Position-based routing is often proposed as a means to achieve scalability in large mobile ad hoc networks. However, such routing protocols are heavily dependent on the existence of scalable location management services. In recent years, many location service protocols have been proposed for ad hoc networks such as the Grid Location Service (GLS), and the Hierarchical Location Service (HLS). In these location services, when a mobile node's location is needed, the previously stored information in the location server is used. Location errors can occur due to infrequent and/or lost updates to location servers, especially when the nodes are highly mobile. A query to a location server fails when a node moves far away from its previous location rendering the previously stored location in the location servers invalid. In this paper we propose a location service called Predictive-Hierarchical Location Service (PHLS) that uses a hierarchy of regions to achieve scalability, and predicts the requested location by utilizing previous location information (location, velocity) to improve the location accuracy. Our simulation results have shown that PHLS outperforms HLS.
Geographic routing protocols have imposed significant challenges for Mobile Ad hoc NETworks (MANETs) to achieve scalability. These routing protocols use location information of mobile nodes in forwarding decisions. However, geographic routing protocols require location management services that handle the location updates sent by nodes and resolve their queries. Most of the location services found in MANET literature resolve the queries as the last stored location which usually makes degradation in the accuracy of the location information due to mobility. In this paper we propose a scalable and energy efficient location service which employs hierarchical geographic clustering structure and considers energy when selecting cluster leaders. Furthermore, our location service is mobility adaptive as it is assisted by mobility prediction model using the well known Kalman Filter. In the proposed protocol, the location servers estimate the locations of the mobile nodes by using the last location information instead of resolving the queries by the last known locations. Through computer simulation, we evaluate the performance of our proposal. Results show an improved performance of our proposal.
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