Deriving the distributions for the numbers of short message arrivals

Hui-Nien Hung, Yi-Bing Lin*, Chao Liang Luo

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

In the broadband era, narrowband short message service (SMS) is still the most popular wireless data service. Many studies have been conducted to investigate the performance of SMS based on the arrival rates of short messages. From Chunghwa Telecom's commercial SMS call data records, we observed that even if the SMS arrival rates are the same, the distributions for the number of SMS arrivals per half hour are quite different for various observed days. We further identify that for the SMS traffic in a specific day, there are non-burst and burst periods. This paper investigates the SMS behaviors on weekdays, weekends, and holidays (specifically, new years' days and eves). With the assistance of kernel-based fitting method, we derive the SMS arrival number distributions of various traffic types and observed days. Our approach fits each SMS arrival number distribution by three cubic polynomial functions that can accurately capture the SMS behaviors. On the basis of the SMS arrival number distributions derived from our model, the mobile operators have better understanding about the volumes of short messages in different times and days, which can be used to design more flexible short message charging rates.

Original languageEnglish
Pages (from-to)450-459
Number of pages10
JournalWireless Communications and Mobile Computing
Volume14
Issue number4
DOIs
StatePublished - 1 Mar 2014

Keywords

  • arrival distribution
  • kernel-based fitting
  • mobile telecommunications network
  • short message service (SMS)

Fingerprint Dive into the research topics of 'Deriving the distributions for the numbers of short message arrivals'. Together they form a unique fingerprint.

  • Cite this