Localization for Wireless Sensor and Actor Networks with Meandering Mobility

Environmental monitoring applications for wireless sensor and actor networks rely on position estimation in order to process or evaluate the observed data. The absence of efficient positioning techniques for sensor nodes operating in harsh environments calls for novel approaches. While monitoring the Amazon river, unprecedented characteristics of the river and its surroundings challenge the node communications and drifting of the nodes makes it difficult to use the existing positioning methods. To address these challenges, we propose a multi-hop localization technique that takes advantage of sensor mobility with local information exchange. The collected information is used to enrich the environmental data with location information. The maximum hop distance for actor affiliation is also adapted according to network characteristics to improve energy consumption behavior. The motion of the sensor nodes follows the advection of the fluid parcels in the river, which is modeled as a combination of a central streamline with a meandering motion around the rough surface. This translates into a stretching topology with correlated motion for sensor nodes. Through extensive simulations, we show that the nodes can be efficiently positioned using the proposed approach, as our technique is compliant with the movement patterns of the sensor nodes in the realistic mobility model of the river.