University of Ottawa - Carleton University
Ottawa-Carleton Institute for Computer Science (OCICS) Presentation
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November 30, 2012 @ 10:00a.m.
Data Collection using Random Walks in Wireless Sensor Networks
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Speaker: Rui Wang
Location: LMX 360 (Lamoureux) |
ABSTRACT
Wireless Sensor Networks are visioned as large ad-hoc collections of very small autonomous devices that can sense environmental conditions in their immediate surrounding while having limited processing and communication capabilities and energy reserves. Data collection in wireless sensor networks is usually achieved by a mobile central sensor node (called data sink). The sink has significant and easily replenishable energy reserves and can move inside the region to receive information sent from sensors.
Data collection using random walks can serve as local, very simple strategies for sink motion that significantly reduce energy dissipation and also probabilistically guarantee that eventually the entire network area will be covered. In this project, we choose to model wireless sensor network via grid graphs. We surveyed random networks algorithms such as Blind Random Walk, Random Walk with Memory, Biased Random Walk, Random walk with Inertia, Explore-and-Go Random Walk, Curly Random Walk, -stretched Random Walk. Through simulations using Python, we investigate the efficiency of different Random Walk Strategies in wireless sensor networks with different network structures.
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