LE3 .A278 2022

2022

Shakshuki, Eihadi

Acadia University

Master of Science

Masters

Computer Science

Computer Science

Every data packet has to pass through few intermediate nodes to reach its destination. Among other reasons, tremendous growth in internet devices encourages those intermediate nodes to drop the data packets. Optimizing the data packet route is an effective solution to deal with packet loss. Advanced machine learning approaches have been identified as apowerful support tool for routing optimization in node networks. Furthermore, as hardware infrastructure develops, the capabilities of cloud computing have expanded enormously. Improved connection, processing power, and memory units enable real-time machine learning. This thesis suggests and evaluates a unique technique for optimising the packet path by one hop for intermediate nodes as a backup called Cloud Acknowledgement Scheme. It offers information on the transmission trend and the tendencies of certain adjacent nodes or groups of neighbouring nodes in a network. We carried out a series of machine learning experiments and validated our idea using real-world node data.

The author grants permission to the University Librarian at Acadia University to reproduce, loan or distribute copies of my thesis in microform, paper or electronic formats on a non-profit basis. The author retains the copyright of the thesis.

https://scholar.acadiau.ca/islandora/object/theses:3701