Self-awareness facilitates a proper assessment of costconstrained cyber-physical systems, allocating limited resources where they are most needed. Together, situation awareness and attention are key enablers for self-awareness in efficient distributed sensing and computing networks.

Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.

Data acquisition and data fusion systems are becoming increasingly complex, being in fact systems of systems, where every component may be a system with varying levels of autonomy by themselves. Possible changes in system configuration by entities joining or being removed from the system make the system complex. As synchronous operation cannot be expected in such a system configuration, the temporal and spatial correctness of data must be achieved via other means. This paper presents the concept of mediated interactions as a method for ensuring correctness of computation in a distributed system. The mediator associated with each computing entity is responsible for online checking of the data both before it is sent out at the sender side and before it is received at the receiver side, ensuring that only data satisfying the validity constraints of the receiver-side data processing algorithm is used in computation. This assumes that each data item is augmented with metadata, which enables online data validation. The validity and quality dimensions in use depend on the system requirements defined by a specific problem and situational context; they may be temporal, spatial and involve various data quality dimensions, such as accuracy, confidence, relevance, credibility, and reliability. Among other capabilities, the mediator is able to cope with the unknowns in the temporal dimension that occur at runtime and are not predictable, such as channel delay, jitter of clocks and processing delays. This capability becomes an especially relevant factor in multi-tasking systems and in configurations in which a computing entity may have to process a variable number of parallel streams of data.Both the architecture and a simulation case study of a distributed data fusion scenario are presented in the paper.

System of systems comprises interacting, heterogeneous, autonomous components with incomplete information about their inner states, and about the surrounding environment. Many interactions are often not rigorously defined, and change dynamically. System of systems usually exhibits emergent behavior that cannot be predicted by analyzing static properties of the components, and is not always permissible. This paper suggests that the designer can improve system's behavior by substituting (part of) regular interactions with smart mediated interactions that bolster up shared situation awareness of the system's components and thus strengthens system's capability to monitor and partially control its emergent behavior. This paper discusses smart mediated interactions that focus on awareness of temporal features and on estimates of spatial location of the components. Interactions are assembled into proactive middleware that forms a backbone of system of systems.

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The application of wireless sensor networks (WSN) for the task of acoustic localization provides great opportunities for distributed cooperative tracking of sound sources in large areas. However WSNs are significantly more limited in terms of computational resources and power than typical computer systems. Therefore the methods applied for acoustic localization in WSN must be optimized for minimal resource consumption. This paper builds on the advances of Steered Response Power with Phase Transform (SRP-PHAT) optimization and proposes a further simplification in terms of additional minimization of the initial search volume. By using several linear microphone arrays we are able to estimate the initial region of sound source and reduce the number of computations by at least one order of magnitude. The results of several experiments on real signals confirm the achieved improvements.