Five-round Adaptive Diagnosis on Hypercubes

• Main Authors: LIOU,YI-GANG, 劉亦剛
• Other Authors: Y-Chuang Chen
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/st8q2q

碩士 === 明新科技大學 === 資訊管理系碩士班 === 105 === The diagnosis of faulty nodes in large networks or multi-processor systems plays an extremely important role. The technique of using the test results obtained from the node tests to identify the fault processors in the system is referred to as system-level diagnosis. The failure of some nodes in large networks or multi-processor systems could lead to a breakdown of the entire network or system. Thus, diagnosis is exactly a process of discovering the system’s faulty nodes. The effective identification of faulty nodes is critical in reducing the adverse factors of the network architecture and enhancing the stability of information transfer between nodes, which is greatly beneficial to the smoothness of the network system operation. Ye et al. provided a five-round adaptive diagnostic algorithm in IEEE Transactions on Parallel and Distributed Systems in 2015. The algorithm could effectively diagnose the Hamiltonian networks and achieve an almost complete diagnosis. The present study realizes the Ye et al.’s algorithm, where the special case of the original algorithm being able to completely diagnose is further analyzed. An in-depth analysis on the diagnostic capability of the network is also conducted in the 5-D and 6-D hypercubes by increasing the number of faulty nodes.