作者： Helmut Simonis
DOI:
关键词: Inference 、 Mathematical optimization 、 Bounded function 、 Flow (mathematics) 、 Resilience (network) 、 Internet Protocol 、 Constraint (information theory) 、 Matrix (mathematics) 、 Artificial intelligence 、 Constraint programming 、 Computer science
摘要: In this paper we give an overview of applications Constraint Programming for IP (Internet Protocol) data networks, and discuss the problem Resilience Analysis in more detail. try to predict loading a network different failure scenarios, without knowing end-to-end flow values throughout network; inference is based only on observed link traffic values. The related Traffic Flow aims derive matrix from data. This severely under-constrained problem, can show that obtained vary widely different, feasible solutions. Experimental results indicate using same much accurate, bounded be Analysis.