Spatial Grasp Model for the Investigation of Distributed Dynamic Worlds.

Abstract

This is a sequel to the previous seven books on high-level management of large distributed systems. Born half a century ago before the Internet and called WAVE in its infancy the developed model and technology were tested on numerous applications in different countries. The book is focused on their extended applications including new worlds of terrestrial and celestial nature, global systems, and NASA strategic research areas and technologies. It presents the main ideas of the Spatial Grasp (SG) paradigm and details of its key Spatial Grasp Language (SGL), including its philosophy, methodology, syntax, semantics, and interpretation in distributed systems. The scenario pattern in SGL spatially propagates, replicates, modifies, covers, and matches the distributed worlds in a parallel wave-like mode, allowing us to evaluate large distributed phenomena by their physical or virtual coverage. The solutions in SGL contain the investigation of the regions of interest like hurricanes and forest fires, with similar techniques applicable for celestial cases, and show how to find images in arbitrary distributed networks using the spatial graph-pattern matching technique. It provides the investigation of group behavior of ocean animals, discovery of unknown terrain features, and path-findings in large transport networks. Comparison of SGL with other programming, specialized, and natural languages shows simplicity and compactness of the obtained solutions, due to SGL operating directly on the distributed networked bodies in a holistic, parallel, and pattern matching mode. The relation of SGL to some higher mental concepts has been investigated by showing how to simulate gestalt psychology principles and maintain global awareness and consciousness of distributed systems by SGL recursive virus-like spatial coverage. The results confirm the potential applicability of the developed paradigm, language, and technology for solving much broader range of problems related to large unknown worlds. The approach can also be used for the high-level formulation of key problems and their solutions instead of natural languages, due to the clarity and compactness of the resulting descriptions.