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Minuteman: Forward Projection of Unmanned Agents Using the Airborne Internet


In future battlefield operations, autonomous agents such as Unmanned Ground Vehicles (UGVs) and Unmanned Airborne Vehicles (UAVs) will be projected to the forefront for intelligence, strike, search and rescue and other tactical operations. The agents will be organized in clusters in order to carry out such missions; different clusters may execute different missions simultaneously. During the mission, the unmanned agents are supported by sensors on the ground and in the air, and can receive commands and send information back to a command ship, say. It is clear that efficient communications between agents, and from agents to sensors and to command posts are critical to mission success. The goal of the Minuteman project is to develop the concept and initial prototype of an agile, dynamic, multi-layer “Internet in the Sky” architecture that can deliver the “forward power” of the unmanned missions. The architecture consists of a high speed, wireless Mobile Backbone Network (MBN) – with point-to-point wireless links, and local access networks feeding to backbone nodes. The design is extremely challenging because of the hostile environment, the need for QoS support and the unpredictable, nature of the requirements. The focus of this paper is on scalable addressing and routing in such a multiplayer, mobile environment where UAVs can fly at speeds exceeding several hundreds miles per hour. We exploit the fact that agents typically move in groups, and achieve scalability by keeping track of a “landmark” for each group. This is done using LANMAR, a Land-Mark Ad hoc Routing scheme. The LANMAR scheme originally developed for “flat” ad hoc networks extends naturally to a network with a physical backbone. Via simulation we show that LANMAR maintains robust, resilient, rapidly restored connectivity in the face of agent mobility.

Paper: PDF file of paper

Information & Date

IEEE Aerospace Conference 2002, Big Sky, MT, March. 2002


Mario Gerla
Kaixin Xu