Paper
12 January 2018 Network placement optimization for large-scale distributed system
Author Affiliations +
Abstract
The network geometry strongly influences the performance of the distributed system, i.e., the coverage capability, measurement accuracy and overall cost. Therefore the network placement optimization represents an urgent issue in the distributed measurement, even in large-scale metrology. This paper presents an effective computer-assisted network placement optimization procedure for the large-scale distributed system and illustrates it with the example of the multi-tracker system. To get an optimal placement, the coverage capability and the coordinate uncertainty of the network are quantified. Then a placement optimization objective function is developed in terms of coverage capabilities, measurement accuracy and overall cost. And a novel grid-based encoding approach for Genetic algorithm is proposed. So the network placement is optimized by a global rough search and a local detailed search. Its obvious advantage is that there is no need for a specific initial placement. At last, a specific application illustrates this placement optimization procedure can simulate the measurement results of a specific network and design the optimal placement efficiently.
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Yu Ren, Fangfang Liu, Yunxia Fu, and Zheng Zhou "Network placement optimization for large-scale distributed system", Proc. SPIE 10621, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 106211S (12 January 2018); https://doi.org/10.1117/12.2295376
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KEYWORDS
Distributed computing

Computer programming

Metrology

Optimization (mathematics)

Genetic algorithms

Mathematical modeling

Network architectures

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