Communicating data in deep-space, across interplanetary distances, entails constraints such as signal propagation delays in the order of minutes and hours, high channel error characteristics, meager and asymmetric bandwidth availability, and disruptions due to planetary orbital dynamics and antenna scheduling constraints on Earth. The Licklider Transmission Protocol (LTP) is being designed as a reliable data transmission protocol optimized for this environment. We present a dynamic priority paradigm for LTP jobs that may help improve the volume and value of data communicated in deep-space by quantifying each job's Intrinsic Value and Immediacy. We study Convolutional codes, Reed-Solomon codes, Raptor codes, and some of their combinations, over various channel error rates. We show how the appropriate application of these mechanisms to each job, based on its Immediacy and Intrinsic Value, can improve the aggregate value of data transferred over the channel across various job mixes.
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