Airborne networks are special types of mobile ad hoc wireless networks that can be used on aerospace vehicles to enhance situational awareness, motion coordination, and operational efficiency. This is achieved through the exchange of state information in a timely, reliable, and secure fashion. Airborne networks are becoming an essential part of the commercial air transportation industry. Other applications include UAVS for military surveillance and attack missions, and crop monitoring for the agricultural industry. While airborne networks can greatly facilitate decentralized flight coordination among the multiple vehicles, the decision making process for this coordination must be made across the networks dynamically and is necessarily distributed in nature. Each vehicle plans its own trajectory to optimize a private performance index subject to its private constraints, and at the same time, seeks to optimize a certain common objective subject to the requirements of flight coordination and common constraints. In this paper, we study this problem by considering the decentralized and dynamic flight planning of multiple UAVs in a real-time sense. In particular, we examine the effect of time delays occurring during the iterative solution process, and discuss the tradeoff of different strategies for implementing decentralized trajectory optimization in real-time.