Connectivity and diagnosability of a class of recursive networks

With the expansion of network scale, it is essential to study network reliability through connectivity and diagnosability. For Hypercube, DCell, BCube, and other networks, their connection modes are specific and different, so it is necessary to use different methods to study the properties of networks. This paper proposes a class of topological structure—cycle composition networks (CCNs), which not only contains k -ary n -cube and BC graph, but also includes the data center network CamCube and many other unknown networks. We then study their diameters and path construction algorithm in them. Furthermore, we establish their classical connectivity and diagnosability under the PMC and the MM ^* models, respectively. Finally, we give the 1-good-neighbor connectivity and diagnosability of the CCNs under the PMC model for n ⩾ 3 and l = 2 .