Paper
24 May 2012 A system architecture for exploiting mission information requirement and resource allocation
Author Affiliations +
Abstract
In a military scenario, commanders need to determine what kinds of information will help them execute missions. The amount of information available to support each mission is constrained by the availability of information assets. For example, there may be limits on the numbers of sensors that can be deployed to cover a certain area, and limits on the bandwidth available to collect data from those sensors for processing. Therefore, options for satisfying information requirements should take into consideration constraints on the underlying information assets, which in certain cases could simultaneously support multiple missions. In this paper, we propose a system architecture for modeling missions and allocating information assets among them. We model a mission as a graph of tasks with temporal and probabilistic relations. Each task requires some information provided by the information assets. Our system suggests which information assets should be allocated among missions. Missions are compatible with each other if their needs do not exceed the limits of the information assets; otherwise, feedback is sent to the commander indicating information requirements need to be adjusted. The decision loop will eventually converge and the utilization of the resources is maximized.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fangfei Chen, Thomas La Porta, Diego Pizzocaro, Alun Preece, and Mani B. Srivastava "A system architecture for exploiting mission information requirement and resource allocation", Proc. SPIE 8389, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III, 838908 (24 May 2012); https://doi.org/10.1117/12.923685
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Intelligence systems

Cameras

Roads

Target detection

Sensors

Unmanned aerial vehicles

Stochastic processes

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