Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/20986
Title: Geographic Routing for Point to Point Data Delivery in Wireless Sensor Network
Authors: SHAO TAO
Keywords: geographic routing, sensor network, hop count vector, principal component analysis, 3D networks, tree
Issue Date: 26-Jul-2010
Source: SHAO TAO (2010-07-26). Geographic Routing for Point to Point Data Delivery in Wireless Sensor Network. ScholarBank@NUS Repository.
Abstract: As the design of sensor network applications diversifies, besides flooding and converge-cast, the point-topoint delivery is often required to support more complex communication schemes. Due to the constraints in the current sensor platforms, the traditional ad hoc routing protocols are not scalable. Geographic routing is an attractive option, because its localized packet forwarding procedure obviates the requirement of routing tables. While wireless networks are generally deployed in three-dimensional environments, most geographic routing protocols are designed and evaluated in a two-dimensional space. Existing face routing protocols rely on a graph planarization procedure, which is not applicable to 3D networks. The greedy forwarding methods are vulnerable to local minimum cases, leading to frequent delivery failures in sparse networks. We present a tree-based routing protocol for 3D wireless networks named Spherical Coordinate Routing (SCR), that uses connectivity-based greedy forwarding to obtain efficient routing paths and a spherical coordinate tree to guarantee packet delivery. SCR can deploy multiple recovery trees simultaneously for better routing efficiency and resilience against network dynamics. Hop count vector-based routing protocols can also be integrated with tree-based routing to improve routing efficiency. However, when the entire hop count vector is used to address each node, the communication and storage overhead in the packets is often too high to be employed in a large scale. We apply a dimension reduction technique, Principal Component Analysis (PCA), to reduce the control overhead in data packets. Compared to the original hop count vector, the embedding coordinates generated from the PCA algorithm preserve the network geometry with much lower overhead, making their use more practical on the current sensor platforms. Simulation results show that the coordinates computed by PCA can achieve higher packet delivery ratio, lower hop stretch and shorter flooding range with the same packet overhead.
URI: http://scholarbank.nus.edu.sg/handle/10635/20986
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