Leveraging Complexity Science and Emergence for a Self-organizing Battlespace

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Apr 11, 2017
Accession Number
AD1038213

Entities

People

  • Josef Schaff

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Ad Hoc Networks
  • Algorithms
  • Cognitive Systems Engineering
  • Complex Systems
  • Equations
  • Genetic Algorithms
  • Mesh Networks
  • Multiagent Systems
  • Network Topology
  • Robotics
  • Self Organizing Systems
  • System Of Systems
  • Systems Biology
  • Systems Engineering
  • Topology
  • Unmanned Systems
  • Warfare

Readers

  • Aerospace Engineering.
  • Computational Modeling and Simulation
  • Computer Networking