A network-centric model of situational awareness

In a wireless ad hoc multimedia network, how does the Quality of Experience (QoE) of the user affect the level of Situational Awareness (SA)? Is maximum QoE necessary for high SA? In this empirical study, we propose a novel measurement approach to quantify SA based on the QoE of the user. The relationship between QoE and network Quality of Service (QoS) metrics such as delay and packet loss is well known. Therefore, quantifying the SA-QoE-QoS relationship will help the network operator to ensure a high level of SA when the network is under attack, through parsimonious allocation of network resources such as spectrum and power. We first define SA metrics in four contexts: Surroundings awareness, Target awareness, Location awareness, and Responsiveness (SETLR model). Next, we design an experiment and define an objective expression for each SETLR metric. We mathematically formulate SA as a function of QoE, using real data, and show that this relationship is logistic in nature. This new utility function for measuring SA can now be used in network optimization techniques to avoid over-provisioning. Finally, we observe that maximum QoE is in fact not necessary to ensure high SA; a Mean Opinion Score of just 2–3 is necessary in our scenario.