Data from mobile and stationary sensors 1,2 will be vital in planetary surface exploration. The distribution and collection of sensor data in an ad-hoc wireless network presents unique challenges. Some of the conditions encountered in the field include: irregular terrain, mobile nodes, routing loops from clients associating with the wrong access point or repeater, network routing reconfigurations caused by moving repeaters, signal fade, and hardware failures. These conditions present the following problems: data errors, out of sequence packets, duplicate packets, and drop out periods (when the node is not connected). To mitigate the effects of these impairments, robust and reliable software architecture tolerant of communications outages must be implemented. This paper describes such a robust and reliable software infrastructure that meets the challenges of a distributed ad hoc network in a difficult environment and presents the results of actual field experiments testing the principles and exploring the underlying technology.
The Mobile Exploration System Project (MEX) at NASA Ames Research Center has been conducting studies into hybrid communication networks for future planetary missions. These networks consist of space-based communication assets connected to ground-based Internets and planetary surface-based mobile wireless networks. These hybrid mobile networks have been deployed in rugged field locations in the American desert and the Canadian arctic for support of science and simulation achvihes on at least six occasions. This work has been conducted over the past five years resulting in evolving architectural complexity, improved component characteristics and better analysis and test methods. A rich set of data and techniques have resulted from the development and field testing of the communication network during field expeditions such as the Haughton Mars Project and NASA Mobile Agents Project.
Wireless mobile networks 12 suffer connectivity loss when used in a terrain that has hills and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc networks at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways:Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge.
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