Mobility-aware Web prefetching over heterogeneous wireless networks

This paper presents a predictive framework for mobility-aware prefetching to enhance the experience of a mobile Web user roaming between heterogeneous wireless access networks. We consider a heterogeneous two-tier wireless access network system, composed of smaller, but faster and cheaper wireless local area networks (WLANs) placed within a much larger, but slower and more expensive cellular wireless data network. An optimal prefetch threshold algorithm is proposed, which takes into consideration the user mobility pattern, the relative characteristics of the networks, and the user perceived value of time. Using current industry network parameters, we study the performance of the proposed prefetching algorithm. Our numerical results show how user mobility and the heterogeneous network configuration significantly alter the prefetching threshold. The performance of this algorithm is compared with that of a static prefetching algorithm, demonstrating that mobility-aware prefetching can significantly improve the performance of future-generation heterogeneous wireless networks.