Delay is a fundamental problem of data communication and networks, a problem that is not usually addressed in classical coding, information or networking theory. We focus on the general problem of delay challenged networks. This delay challenge may be related to different reasons, for example, 1) large latency, which can affect the performance of the system in delay, throughput or energy efficiency, 2) half-duplex constraints on the nodes, which precludes a node to receive and transmit at the same time, and/or 3) application-level requirements for reliable, fast and efficient dissemination of information. We consider three main problems of study and the role of network coding on solving these problems. The first is related to the problem of reliable communication in time-division duplexing channels, also known as half-duplex channels, in the presence of large latency. In large latency channels, feedback about received packets may lag considerably the transmission of the original packets, limiting the feedback's usefulness. Moreover, the time duplex constraints may entail that receiving feedback may be costly. In this work, we consider tailoring feedback and (network) coding jointly in such settings to reduce the mean delay for successful in order reception of packets. We find that, in certain applications, judicious choices provide results that are close to those that would be obtained with a full-duplex system. The second part of this thesis studies the problem of data dissemination in arbitrary networks. In particular, we study the problem of minimizing the delay incurred in disseminating a finite number of data packets. We show that the optimal solution to the problem can be thought of as a scheduling problem, which is hard to solve. Thus, we consider the use of a greedy linear network coding algorithm that only takes into account the current state of the system to make a decision. The proposed algorithm tries to maximize the impact on the network at each slot, i.e., maximize the number of nodes that will benefit from the coded packet sent by each active transmitter. We show that our scheme is considerably better, in terms of the number of slots to complete transmission, than schemes that choose the node with more information as the transmitter The third part of this work studies the case of underwater acoustic networks as an example of delay challenged networks. We consider the use of network coding under two different lights. First, as a means to obtain a lower bound on the transmission power of multicast connections in underwater networks. Second, to develop practical schemes useful in such networks. Finally, we study upper bounds on the transport capacity of underwater acoustic networks under unicast connections. We show that the amount of information that can be exchanged by each source-destination pair in underwater acoustic networks goes to zero as the number of nodes n goes to infinity. This occurs at least at a rate n-1/Qe-Wo(O(n-k)) where Wo represents the branch zero of the Lambert W function, and a path loss exponent of a. Note that typical values of the path loss exponent are a E [1, 2] for underwater acoustic networks. This is significantly different to the a> 2 of radio wireless applications.