Kyunghan Lee

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.

Mobile data offloading: how much can WiFi deliver?

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 97 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during a two-and-a-halfweek period in February 2010. Our trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100-s delays, the achievable gain is less than only 2%-3%, whereas with 1 h or longer deadlines, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in contrast to the substantial gain (20%-33%) reported by the existing work even for 100-s delayed transmission using traces taken from transit buses or war-driving. In addition, a distribution model-based simulator and a theoretical framework that enable analytical studies of the average performance of offloading are proposed. These tools are useful for network providers to obtain a rough estimate on the average performance of offloading for a given WiFi deployment condition.

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.

Tackling bufferbloat in 3G/4G networks

The problem of overbuffering in the current Internet (termed as bufferbloat) has drawn the attention of the research community in recent years. Cellular networks keep large buffers at base stations to smooth out the bursty data traffic over the time-varying channels and are hence apt to bufferbloat. However, despite their growing importance due to the boom of smart phones, we still lack a comprehensive study of bufferbloat in cellular networks and its impact on TCP performance. In this paper, we conducted extensive measurement of the 3G/4G networks of the four major U.S. carriers and the largest carrier in Korea. We revealed the severity of bufferbloat in current cellular networks and discovered some ad-hoc tricks adopted by smart phone vendors to mitigate its impact. Our experiments show that, due to their static nature, these ad-hoc solutions may result in performance degradation under various scenarios. Hence, a dynamic scheme which requires only receiver-side modification and can be easily deployed via over-the-air (OTA) updates is proposed. According to our extensive real-world tests, our proposal may reduce the latency experienced by TCP flows by 25% ~ 49% and increase TCP throughput by up to 51% in certain scenarios.

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.

Understanding bufferbloat in cellular networks

Bufferbloat is a prevalent problem in the Internet where excessive buffers incur long latency, substantial jitter and sub-optimal throughput. This work provides the first elaborative understanding of bufferbloat in cellular networks. We carry out extensive measurements in the 3G/4G networks of the four major U.S. carriers to gauge the impact of bufferbloat in the field. Due to the bufferbloat problem, several pitfalls of current TCP protocols have been proposed in this paper. We also discover a trick employed by smart phone vendors to mitigate the issue and point out the limitations of such ad-hoc solutions. Our measurement study is coupled with theoretical analysis using queuing models. Finally, we comprehensively discuss candidate solutions to this problem and argue for a TCP-based end-to-end solution.

Advertising cached contents in the control plane: Necessity and feasibility

A key feature of Information-Centric Networking architectures is universal caching where anyone can cache any content and users can obtain the content from anywhere as long as the content itself is intact. This powerful feature benefits the content providers, the Internet service providers (ISPs) as well as end users since the requested content can be fetched from the nearest cache who is able to satisfy the request. Hence, server load, redundant network traffic and fetch latency are all reduced. However, given the huge number of contents in the Internet and the rapid replacement of cached contents, designing a scalable routing protocol to reach the full potential of universal caching is very challenging. Previous proposal in [1] tackles the problem by only considering contents on original servers in the control plane and opportunistically exploring cached contents in the data plane via so-called forwarding strategy. In this paper we argue that, to unleash the full potential of Information-Centric Networking, cached contents should be taken into consideration in the control plane and propose a specific scheme to achieve that. We believe addressing cached contents in the control plane (even imperfectly) is more efficient than “guessing” them in the data plane.

FM-based indoor localization via automatic fingerprint DB construction and matching

We present ACMI, an FM-based indoor localization that does not require proactive site profiling. ACMI constructs the fingerprint database based on the pure estimation of indoor RSS distribution, where the signals transmitted from commercial FM radio stations are used. For this, ACMI makes use of our signal model harnessing public transmission information of FM stations in a combination with a floorplan of a building. Using the fingerprint database as the knowledge base, ACMI actively performs multi-level online signal matching to infer the current location of a mobile user. ACMI achieves good indoor localization accuracy even without site profiling efforts. We evaluate ACMI with extensive indoor experiments in 7 different locations with over 1,100 indoor spots. The results show that ACMI achieves up to 89% room identification and accuracy of 6m localization error on average using 8 FM broadcast signals.

Delay-capacity tradeoffs for mobile networks with Lévy walks and Lévy flights

This paper analytically derives the delay-capacity tradeoffs for Lévy mobility: Lévy walks and Lévy flights. Lévy mobility is a random walk with a power-law flight distribution. α is the power-law slope of the distribution and 0 < α ≤ 2. While in Lévy flight, each flight takes a constant flight time, in Lévy walk, it has a constant velocity which incurs strong spatio-temporal correlation as flight time depends on traveling distance. Lévy mobility is of special interest because it is known that Lévy mobility and human mobility share several common features including heavy-tail flight distributions. Humans highly influence the mobility of nodes (smartphones and cars) in real mobile networks as they carry or drive mobile nodes. Understanding the fundamental delay-capacity tradeoffs of Lévy mobility provides important insight into understanding the performance of real mobile networks. However, its power-law nature and strong spatio-temporal correlation make the scaling analysis non-trivial. This is in contrast to other random mobility models including Brownian motion, random waypoint and i.i.d. mobility which are amenable for a Markovian analysis. By exploiting the asymptotic characterization of the joint spatio-temporal probability density functions of Lévy models, the order of critical delay, the minimum delay required to achieve more throughput than Θ(1/√n) where n is the number of nodes in the network, is obtained. The results indicate that in Lévy walk, there is a phase transition that for 0 < α < 1, the critical delay is constantly Θ(n^1/2) and for 1 ≤ α ≤ 2, is Θ(n^α/2). In contrast, Lévy flight has critical delay Θ(n^α/2) for 0 < a ≤ 2.