Towards new methods for mobility data gathering: content, sources, incentives

Over the past decade, huge amounts of work has been done in mobile and opportunistic networking research. Unfortunately, much of this has had little impact as the results have not been applicable to reality, due to incorrect assumptions and models used in the design and evaluation of the systems. In this paper, we outline some of the problems of the assumptions of early research in the field, and provide a survey of some initial work that has started to take place to alleviate this through more realistic modelling and measurements of real systems. We do note that there is still much work to be done in this area, and then go on to identify some important properties of the network that must be studied further. We identify the types of data that are important to measure, and also give some guidelines on finding existing and potentially new sources for such data and incentivizing the holders of the data to share it

Evaluating Mobility Pattern Space Routing for DTNs

Because a delay tolerant network (DTN) can often be partitioned, the problem of routing is very challenging. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high-dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and the large scale evaluation of this routing scheme in the context of ambient networking by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visit of nodes for each possible location. We show that the MobySpace can achieve good performance compared to that of the other algorithms we implemented, especially when we perform routing on the nodes that have a high connection time. We determine that the degree of homogeneity of mobility patterns of nodes has a high impact on routing. And finally, we study the ability of nodes to learn their own mobility patterns.Comment: IEEE INFOCOM 2006 preprin

Understanding the WiFi usage of university students

In this work, we analyze the use of a WiFi network deployed in a large-scale technical university. To this extent, we leverage three weeks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then, we search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely, we answer the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results

WLAN PLANNING AND CONCEPTUAL DESIGN IN UNIVERSITI TEKNOLOGI PETRONAS

Wireless Local Area Network (WLAN) is one of the new networking environments where it supports the mobility of the network user without being encumbered by the cable existence. Since the current Local Area Network (LAN) in Universiti Teknologi PETRONAS (UTP) is fairly growth and the performance reliability is good shifting the current setup to WLAN is locally accepted. This will benefit all the UTP users including students, respective lecturers, and beneficial for administration line of staff. The current planning and setup will cover certain stages in order to build a high reliability and best performance of the WLAN environment. Data transmission and signal strength for the area is fairly surveyed in order to result the best performance and ability to transmit data in bit per second required. Research and questionnaire have also been done throughout the UTP students, IT Media Services Executives, respective IT Consultants from KLCCB Project Berhad in order to determine the best design concept to be applied in UTP campus and to determine the best place for WLAN to be implemented. Usage models are also needed to be determined in order to support the activity that will be in the WLAN environment. The conceptual design of WLAN environment will cater the area of the student residential including the Student Center, cafeteria, and residential buildings for Village 3,4 and 5. With help of this design it will be easier to determine the location of all the devices such as the wireless access point (AP) and security access point (SAP) as to roam the signal coverage and to secure the signal for data transmission. The technology use in data transmission is also being covered in this research paper, which includes the Spread Spectrum LAN. As to meet the problem statement requirement to ensure the system meets the budgeted cost, the author came out with the budgeting plan for all the devices allocated for the WLAN setup. The WLAN planning and setup in UTP research will help the UTP management in getting the grasp idea how to setup WLAN environment in UTP campus and to compliance with the current LAN setup and to secure the cost and budgeting for all devices related

IMPACT: Investigation of Mobile-user Patterns Across University Campuses using WLAN Trace Analysis

We conduct the most comprehensive study of WLAN traces to date. Measurements collected from four major university campuses are analyzed with the aim of developing fundamental understanding of realistic user behavior in wireless networks. Both individual user and inter-node (group) behaviors are investigated and two classes of metrics are devised to capture the underlying structure of such behaviors. For individual user behavior we observe distinct patterns in which most users are 'on' for a small fraction of the time, the number of access points visited is very small and the overall on-line user mobility is quite low. We clearly identify categories of heavy and light users. In general, users exhibit high degree of similarity over days and weeks. For group behavior, we define metrics for encounter patterns and friendship. Surprisingly, we find that a user, on average, encounters less than 6% of the network user population within a month, and that encounter and friendship relations are highly asymmetric. We establish that number of encounters follows a biPareto distribution, while friendship indexes follow an exponential distribution. We capture the encounter graph using a small world model, the characteristics of which reach steady state after only one day. We hope for our study to have a great impact on realistic modeling of network usage and mobility patterns in wireless networks.Comment: 16 pages, 31 figure