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 resu
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. iti tic
emergence of multi-core processors and availability of large amounts of main memory> at low cost new
breakthroughs in the sofrware industry such as in-memory technologyt are being created. In-memoiy 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 multicore 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.
