) network topology, which implies that the connectivity of all layer-2 elements in networks is ignored. In this paper, we pre-sent a novel algorithm for discovering physical (i.e., layer-2) topo-logy in heterogeneous (i.e., multi-vendor) multi-subnet. The algo-rithm presented in this paper relies on standard SNMP MIB info-rmation that is supported by IP network elements and require no modification to the operating system software. The algorithm has been implemented and has been tested on our own research netw-ork. The experimental results can clearly validate our approach, demonstrating that our tool can consistently discover the accurat-e physical topology in time.

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