Abstract
Artificial satellites, space stations, landers, and rovers are continuously deployed in deep space to explore the planets’ potential resources in the solar system. Data transmission in deep space, therefore, will not be a prescheduled time/bandwidth-specific communication as it exists now. A number of sources in deep space may simultaneously transmit a vast amount of sensitive data to the Earth station (destination) using limited bandwidth and multiple hops. In this article, using a brute force approach, we first show that computing maximum flow through the nodes of a deep-space network is superexponential in nature. We evolve a number of pruning techniques to reduce the search space of the complex augmented deep-space network into trivial cases, where maximum flow (and corresponding routing) may easily be derived. In cases where it is not possible to reduce, a heuristic has been developed to find a good solution for maximizing data flow. Finally, we give a comparative simulation study and analysis between our proposed technique and the standard <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">contact graph routing</i> (CGR) protocol. Our algorithm outperforms CGR by a significant margin when tested in different network topologies and with various traffic generation rates at the sources.
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