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Global network management under spatial grasp paradigm


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Abstract

The paper describes basics of high-level management model and technology for dealing with large distributed human or technical systems which can be represented as dynamic physical-virtual networks covering any terrestrial or celestial environments. The main technology component, Spatial Grasp Language (SGL), allows us to obtain powerful and compact spatial solutions of different problems by directly expressing their top semantics while hiding traditional system organization and management routines inside efficient networked implementation.  Different network creation, evolution, matching, and transformation approaches are investigated and shown in SGL on general networks, which may be practically useful in a variety of areas influencing the dangerously growing world dynamics and caused, for example, by climate change, military, religious and ethnic conflicts, terrorism, refugee flows, weapons proliferation, political and industrial restructuring, growing inequality, economic instability, global insecurity, and very recently, due to the world-wide pandemic horror. The demonstrated networking approach, with its unlimited parallel and fully distributed capabilities to operate without vulnerable central information and management resources, can also cover much greater spheres, up to the creation and evolution of the very universe, by offering real mechanisms for its simulation on arbitrary large distributed computer networks with millions to billions of communication nodes. The developed networking technology can be readily implemented even in traditional university environments, as was done in the past for its previous versions in different countries under the author’s supervision.

Keywords

world dynamics, high-level network management, spatial grasp technology, spatial grasp language, network evolution, network dynamics, graph pattern matching, distributed simulation, parallel and distributed programming, millions, computer, economic, restructuring, growing, ethnic

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