Abstract
Engineers dealing with different scaled and interconnected engineering systems such as tactical wireless RF communication systems have growing needs for analyzing complex adaptive systems. We propose a systemic engineering methodology based on systematic resolution of complex issues in engineering design. Issues arise which affect the success of each process. There are a number of potential solutions for these issues, which are subject to discussion based on the result assembled from a variety of sources with a range of measures. There are needs to assemble and balance the results in a success measure showing how well each solution meets the system’s objectives. The uncertain arguments used by the participants and other test results are combined using a set of mathematical theory for analysis. This process-based construction helps not only in capturing the way of thinking behind design decisions, but also enables the decision-makers to assess the support for each solution. The complexity in this situation arises from the many interacting and conflicting requirements of an increasing range of possible parameters. There may not be a single ‘right’ solution, only a satisfactory set of resolution, which this system helps to facilitate. Applying systems engineering approaches will definitely help in measuring and analyzing tactical RF wireless networks, smart and innovative performance matrixes through tactical modeling and simulation scenarios may also be developed and enhanced. Systematic utilize of systems engineering approaches with RF electronic warfare modeling and simulation scenarios can support future research in vulnerability analysis of RF communication networks. RF electronic tactical models are used to provide a practical yet simple process for assessing and investigate the vulnerability of RF systems. The focus is also on tactical wireless network within a system of systems (SoS) context research area and to provide a comprehensive network assessment methodology. Researchers have proposed a variety of methods to build network trees with chains of exploits, and then perform normal post-graph vulnerability analysis. This chapter presents an approach to use mathematical Bayesian network to model, calculate and analyze all potential vulnerability paths in wireless RF networks.
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