dbsfrael-Our goal is to erplnre characteristics nf the envirnnnient that provide opportunities fur caching, prefetching, coverage planning, and resource reseerratinn.-We cnndud a oneniontli measurenient study of locality phennmena among wireless weh users and their assoriation patterns on a major university rampw using the IEEE !3002.11 wirelesc infrastructure. W e evaluate the performance of different caching paradigms, such as single user cache. cache attached to an access pnint (AP), and peer-to-peer caching. In several settings such caching niechanisms could he heneficial. Unlike other measurement studies in wired networks in which 1 5 % to 40% of documents draw 70% of weh access, nur trace5 indirute,that 13% of unique LTR,LS draws this nnmher of weli accesses. In addition, the overall ideal hit ratio nf tlie user cache, cache attached to an access pnint. and peer-to-peer caching paradigms (where peers are caresident within an AP) are 51%. 55%. and U%, respectively. We distinguish wireless clients hksed on their inter-huilding mnhility. their risiic to APs, their continunus walks in the wireless infrastructure, and their wireless information access during these periods. We mndel the swnciatinns as a Markov chain using as .state information the ni&t recent AP visits. We-ran predict with high prnbahility (86%) the next AP with which B wireless client ! i l l assnociate. Also, there ace APs with a high percentage of user revisits. Such measurenients can benefit protwnls and algorithms that aim to inipmre the performance nf the wireless infrastructures hy lnad halancing, admission contrnl, and resource reservation acrnsc APs. 0-7803-8355
Our earlier work REF models the associations of each wireless client as a Markov-chain in which a state corresponds to an AP that the client has visited.
Analysis of wireless information locality and association patterns in a campus
IEEE INFOCOM 2004
IEEE INFOCOM 2004
Computer Science