Analysis of wireless information locality and association patterns in a campus

Our goal is to explore characteristics of the environment that provide opportunities for caching, prefetching, coverage planning, and resource reservation. We conduct a one-month measurement study of locality phenomena among wireless Web users and their association patterns on a major university campus using the IEEE 802.11 wireless infrastructure. We evaluate the performance of different caching paradigms, such as single user cache, cache attached to an access point (AP), and peer-to-peer caching. In several settings such caching mechanisms could be beneficial. Unlike other measurement studies in wired networks in which 25% to 40% of documents draw 70% of Web access, our traces indicate that 13% of unique URLS draws this number of Web accesses. In addition, the overall ideal hit ratio of the user cache, cache attached to an access point, and peer-to-peer caching paradigms (where peers are coresident within an AP) are 51%, 55%, and 23%, respectively. We distinguish wireless clients based on their inter-building mobility, their visits to APs, their continuous walks in the wireless infrastructure, and their wireless information access during these periods. We model the associations as a Markov chain using as state information the most recent AP visits. We can predict with high probability (86%) the next AP with which a wireless client will associate. Also, there are APs with a high percentage of user revisits. Such measurements can benefit protocols and algorithms that aim to improve the performance of the wireless infrastructures by load balancing, admission control, and resource reservation across APs.