Advertisement

Scalability and Performance of Multi-threaded Algorithms for International Fare Construction on High-Performance Machines

  • Chandra N. Sekharan
  • Krishnan Saranathan
  • Raj Sivakumar
  • Zia Taherbhai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2552)

Abstract

We describe the design, implementation and performance of a project for constructing international fares at United Airlines. An efficient fare construction engine allows an airline to simplify, and automate the process of pricing fares in lucrative international markets. The impact of a fare engine to the revenues of a large airline has been estimated at between $20M and $60M per year. The goal is to design an efficient software system for handling 10 Gb of data pertaining to base fares from all airlines, and to generate over 250 million memory-resident records (fares). The software architecture uses a 64-bit, object -oriented, and multi-threaded approach and the hardware platforms used for benchmarking include a 24-CPU, IBM S-80 and 32-CPU, Hewlett-Packard Superdome. Two competing software designs using (i) dynamic memory and (ii) static memory are compared. Critical part of the design includes a scheduler that uses a heuristic for load balancing which is provably within a constant factor of optimality. Performance results are presented and discussed.

Keywords

Link Formation Dynamic Memory Fare Class Compatibility Check Destination City 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [2]
    Sarac, S. Rayaprolu, K. Saranathan, and S. Ramaswamy. “Automated Fare Response: An International Pricing Problem”, INFORMS, Aviation Applications, Miami, 2001.Google Scholar
  2. [3]
    Garey, J and Johnson, D. “Theory of NP-Completeness”, Freeman Press, 1976.Google Scholar
  3. [4]
    Hochbaum, D. Shmoys, D. “Using Dual Approximation Algorithms for Scheduling Problems: Theoretical and Practical Results”, Journal of ACM, Vol. 34, No.1, January 1987, pp.144–162.CrossRefMathSciNetGoogle Scholar
  4. [5]
    Graham, R. “Bounds on Multi-processing Timing Anomalies”, SIAM J. Applied Mathematics, Vol. 17, 1969, pp. 416–429.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Chandra N. Sekharan
    • 1
  • Krishnan Saranathan
    • 2
  • Raj Sivakumar
    • 2
  • Zia Taherbhai
    • 2
  1. 1.Department of Computer ScienceLoyola University of Chicago
  2. 2.Information Sciences DivisionWHQKB, United AirlinesChicago

Personalised recommendations