Comparing Mobility and Predictability of VoIP and WLAN Traces

How can we obtain realistic mobility models? This has been a question that many researchers have attempted to answer, mostly by analyzing existing WLAN traces. But in the future, will user on-line behavior change with the introduction of new mobile services and devices? We aim to investigate this issue in our study. In this paper, we analyze the mobility of a subset of users different than the general WLAN users; the VoIP users. These users are often mobile while online and their devices are always ‘on’. We conjecture that their mobility is captured by the traces better than that of the WLAN users, and we expect them to be highly mobile users representing a trend for future mobile users. To that extent, we contrast the mobility of the VoIP, WLAN users, and three carefully selected sets of users across various metrics. We find that the fraction of time a VoIP user spends at a given AP is lower than WLAN users, indicating that the VoIP users are indeed more mobile than WLAN users. Also, the average and median number of access points visited for VoIP users are 4 to 8 times larger than that of the WLAN users. VoIP users cover a larger area range than WLAN users, indicating that VoIP users are physically more mobile. These findings point to significant difference in mobility characteristics between VoIP users and average WLAN users (commonly used for mobility modeling). In order to examine whether this sharp contrast in mobility affects mobile networking protocols, we compare the performance of different classes of predictors across these different sets of traces. In particular, we evaluate the Markov O(1), O(2), O(3) and the LZ predictors. To our surprise, we find that the average prediction rate is over 60% for general WLAN traces while the prediction success rate drops below 25% for VoIP traces. Lessons learned in our study strongly suggest that both mobility modeling and location prediction should be re-visited in the context of future highly mobile users and devices. Keywords-VoIP; WLAN; mobility; wireless traces; location prediction