Compressing SMS Messages for Lowering Communication Costs in Rural Africa

Abstract

Traditional compression algorithms appear to be largely unsuccessful with regards to short strings. In developing countries without connectivity to the web and data infrastructure, SMS remains one of the few ways of handling text-based information. With SMS service providers typically charging for SMS messages on a per-message basis, there exists a need to provide some form of short string compression, specifically with regards to highly structured data. This paper seeks to answer whether or not dictionary structures produce better results of compression than traditional algorithms with respect to highly structured data. To determine whether or not this approach would work, we developed a configurable parser that, when properly configured, accepts the various forms of structured data as provided by the client. We then compare the results to traditional compression mechanisms and measure the success.