Abstract Geo-localization and Location-aware Opportunistic Communication for Mobile Phones

Transcription

1 Abstract Geo-localization and Location-aware Opportunistic Communication for Mobile Phones by Kuldeep Yadav Department of Computer Science Indraprastha Institute of Information Technology, New Delhi Date: Approved: Dr. Vinayak Naik, Supervisor Dr. Pushpendra Singh, Co-supervisor Dr. Amarjeet Singh, Co-supervisor Prof. Murat Demirbas (SUNY Buffalo) Prof. Romit Roy Choudhury (UIUC) Prof. Sudip Mishra (IIT Kharagpur) An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science

2 in the Graduate School of Indraprastha Institute of Information Technology, New Delhi 2014 iv

3 Copyright 2014 by Kuldeep Yadav All rights reserved except the rights granted by the Creative Commons Attribution-Noncommercial Licence

4 Abstract Location-based mobile applications are steadily gaining popularity across the world. These applications require information about user s current location to access different kind of services. However, location-based applications have diverse set of requirements, some of them require location information intermittently such as local search, whereas other applications require continuous access to location information i.e. ones which need to infer high level information such as places and routes. Additionally, localization accuracy requirements are different across various locationbased services. For instance, navigation applications require high level of accuracy ( 10 meters) whereas sharing location with online social networks may suffice with an accuracy of hundreds of meters. There are mainly three different localization approaches which are used to estimate current user location using a mobile phone, i.e. Global Positioning System (GPS), WiFi-based, and GSM-based. These three different approaches differ in terms of localization accuracy, availability, and energy consumption. GPS and WiFi-based approaches provide fine grained localization accuracy but there are many phones, which do not have GPS and WiFi sensors (i.e. feature phones). It is predicted that for the at least next five years, over 50% of the phones will not have GPS. Apart from limited availability, GPS and WiFi-based approaches result in high energy consumption specially for the services which require continuous tracking of location information. Further, many cities in the world do not have a large scale Wi-Fi infrastructure, which is a sole requirement for all vi

5 WiFi-based approaches. GSM-based approaches (Cell ID-based) work on both feature phones as well as smartphones and energy-efficient as compared to GPS/WiFi. However, they require access to a comprehensive database of Cell IDs created using war-driving. Such a database either does not exist or have limited coverage in developing countries. In this thesis, we make the following contributions to enable energy-efficient geolocalization and location-aware communication on mobile phones: (1) We propose a novel Cell Broadcast (CBS) based localization system, which removes the necessity of war-driving or building a Cell ID database for GSM-based localization. Evaluation using self-collected real world traces show that the proposed approach provide good accuracy (nearly meters), which is sufficient for enabling many locationbased services on feature phones. We have developed several location-aware applications using CBS-based approach and combined it with existing techniques such as Cell ID and GPS for improving localization availability while minimizing energy consumption on smartphones. (2) We propose PlaceMap, a system to discover places and routes visited by mobile users based on only Cell ID information. Our system employs a novel graph-based clustering algorithm, which handles challenges such as fluctuating among Cell IDs on same place and segregate Cell IDs according to physical places. To provide better accuracy in place discovery, we design algorithm that uses an initial training of WiFi/GPS data to learn places and later use Cell ID data only. Our evaluations on two large scale mobility dataset collected in India and Switzerland show that PlaceMap can correctly discover nearly 80% of places as compared to baseline (GPS/WiFi). (3) We build and evaluate designs of two Cloud-enabled mobile systems, which facilitate opportunistic communication among co-located phones. These system are designed specifically for bandwidth constrained settings. One of them, MobiShare uses the Cloud for scalable content search and an encounter prediction framework to predict encounter time between content source vii

6 and requestor based on their mobility history. Second system, Unity finds social groups, who have similar interests and have frequent encounters to enable collaborative download of mutually interested content from the Internet. (4) We discover aggregated mobility and place visiting patterns of people in developing countries using one CDR (Call Detail Records) dataset collected in Ivory Coast and two finegrained location information datasets collected in India and Switzerland. We have compared these mobility patterns with existing studies for developed countries (US and Switzerland) and found several differences. One of the difference is that people in developing countries are less likely to travel long distance on weekends as compared to developed countries. With the fast evolution of hardware and software technologies for mobile phones, there has been a large gap created between capabilities of feature phones and smartphones. This thesis tries to fill that gap and provide practical and promising solutions to enable location-based services on both feature phones and smartphones using low energy location interfaces. viii