Evolutionary Content Pre-fetching in Mobile Networks

Abstract

Recently, an increasing number of smart phone users are eagerly using the cellular network in extensive data applications. In particular, multimedia downloads generated by Internet-capable smart phones and other portable devices (such as iPad) have been widely recognized as the major source for strains in cellular networks, to a degree where service quality for all users is significantly impacted. Lately, patterns in both the content consumption as well as the Wi-Fi access by the users were alleged to be available. In this paper we introduce a technique to schedule the content for prefetching based on mobile usage patterns. This technique utilizes both a content profile as well as a bandwidth profile to schedule content for prefetching. Users can then use the cached version of the content in order to achieve a better user experience and reduce the peak-to-average ratio in mobile networks, especially during peak hours of the day. An experiment using real users traces was conducted and the results after applying the proposed evolutionary scheduling algorithm show that up to 70 percent of the user content requests can be fulfilled i.e. the content was successfully cached before request.