Abstract
A common approach to scale up a network is by connecting several small-scale networks to form a larger network. A multigraph composition network is a typical network structure obtained by adding an edge set between several connected graphs in the same order. This paper investigates the diagnosability on two categories of multigraph composition networks, that is, multigraph alternating composition networks and multigraph 2-matching composition networks, under the PMC and MM⁎ models. As corollaries, the diagnosability of several known networks, such as alternating group graphs, k-ary n-cubes, and round matching composition networks, can be derived directly.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
