This investigation starts with the hypothesis that fusing heterogeneous data sources can increase the data coverage and improve the accuracy of traffic-related applications in Intel-ligent Transportation Systems (ITS). Therefore, we designed (i) a Data Fusion on Intelligent Transportation Systems (DataFITS) framework that allows collecting data from numerous sources and fusing them according to spatial and temporal criteria; (ii) a traffic estimation method that groups road segments into regions, identify correlations between them, and measure the traffic distribution to estimate traffic. As a result, DataFITS increased by 130% the number of road segments coverage and enhanced, by fusion process, around 35% of road overlapping data sources. We evaluate the traffic estimation of the 15 most correlated regions, where the fused data together with correlated areas resulted in the best traffic estimation accuracy by reaching up to 40% in some cases and 9% on average.

This paper introduces a hierarchy of queues complementing each other to handle ever-changing communication scenarios in tactical networks. The first queue stores the QoS-constrained messages from command and control systems. These messages are fragmented into IP packets, which are stored in a queue of packets (second) to be sent to the radio buffer (third), which is a queue with limited space therefore, open to overflow. We start with the hypothesis that these three queues can handle ever-changing user(s) data flows (problem$A$) through ever-changing network conditions (problem$B$) using cross-layer information exchange, such as buffer occupancy, data rate, queue size and latency (problem$A|B$). We introduce two stochastic models to create sequences of QoS-constrained messages ($A$) and to create ever-changing network conditions ($B$). In sequence, we sketch a control loop to shape$A$to$B\;$to test our hypothesis using model$A|B$, which defines enforcement points at the incoming/outgoing chains of the system together with a control plane. Then, we discuss experimental results in a network with VHF radios using data flows that overflows the radio buffer over ever-changing data rate patterns. We discuss quantitative results showing the performance and limitations of our solutions for problems$A$,$B$, and$A|B$.