| Title | Scalability Evaluation of Aspen Tree and Fat Tree Using NS3 |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Nugroho, Yeremia Nikanor, Andika, Ferdi, Sari, Riri Fitri |
| Conference Name | 2019 IEEE Conference on Application, Information and Network Security (AINS) |
| Keywords | Aspen Tree, compositionality, DCN, fat tree, Fault tolerance, pubcrawl, Scalability, security scalability |
| Abstract | When discussing data center networks (DCN), topology has a significant influence on the availability of data to the host. The performance of DCN is relative to the scale of the network. On a particular network scale, it can even cause a connection to the host to be disconnected due to the overhead of routing information. It takes a long time to get connected again so that the data packet that has been sent is lost. The length of time for updating routing information to all parts of the topology so that it can be reconnected or referred to as the time of convergence is the cause. Scalability of a network is proportional to the time of convergence. This article discusses Aspen Tree and Fat Tree, which is about the modification of multi-root trees that have been modified. In Fat Tree, a final set of hosts from a network can be disconnected from a network topology until there is an update of routing information that is disseminated to each switch on the network, due to a link failure. Aspen Tree is a reference topology because it is considered to reduce convergence time and control the overhead of network failure recovery. The DCN topology performance models are implemented using the open source NS-3 platform to support validation of performance evaluations. |
| DOI | 10.1109/AINS47559.2019.8968700 |
| Citation Key | nugroho_scalability_2019 |
Scalability Evaluation of Aspen Tree and Fat Tree Using NS3