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.
Computing on the edge of the Internet of things comprises among other tasks in-sensor signal processing and performing distributed data fusion and aggregation at network nodes. This poses a challenge to distributed sensor networks of low computing power devices that have to do complex fusion, aggregation and signal processing in situ. One of the difficulties lies in ensuring validity of data collected from heterogeneous sources. Ensuring data validity, for example, the temporal and spatial correctness of data, is crucial for correct in-network data fusion and aggregation. The article considers wireless sensor technology in military domain with the aim of improving situation awareness for military operations. Requirements for contemporary intelligence, surveillance and reconnaissance applications are explored and an experimental wireless sensor network, designed to enhance situation awareness to both in-the-field units and remote intelligence operatives, is described. The sensor nodes have the capability to perform in-sensor signal processing and distributed in-network data aggregation and fusion complying with edge computing paradigm. In-network data processing is supported by service-oriented middleware which facilitates run-time sensor discovery and tasking and ad hoc (re)configuration of the network links. The article describes two experiments demonstrating the ability of the wireless sensor network to meet intelligence, surveillance and reconnaissance requirements. The efficiency of distributed data fusion is evaluated and the importance and effect of establishing data validity is shown.
The Command and Control (C2) system that provide information to the actors in a conflict has always been a key target for technology advancement. The ongoing development of automated digital military information systems has enabled, and is demanding the development of specific functional area support systems. The focus of communication systems and methods is shifting away from human to human communication towards human to machine and machine to machine communication. Along with this change have come proliferation of operating systems, data representation schemata, data exchange methods and other aspects that now confront us with a "confusion of languages" [1].The paper describes the information exchange issues and challenges involved in creating shared situation awareness in the described systems. Some existing models for both information representation and exchange are described and a proactive communication model for information exchange in a distributed system is presented. The proactive communication model caters for the data requirements of the data consumers, the objective being to provide the information required for forming good situational awareness of the data consumer. The proactive communication model relies on a middleware [5] that is able to acquire the information required by the consumer and to cater for the restrictions set by the data consumer on the requested data. The paper describes the middleware and how it can be applied in the above-described systems.Index Terms -cooperative distributed systems, interactive computing, middleware (for subscription and distribution of situational information), situation awareness, validation and verification
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