Leveraging Complexity Science and Emergence for a Self-organizing Battlespace [video]
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The network-centric battlespace is constructed from thousands of decentralized nodes that need to share a world model known as a common operational picture (COP). The nodes represent each element of the battlespace, and consist of the functional element with aspects of communication and simple autonomy. Each node is mapped to a mobile vehicle or static intelligent communication device, and in some cases, can consist of several intelligent sensors at a single location. To effectively manage the battlespace, each node should have some awareness of the topology of the force laydown, as well as the relative position of some of its neighbors. This knowledge would facilitate rapid self-organizing strategies for dynamic routing of priority data between nodes in one section of the battlespace, with a more distant section. The chosen topology can affect network failures as well as the success of network attacks, and this information should be transferred within a sparse data element, similar to the stigmergic information used by ant colonies (pheromone marker) and beehives (bee “dance”). Recent work has shown that spatially distributed large ad-hoc networks lose edge-node communication due to scaling issues for the large numbers of networked nodes needed for a battlespace. This can compromise availability within the network. To further complicate matters, a Congressional Research Report from 2007 showed that the resulting scaling limitations were caused by a combinatorial explosion, due to the massive number of route calculations needed for large scale ad-hoc networks. This research investigated an adaptive fractal algorithm (NPPR) for emergent self-organizing topologies, that may improve the availability and resiliency for large ad-hoc networks required for cyber offense and defense. The results of this study showed stigmergic behavior, where two variables were able to dynamically convey the collective topology to all network nodes. By using a linear equation similar to the point-slope line equation, the calculation requirement for each node to compute the relative positions of 10,000 other nodes in under 100 milliseconds, was met by even the slowest computational nodes. The resulting topologies exhibited swarm-like self-organizing behaviors that clustered around targets and rendezvous points.
TechCon2017 (CRUSER)Presented by Dr. Josef Schaff: NAVAIRIncludes slides
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Milicic, Gregory J. (Monterey California. Naval Postgraduate School, 2005-03);Wireless mesh mobile ad hoc networks (MANETs) provide the military with the opportunity to spread information superiority to the tactical battlespace in support of network-centric warfare (NCW). These mesh networks provide ...
Neushul, James D. (Monterey, California. Naval Postgraduate School, 2003-09);This work represents the realization of Network-Centric goals of interoperability, information management, systems integration and cohesive battlespace visualization using networked computer technology. The application of ...
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