Flight search optimization using in-memory data management

Abstract

In current travel planning systems, even for a relatively straightforward round-trip query, it is not uncommon to spend more than 30 seconds. If the results can be produced as quickly as possible it will res u I t in a competitive advantage in the market since the delay is undesirable for the user of the system, as it reduces inter activity. Traditionally, data will be placed in storage then, when needed, will be accessed and acted upon in the computer's memory which results in a natural bottleneck that reduces speed. With the emergence of multi-core processors and availability of large amounts of main memory at low cost new breakthroughs in the software industry such as in-memory technology are being created In-memory and multicore technology have the potential to improve the performance. If all data can be stored in the main memory instead of on disk, the performance of operations on data, especially on mass data, is improved. In this paper it is intended to take the advantage of in memory technology, where all the data resides and has been processed in the main memory and develop a CPU based algorithm in order to optimize the flight and air fare search in air travel planning, basically using hashing technique. This algorithm also has the potential to take the advantage of multi core processors in the future since it used in-memory data management. With the use of Google hash maps the memory has been used effectively. With the selected sample data almost all the searches could be performed in milliseconds. Also with the increase of the maximum number of connecting airports, searching time is also increased.