A Hub-Related Mobility Profile and Location Prediction Based Routing for Intermittently Connected Ad Hoc Networks
Date
2015-09-24
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Abstract
Due to the lack of full connectivity between nodes and the time varying nature of node movement, routing is challenging in Intermittently Connected Mobile Ad hoc Networks (ICMAN). In this thesis, we creatively exploit the knowledge of the mobility of nodes by a clustering strategy that we refer to as “Density Based Spatial Clustering of Applications with Noise (DBSCAN)”. The mobility of nodes is predicted with Markov chain, based on which a hub-related mobility profile and location prediction based routing algorithm (HLR) with storage management is proposed. The simulation model of HLR is built with NetLogo and compared with Epidemic routing and Single-Hop Single-copy Routing. The simulation results show that the performance of HLR is superior to the other two routing schemes in terms of achieving a relatively high throughput and low overhead.
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Engineering--Electronics and Electrical
Citation
Hu, X. (2015). A Hub-Related Mobility Profile and Location Prediction Based Routing for Intermittently Connected Ad Hoc Networks (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/24759