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Engineering Algorithms for Large Network Applications

2002; Schulz, Wagner, Zaroliagis

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Encyclopedia of Algorithms

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Problem Definition

Dealing effectively with applications in large networks, it typically requires the efficient solution of one ore more underlying algorithmic problems. Due to the size of the network, a considerable effort is inevitable in order to achieve the desired efficiency in the algorithm.             

One of the primary tasks in large network applications is to answer queries for finding best routes or paths as efficiently as possible. Quite often, the challenge is to process a vast number of such queries on-line: a typical situation encountered in several real-time applications (e. g., traffic information systems, public transportation systems) concerns a query‐intensive scenario, where a central server has to answer a huge number of on-line customer queries asking for their best routes (or optimal itineraries). The main goal in such an application is to reduce the (average) response time for a query.

Answering a best route (or optimal itinerary) query translates in computing a minimum...

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Recommended Reading

  1. Delling, D., Holzer, M., Müller, K., Schulz, F., Wagner, D.: High‐Performance Multi-Level Graphs. In: 9th DIMACS Challenge on Shortest Paths, Nov 2006. Rutgers University, USA (2006)

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  2. Delling, D., Sanders, P., Schultes, D., Wagner, D.: Highway Hierarchies Star. In: 9th DIMACS Challenge on Shortest Paths, Nov 2006 Rutgers University, USA (2006)

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  3. Goldberg, A.V., Harrelson, C.: Computing the Shortest Path: A * Search Meets Graph Theory. In: Proc. 16th ACM-SIAM Symposium on Discrete Algorithms – SODA, pp. 156–165. ACM, New York and SIAM, Philadelphia (2005)

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  4. Gutman, R.: Reach-based Routing: A New Approach to Shortest Path Algorithms Optimized for Road Networks. In: Algorithm Engineering and Experiments – ALENEX (SIAM, 2004), pp. 100–111. SIAM, Philadelphia (2004)

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  5. Holzer, M., Schulz, F., Wagner, D.: Engineering Multi-Level Overlay Graphs for Shortest-Path Queries. In: Algorithm Engineering and Experiments – ALENEX (SIAM, 2006), pp. 156–170. SIAM, Philadelphia (2006)

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  6. Pyrga, E., Schulz, F., Wagner, D., Zaroliagis, C.: Efficient Models for Timetable Information in Public Transportation Systems. ACM J. Exp. Algorithmic 12(2.4), 1–39 (2007)

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  7. Sanders, P., Schultes, D.: Highway Hierarchies Hasten Exact Shortest Path Queries. In: Algorithms – ESA 2005. Lect. Note Comp. Sci. 3669, 568–579 (2005)

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  8. Sanders, P., Schultes, D.: Engineering Highway Hierarchies. In: Algorithms – ESA 2006. Lect. Note Comp. Sci. 4168, 804–816 (2006)

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  9. Schulz, F., Wagner, D., Weihe, K.: Dijkstra's Algorithm On-Line: An Empirical Case Study from Public Railroad Transport. ACM J. Exp. Algorithmics 5(12), 1–23 (2000)

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  10. Schulz, F., Wagner, D., Zaroliagis, C.: Using Multi-Level Graphs for Timetable Information in Railway Systems. In: Algorithm Engineering and Experiments – ALENEX 2002. Lect. Note Comp. Sci. 2409, 43–59 (2002)

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  11. Wagner, D., Willhalm, T., Zaroliagis, C.: Geometric Containers for Efficient Shortest Path Computation. ACM J. Exp. Algorithmics 10(1.3), 1–30 (2005)

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Author information

Authors and Affiliations

  1. Department of Computer Engineering & Informatics, University of Patras, Patras, Greece

    Christos Zaroliagis

Authors
  1. Christos Zaroliagis
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer ScienceMcCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL, 60208, USA

    Ming-Yang Kao Professor of Computer Science

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© 2008 Springer-Verlag

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Zaroliagis, C. (2008). Engineering Algorithms for Large Network Applications. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30162-4_125

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