A Metropolitan Geo Tracking based Opportunistic Data Dissemination for MANETS

In mobile scenarios, location dependent data can be provided by an infrastructure, or, in case an infrastructure is not available or feasible, by opportunistic networking among mobile devices populating the region of interest. Caused by node mobility, data availability within the region of interest relies on replication and forwarding techniques. Our approach associates data with a geo-address describing the Point of Interest (POI) of the data and proposes a decentralized al-gorithm for data dissemination. Mobile devices replicate data to increase data availability within a circular area around the POI. To avoid unnecessary communication overhead, the distributed algorithm Sector Heads Aided Flooding Technique (SHAFT) restricts the number of mobile nodes that forward data by arranging data placement geometrically in the area. Hereby, each mobile node decides whether to become a forwarding node based on its geo-location and the known scheme for data arrangement. Additionally, the algorithm adapts to the locally measured density of mobile de-vices in range. By applying the approach to a cooperative parking lot management system based on the Manhattan mobility model we demonstrate its usefulness. Simulation results are provided show-ing that SHAFT reaches similar data availability as flooding by re-ducing the number of packets transferred by a factor of up to newly created data and by up to 81:1% for data updates in scenarios of high node density.