Dynamic Adaptive Content Delivery using Genetic Algorithm

We present a new framework of Dynamic Adaptive Content Delivery (DACD), suitable for diversified mobile devices. This system is capable to adapt multiple types of content dynamically in response to the change of device environment. We introduce Genetic Algorithm for the dynamic learning and identification of the Majority Supported Capability Set (MSCS) which is the key decision element for adaptation. The framework is demonstrated using real telecom network data with the help of WURFL (Wireless Universal Resource File) repository. Results indicate that the DACD framework can efficiently identify the MSCS that closely matches the capability of the population. Thus the content delivery servers store significantly reduced variety of content maintaining the satisfaction of majority devices in the population.