Research Article
Rate of Network Convergence Determination Using Deterministic Adaptive Rendering Technique
@INPROCEEDINGS{10.1007/978-3-030-70572-5_9, author={Ayotuyi T. Akinola and Matthew O. Adigun and Pragasen Mudali}, title={Rate of Network Convergence Determination Using Deterministic Adaptive Rendering Technique}, proceedings={Towards new e-Infrastructure and e-Services for Developing Countries. 12th EAI International Conference, AFRICOMM 2020, Eb\'{e}ne City, Mauritius, December 2-4, 2020, Proceedings}, proceedings_a={AFRICOMM}, year={2021}, month={7}, keywords={SDN Protocol Multi-criteria ART SDN DART_MCP}, doi={10.1007/978-3-030-70572-5_9} }- Ayotuyi T. Akinola
Matthew O. Adigun
Pragasen Mudali
Year: 2021
Rate of Network Convergence Determination Using Deterministic Adaptive Rendering Technique
AFRICOMM
Springer
DOI: 10.1007/978-3-030-70572-5_9
Abstract
Software-Defined Networking (SDN) has become a popular paradigm for modern day optimal performance of the network system as a result of the separation of the control component from other network elements. This enables the maintenance of the flow table structure on these devices while optimal forwarding of packets is enhanced via the central controller. Being a growing network architecture which is supposed to be able to meet up with increasing traffic demands in the future, it becomes apparently important that the mechanism that takes care of the QoS of the network demands is put in place. Such demands include the smooth running of big data transmission, D2D video exchange, Voice over IP and real-time multimedia applications which needed certain QoS requirements for optimal service delivery. However, fewer research articles have reported on the improvement on the QoS routing especially in connection with the SDN paradigm. We propose a multi-criteria routing algorithm that is based on deterministic Adaptive rendering technique called DARTMCP. Our DARTMCP QoS routing algorithm deployed Dijkstra’s algorithm to simplify the topology of the network before using multiple-criteria energy function to address the QoS requirements. We recorded a relatively stable bandwidth and user experience maximization under a low rate of network convergence in comparison with other approaches.