We collected mobility traces of 84,208 avatars spanning 22 regions over two months in Second Life, a popular networked virtual environment. We analyzed the traces to characterize the dynamics of the avatars mobility and behavior, both temporally and spatially. We discuss the implications of the our findings to the design o f peer-to-peer networked virtual environments, interest management, mobility modeling of avatars, server load balancing and zone partitioning, client-side caching, and prefetching.
Most recently, La and Pietro have independently conducted a similar study on mobility in Second Life @cite_17 . Their study, however, focuses on metrics relevant to mobile communications, such as graph theoretic properties of line-of-sight networks formed by the avatars, travel length and time of avatars, and contact opportunities among avatars. Their goal is to use the mobility traces of avatars to model human mobility for applications related to wireless and delay-tolerant networks. On the other hand, we focus on metrics that are of interest to systems design of NVEs.
@cite_17
2953210768 2145517691 2092003045 2520036704
In this work we present a measurement study of user mobility in Second Life. We first discuss different techniques to collect user traces and then focus on results obtained using a crawler that we built. Tempted by the question whether our methodology could provide similar results to those obtained in real-world experiments, we study the statistical distribution of user contacts and show that from a qualitative point of view user mobility in Second Life presents similar traits to those of real humans. We further push our analysis to line of sight networks that emerge from user interaction and show that they are highly clustered. Lastly, we focus on the spatial properties of user movements and observe that users in Second Life revolve around several point of interests traveling in general short distances. Besides our findings, the traces collected in this work can be very useful for trace-driven simulations of communication schemes in delay tolerant networks and their performance evaluation. We examine the fundamental properties that determine the basic performance metrics for opportunistic communications. We first consider the distribution of inter-contact times between mobile devices. Using a diverse set of measured mobility traces, we find as an invariant property that there is a characteristic time, order of half a day, beyond which the distribution decays exponentially. Up to this value, the distribution in many cases follows a power law, as shown in recent work. This powerlaw finding was previously used to support the hypothesis that inter-contact time has a power law tail, and that common mobility models are not adequate. However, we observe that the time scale of interest for opportunistic forwarding may be of the same order as the characteristic time, and thus the exponential tail is important. We further show that already simple models such as random walk and random way point can exhibit the same dichotomy in the distribution of inter-contact time ascin empirical traces. Finally, we perform an extensive analysis of several properties of human mobility patterns across several dimensions, and we present empirical evidence that the return time of a mobile device to its favorite location site may already explain the observed dichotomy. Our findings suggest that existing results on the performance of forwarding schemes basedon power-law tails might be overly pessimistic. We examine the fundamental properties that determine the basic performance metrics for opportunistic communications. We first consider the distribution of intercontact times between mobile devices. Using a diverse set of measured mobility traces, we find as an invariant property that there is a characteristic time, order of half a day, beyond which the distribution decays exponentially. Up to this value, the distribution in many cases follows a power law, as shown in recent work. This power law finding was previously used to support the hypothesis that intercontact time has a power law tail, and that common mobility models are not adequate. However, we observe that the timescale of interest for opportunistic forwarding may be of the same order as the characteristic time, and thus, the exponential tail is important. We further show that already simple models such as random walk and random waypoint can exhibit the same dichotomy in the distribution of intercontact time as in empirical traces. Finally, we perform an extensive analysis of several properties of human mobility patterns across several dimensions, and we present empirical evidence that the return time of a mobile device to its favorite location site may already explain the observed dichotomy. Our findings suggest that existing results on the performance of forwarding schemes based on power law tails might be overly pessimistic. Short range vehicle to vehicle and device to device communications are of growing interest due to their utility for vehicular safety and infotainment applications as well as for improving the capacity of cellular networks. These mobile systems are characterized by ephemeral, stochastic links. We consider a fundamental problem in this domain -- how to maximize the amount of useful content downloaded by a client from a server over an encounter that lasts a random amount of time. We assume that the distribution of link duration is known or estimated based on historical as well as real-time measurements. We present MERLIN (Maximum Expected download over Random LINks), a single-phase file request protocol that is provably optimal. We evaluate MERLIN comprehensively via simulations based on both ideal link duration distributions as well as empirical distributions obtained from real vehicular mobility traces (from Taxis in Shanghai and Buses in Chicago). We also present two Contiki OS-based implementations of MERLIN (with local and remote calculations) evaluated on the Tmote Sky wireless embedded platform.