=== Mobility Traces === * [http://nile.cise.ufl.edu/MobiLib/USC_trace_intro.html MobiLib-USC: Traces from the USC wireless LAN] - 4500 users, 400 access points. 2005 * [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.79.617 IMPACT: Investigation of Mobile-user Patterns Across University Campuses using WLAN Trace Analysis] - analyzes 4 campus traces * [http://crawdad.cs.dartmouth.edu/meta.php?name=mit/reality MIT Reality trace] - 2005 * [http://crawdad.cs.dartmouth.edu/meta.php?name=nus/bluetooth Natl. Singapore U. trace] - 2007 * [http://crawdad.cs.dartmouth.edu/meta.php?name=cambridge/haggle Cambridge Haggle traces] - multiple traces from 2006 and 2009 * [http://crawdad.cs.dartmouth.edu/meta.php?name=epfl/mobility San Francisco taxicab traces] - 2009 * [http://wirelesslab.sjtu.edu.cn/ Shanghai Jiao Tong U. SUVNet traces] - Traffic GPS data from ~2000 taxis and N buses during 1 month in 2007 - [http://wirelesslab.sjtu.edu.cn/resource/publication/Conference/HZLLW10.pdf Paper] on mobility model extracted from trace Community Trace repositories: [http://crawdad.cs.dartmouth.edu/ CRAWDAD (Dartmouth)] [http://nile.cise.ufl.edu/MobiLib/ MobiLib (UFL)] === Mobility Models === * [http://nrlweb.cs.ucla.edu/publication/download/315/rpgm.pdf A Group Mobility Model for Ad Hoc Wireless Networks] - Hong et al., UCLA - 1999 * [http://onlinelibrary.wiley.com/doi/10.1002/wcm.72/pdf A Survey of Mobility Models for Ad Hoc Network Research] - Tracy Camp, Jeff Boleng, Vanessa Davies, 2002 * [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1497932 A Mobility Model Based on WLAN Traces and its Validation] - Tuduce et al., 2005 * [http://portal.acm.org/citation.cfm?doid=1134680.1134699 Building Realistic Mobility Models from Coarse-Grained Traces] - Yoon et al., MobiSys 2006 * [http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04215676 Modeling Time-Variant User Mobility in Wireless Mobile Networks] - Hsu et al., 2007. [http://nile.cise.ufl.edu/TVC_model/ Code] * [http://wirelesslab.sjtu.edu.cn/resource/publication/Conference/HZLLW10.pdf META: a Mobility Model of MEtropolitan TAxis Extracted from GPS Traces] - Huang et al., 2010 === Trends === * [http://www.cisco.com/en/US/netsol/ns827/networking_solutions_sub_solution.html Cisco Visual Network Index (VNI) Home] [http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns827/white_paper_c11-520862.html Global Mobile Data Traffic Forecast Update, 2010–2015] * 2010 mobile traffic starting to reflect the 1:20 skewed behavior long observed in fixed networks - '''top 1% clients generate ~20% of all traffic''' * Bottom 80% clients generated ~20% of overall 2010 mobile data traffic * [http://www.morganstanley.com/institutional/techresearch/pdfs/Internet_Trends_041210.pdf Morgan Stanley Report on 'Internet Trends' - 2010] === DNS Queries === * MIT DNS client-side traces - 3 traces 2000-01, 2 from MIT, 1 from Korea * [http://portal.acm.org/citation.cfm?id=505223 DNS Performance and Effectiveness of Caching] - Jung et al. - SIGCOMM 2001. * Domain name popularity - Zipf-like distribution with param=0.91 * Latency - median ~100ms, 90th%ile is ~400-1200ms * [http://www.cs.cornell.edu/People/egs/papers/codons-sigcomm.pdf CoDoNS] re-evaluated DNS perf. from PlanetLab nodes based on above trace: Latency mean/median/90th%ile = 382/39/337ms * Gatech DNS client-side traces - 75 diff locations, 21 countries, 2002 * [http://portal.acm.org/citation.cfm?id=637204 Diversity in DNS Performance Measures] - Liston et al., SIGCOMM'02 * Latency - varies, mean is between .95-2.31s, breakdown shows only ~20% of time spent to query root/gTLD * UCLA DNS local-resolver traces - 3 traces all during same 12 days, 2004 * [http://www.cs.colostate.edu/~massey/pubs/conf/massey_infocom06.pdf A Comparative Study of the DNS Design with DHT-Based Alternatives] - Pappas et al - INFOCOM'06 * Domain name popularity - combined Zipf param=0.93 * [http://www.caida.org/research/dns/roottraffic/ CAIDA DNS root server traces] - periodic simultaneous collections across all root servers * [http://www.caida.org/publications/papers/2008/root_internet/root_internet.pdf A Day at the Root of the Internet] - Castro et al. SIGCOMM CCR 2008 * 98% of queries are categorized as root pollution - including ~80% that are identical, repeated or resulting from not caching prior referrals * [http://www.caida.org/publications/papers/2010/understanding_dns_evolution/understanding_dns_evolution.pdf Understanding and preparing for DNS evolution] - comparative analysis across 2007-2009. Includes distribution of queries and query rates across client bins - useful to model client behavior. '''Very small % of clients generate most queries'''. Unfortunately, these heavy hitters are mostly sending invalid queries due to mis-configs, firewalls blocking responses, etc. === Web Site and Content Popularity === * [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=749260 Web Caching and Zipf-like Distributions: Evidence and Implications] - Breslau et al. INFOCOM'99 * Zipf-like distribution and no correlation between request frequency and response size or rate of change * [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.5143&rep=rep1&type=pdf On the universality of rank distributions of website popularity] - modified Zipf * [http://www.cs.cornell.edu/People/egs/papers/rsssurvey.pdf Client Behavior and Feed Characteristics of RSS, a Publish-Subscribe System for Web Micronews] - Liu et al. IMC'05 * Popularity of RSS feeds by hits is Zipf with param=1.37, Popularity by subscribers is Zipf with param=0.5 * Con: popularity derived from passive logs from univ. dept - small user base === Peer-to-Peer Traffic === * [http://portal.acm.org/citation.cfm?id=987234 Analyzing peer-to-peer traffic across large networks] - Sen et al. ToN 2004 * [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=990433&tag=1 Peer-to-peer architecture case study: Gnutella network] - Ripeanu, P2P Computing 2001 * [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.74.7773&rep=rep1&type=pdf A Measurement Study of Peer-to-Peer File Sharing Systems] - Saroiu et al. 2002