Optimizing Opportunistic Routing between Communities Using Decision Trees and Apriori Algorithm


  • Jingyun You




Decision tree, Apriori, Probability of meeting, Opportunistic routing


This study proposes a novel data transmission framework aimed at optimizing node data transmission between different communities. We have designed an intelligent routing strategy based on node characteristics for situations where the source node and destination node have different communities. Through the decision tree algorithm, we trained a model to identify "messenger nodes" that are specifically responsible for cross community data transmission. In addition, the association rule model constructed using the apriori algorithm can calculate the probability of establishing a connection between the "messenger node" and the destination community node, thereby selecting the optimal path for data transmission. This method effectively reduces transmission delay and improves the efficiency and reliability of data transmission.


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How to Cite

You, J. (2024). Optimizing Opportunistic Routing between Communities Using Decision Trees and Apriori Algorithm. International Journal of Computer Science and Information Technology, 3(1), 106-116. https://doi.org/10.62051/ijcsit.v3n1.14

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