Seongik Hong

On the levy-walk nature of human mobility

We report that human walk patterns contain statistically similar features observed in Levy walks. These features include heavy-tail flight and pause-time distributions and the super-diffusive nature of mobility. Human walks are not random walks, but it is surprising that the patterns of human walks and Levy walks contain some statistical similarity. Our study is based on 226 daily GPS traces collected from 101 volunteers in five different outdoor sites. The heavy-tail flight distribution of human mobility induces the super-diffusivity of travel, but up to 30 min to 1 h due to the boundary effect of peoples daily movement, which is caused by the tendency of people to move within a predefined (also confined) area of daily activities. These tendencies are not captured in common mobility models such as random way point (RWP). To evaluate the impact of these tendencies on the performance of mobile networks, we construct a simple truncated Levy walk mobility (TLW) model that emulates the statistical features observed in our analysis and under which we measure the performance of routing protocols in delay-tolerant networks (DTNs) and mobile ad hoc networks (MANETs). The results indicate the following. Higher diffusivity induces shorter intercontact times in DTN and shorter path durations with higher success probability in MANET. The diffusivity of TLW is in between those of RWP and Brownian motion (BM). Therefore, the routing performance under RWP as commonly used in mobile network studies and tends to be overestimated for DTNs and underestimated for MANETs compared to the performance under TLW.

SLAW: A New Mobility Model for Human Walks

Simulating human mobility is important in mobile networks because many mobile devices are either attached to or controlled by humans and it is very hard to deploy real mobile networks whose size is controllably scalable for performance evaluation. Lately various measurement studies of human walk traces have discovered several significant statistical patterns of human mobility. Namely these include truncated power-law distributions of flights, pause-times and inter-contact times, fractal way-points, and heterogeneously defined areas of individual mobility. Unfortunately, none of existing mobility models effectively captures all of these features. This paper presents a new mobility model called SLAW (self-similar least action walk) that can produce synthetic walk traces containing all these features. This is by far the first such model. Our performance study using using SLAW generated traces indicates that SLAW is effective in representing social contexts present among people sharing common interests or those in a single community such as university campus, companies and theme parks. The social contexts are typically common gathering places where most people visit during their daily lives such as student unions, dormitory, street malls and restaurants. SLAW expresses the mobility patterns involving these contexts by fractal way points and heavy-tail flights on top of the way points. We verify through simulation that SLAW brings out the unique performance features of various mobile network routing protocols.

On the Levy-Walk Nature of Human Mobility

We report that human walks performed in outdoor settings of tens of kilometers resemble a truncated form of Levy walks commonly observed in animals such as monkeys, birds and jackals. Our study is based on about one thousand hours of GPS traces involving 44 volunteers in various outdoor settings including two different college campuses, a metropolitan area, a theme park and a state fair. This paper shows that many statistical features of human walks follow truncated power-law, showing evidence of scale-freedom and do not conform to the central limit theorem. These traits are similar to those of Levy walks. It is conjectured that the truncation, which makes the mobility deviate from pure Levy walks, comes from geographical constraints including walk boundary, physical obstructions and traffic. None of commonly used mobility models for mobile networks captures these properties. Based on these findings, we construct a simple Levy walk mobility model which is versatile enough in emulating diverse statistical patterns of human walks observed in our traces. The model is also used to recreate similar power-law inter-contact time distributions observed in previous human mobility studies. Our network simulation indicates that the Levy walk features are important in characterizing the performance of mobile network routing performance.

SLAW: self-similar least-action human walk

Many empirical studies of human walks have reported that there exist fundamental statistical features commonly appearing in mobility traces taken in various mobility settings. These include: 1) heavy-tail flight and pause-time distributions; 2) heterogeneously bounded mobility areas of individuals; and 3) truncated power-law intercontact times. This paper reports two additional such features: a) The destinations of people (or we say waypoints) are dispersed in a self-similar manner; and b) people are more likely to choose a destination closer to its current waypoint. These features are known to be influential to the performance of human-assisted mobility networks. The main contribution of this paper is to present a mobility model called Self-similar Least-Action Walk (SLAW) that can produce synthetic mobility traces containing all the five statistical features in various mobility settings including user-created virtual ones for which no empirical information is available. Creating synthetic traces for virtual environments is important for the performance evaluation of mobile networks as network designers test their networks in many diverse network settings. A performance study of mobile routing protocols on top of synthetic traces created by SLAW shows that SLAW brings out the unique performance features of various routing protocols.

Routing performance analysis of human-driven delay tolerant networks using the truncated levy walk model

The routing performance of delay tolerant networks (DTN) is highly correlated with the distribution of inter-contact times (ICT), the time period between two successive contacts of the same two mobile nodes. As humans are often carriers of mobile communication devices, studying the patterns of human mobility is an essential tool to understand the performance of DTN protocols. From measurement studies of human contact behaviors, we find that their distributions closely resemble a form of power-law distributions called truncated Pareto. Human walk traces has a dichotomy distribution pattern of ICT; it has a power-law tendency up to some time, and decays exponentially after that time. Truncated Pareto distributions offer a simple yet cohesive mathematical model to express this dichotomy in the measured data. Using the residual and relaxation time theory [17] [4], we apply truncated Pareto distributions to quantify the performance of opportunistic routing in DTN. We further show that Truncated Levy walk (TLW) mobility model [22] commonly used in biology to describe the foraging patterns of animals [25], provide the same truncated power-law ICT distributions as observed from the empirical data, especially when mobility is confined within a finite area. This result confirms our recent finding that human walks contain similar statistical characteristics as Levy walks [22].

DTN routing strategies using optimal search patterns

Biologists have long shown that the mobility patterns of many foraging animals and insects are similar to Levy walks and Levy walks are an optimal search strategy when target objects (i.e., food sources) are sparse and their locations are not known in advance. In this paper, we apply Levy walk patterns to routing in delay tolerant networks (DTN). In DTNs, message forwarding nodes often do not have full information about the whereabout of message destinations. Using the optimality property of Levy walks, we devise two styles of routing strategies. One is an active strategy using message ferries (MF) where the movement of MFs can be controlled to have a Levy walk pattern in order for them to maximize the opportunity of meeting the destinations and the other is a passive strategy in which the movement of nodes cannot be controlled, but messages are forwarded in such a manner that their forwarding patterns mimic the Levy walk patterns. We show through simulation that (1) both strategies are very effective when knowledge about destinations (i.e., contact history, trajectory or locations of destinations) is highly limited and (2) they complement existing utility-based routing which excels when such knowledge is available.

STEP: A spatio-temporal mobility model for humans walks

The movement of people is by-products of spatial and temporal correlations. People go to a place at a certain time with a purpose and they meet because they are in the same place at the same time. Extracting and representing the statistical features of spatio-temporal correlations inherent in human mobility is the goal of this paper. Most of the existing human mobility models focus on representing only the spatial features of human mobility (e.g., where and how they visit) and devote less attention to representing the temporal features (when they visit). This paper shows through GPS experiments simultaneously tracking the movement of about 200 students in two university campuses that many existing models cannot capture the temporal features and their correlations with the spatial features, and proposes a new mobility model called spatio-temporal mobility model (STEP) that aims to remedy this deficiency. The paper reports a work-in-progress for evaluating the performance of STEP and the other mobility models in representing inherent spatio-temporal features of human mobility such as the inter-contact times and diffusion speeds which are captured in the GPS experiments.

CCN networking architecture for mobile applications

We have proposed a CCN-based Virtual Private Community (VPC) service for content sharing as a prototype for Content-Centric Networking (CCN). A VPC is a hierarchical and closed user group which consumers themselves can easily create and manage on their devices. CCN is a new networking paradigm that was considered to bring significant advantages over current IP-based Internet. Their main idea was based on named data networking not the named hosts. CCN is known to have advantages of reducing congestion and latency by eliminating redundant data delivery, ensuring secure data delivery by content protection, improving delivery efficiency by utilizing multiple paths over IP-based networking paradigm. In this paper, in addition to the well-known properties of CCN listed above, we show that CCN-based networking architecture fits with community grouping solution such as VPC. Then, we describe how the communities are formed and existing applications run with the CCN VPC. We have implemented our CCN VPC on Android platforms to demonstrate the potential of user device oriented CCN applications.