Based on evolutionary computation, a novel real-time route planner for unmanned air vehicles is presented. In the evolutionary route planner, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is not required. The planner incorporates domain-specific knowledge, can handle unforeseeable changes of the environment, and take into account different kinds of mission constraints such as minimum route leg length and flying altitude, maximum turning angle, and fixed approach vector to goal position. Furthermore, the novel planner can be used to plan routes both for a single vehicle and for multiple ones. With Digital Terrain Elevation Data, the resultant routes can increase the surviving probability of the vehicles using the terrain masking effect.

Collecting network traffic is becoming a more challenging task in passive network measurement due to the rapid growth of link speed. Flow-based network traffic capture and storage is an efficient way for high-speed network measurement. Based on the statistical investigation of the correlations between flow size and the maximum packet interinterval time of consecutive packets within a flow, we obtain the empirical conditional distribution functions for some popular TCP protocol-based application flows, and then propose a probability-guaranteed adaptive timeout algorithm (PGAT) for flow termination decision. The assessment criteria for the flow termination decision algorithm is systematically developed. Comparisons on flow generation ratio, flow intact ratio, and mean flow extra retaining time metrics indicate that the PGAT algorithm can obtain more attractive performance than other schemes.