An Energy Efficient Dynamic Location Server Hierarchy for Mobile Ad Hoc Networks

By using position information in forwarding decisions, location based routing protocols for mobile networks are stateless and efficient. However, they are heavily dependent on location services which provide the position information of the desired destination node. Although several location service schemes have been proposed, their main goal is just to find the location of the destination node. Seldom they include energy efficiency metrics when evaluating their performance in forwarding location update and query packets. Based on the analysis of the previous related works, we propose a novel location service for mobile networks that aims at decreasing the distance traveled by the location update and query packets and, thus, at reducing the overall energy cost. The solution uses a hierarchy of mobile servers embedded into the network. As a result, the same scheme can be used for mapping logical networks with desired properties, such as hypercubes, onto to mobile ad hoc networks efficiently. A connection of this solution to the efficient query execution in the Gaian database is also discussed. Simulation results for both static and mobile wireless networks are presented to demonstrate that the new scheme achieves energy efficiency while maintaining all the other performance metrics comparable to the previously published algorithms.

Recently, hashing-based protocols have been proposed, in which location servers are determined via a global hash function. These protocols can further be divided into flat or hierarchical, depending on the structure of the area used. In the flat hashing-based protocols [4-5], each node’s identifier is mapped to a home region consisting of one or more nodes within a fixed location in the network area. All nodes in the home region serve as location servers maintaining location information and replying to location queries. However, there are several drawbacks of such approach. First, a large overhead is introduced when moving nodes periodically send location update to their location servers which may be far away. Second, even if the destination node is arbitrarily close to the source node, the source node still needs to send location query to the destination node’s location server that could be far away. Third, when all the location servers are within a fixed geographical area, frequent location queries and replies drain energy and cause early death of the nodes within this area.

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