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Hub labels: Theory and practice
 In SEA
, 2014
"... Abstract. The Hub Labeling algorithm (HL) is an exact shortest path algorithm with excellent query performance on some classes of problems. It precomputes some auxiliary information (stored as a label) for each vertex, and its query performance depends only on the label size. While there are polynom ..."
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Abstract. The Hub Labeling algorithm (HL) is an exact shortest path algorithm with excellent query performance on some classes of problems. It precomputes some auxiliary information (stored as a label) for each vertex, and its query performance depends only on the label size. While there are polynomialtime approximation algorithms to find labels of approximately optimal size, practical solutions use hierarchical hub labels (HHL), which are faster to compute but offer no guarantee on the label size. We improve the theoretical and practical performance of the HL approximation algorithms, enabling us to compute such labels for moderately large problems. Our comparison shows that HHL algorithms scale much better and find labels that usually are not much bigger than the theoretically justified HL labels. 1
R.F.: Robust exact distance queries on massive networks
, 2014
"... We present a versatile and scalable algorithm for computing exact distances on realworld networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road networks. W ..."
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We present a versatile and scalable algorithm for computing exact distances on realworld networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road networks. We achieve this by providing a unified approach based on the concept of 2hop labels, improving upon existing methods. In particular, we introduce a fast samplingbased algorithm to order vertices by importance, as well as effective compression techniques.
Robust distance queries on massive networks
 In Proceedings of the 22nd Annual European Symposium on Algorithms (ESA’14), Lecture Notes in Computer Science
, 2014
"... Abstract. We present a versatile and scalable algorithm for computing exact distances on realworld networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road n ..."
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Abstract. We present a versatile and scalable algorithm for computing exact distances on realworld networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road networks. We achieve this by providing a unified approach based on the concept of 2hop labels, improving upon existing methods. In particular, we introduce a fast samplingbased algorithm to order vertices by importance, as well as effective compression techniques.