EIPSO: An Energy Efficient Indoor Positioning System based on Game Theory

Location information is attracting more and more attention due to the increasing awareness of its importance for a wide range of applications. Whether it is for tracking valuable assets in the industrial context or monitoring the motion of elderly people and patients to prevent accidents or offering a better shopping experience using proximity and positioning marketing, an accurate and efficient indoor positioning has become crucial. Aware of this increasing need, we present in this paper “EIPSO” a new indoor 3D positioning algorithm based on Game Theory. An emphasis has been put on the energy efficiency of the proposed solution using “mGAPS” a hybrid micro-genetic and pattern search optimization process to reach the Nash equilibrium. A series of real experiments using Zigbee technology have been conducted on a testbed in LaRINa laboratory at the University of Carthage to evaluate the performances of the proposed solution. The obtained results prove the dynamic behavior of EIPSO which adapts the transmit power to both the signal quality and the battery level of the considered nodes. Moreover, a significant improvement of more than 40% of the network lifetime has been observed when using EIPSO while maintaining the positioning accuracy at a high level (≥ 90%).