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A Spatial Computing Approach to Distributed Algorithms

Creating distributed applications for large, decentralized networks is challenging for traditional programming approaches, posing a growing obstacle as the number and capabilities of networked devices continue to advance. In many applications, however, the network of devices is not itself of interest. Rather, we are interested in the relationships of the devices to their surroundings and their relative positions. We may thus instead write programs for the continuous space occupied by the devices, viewing the network as a discrete approximation of that space. This “amorphous medium” approach to spatial computing leads to algorithms based on manifold geometry, which are by their nature robust, adaptive, and scalable to vast numbers of devices. This paper brings together previous results into an overview of this programming approach and explains how the manifold geometry abstraction provides benefits in scalability, robustness, and adaptability. Keywords-spatial computing; amorphous medium; distributed algorithms; Proto; self-*