Railroad Fare Modeling

Problem:

A European railroad needed to monitor its seat reservation activity in order to create a fare model reflecting the usage of the rail line. The fare modeling was a computationally intensive application running on a Solaris system with an Oracle database.

HPE Shadowbase Solution: Heterogeneous Continuous Processing Systems

In Figure 1, an HPE NonStop server hosts a ticketing and seat reservation application, which sends the reservation information to an Oracle database on a Solaris server that runs a fare/price modeling application. The fare modeling application sends back the updated pricing information to the NonStop server for ticket availability and pricing updates, and logs consumer demand so that the company can attain price equilibrium for optimum profits. Both applications and databases are updated in real-time using Shadowbase heterogeneous bi-directional replication.

railroad-fare-modeling

Figure 1 — Shadowbase for Heterogeneous Bi-directional Data and Application Integration

  • Ticketing and seat reservations are handled by an HPE NonStop server.
  • As tickets are sold, the reservation information is replicated from the NonStop SQL database to the Oracle database on the Solaris system.
  • There, the fare modeling applications track reservation activity and make decisions concerning future fares.
  • Changes to the pricing of remaining available seats are then returned to the NonStop server.
  • The railroad can now monitor ridership traffic and modify its fare model to maximize profits in real-time.

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The above was adapted from the book: Breaking the Availability Barrier, Volume III: Active/Active Systems in Practice by Paul J. Holenstein, Dr. Bruce Holenstein, and Dr. Bill Highleyman.