Jihoon Ryoo

Geo-fencing: geographical-fencing based energy-aware proactive framework for mobile devices

Location-based services (LBSs) are often based on an area or place as opposed to an accurate determination of the precise location. However, current mobile software frameworks are geared towards using specific hardware devices (e.g., GPS or 3G or WiFi interfaces) for as precise localization as possible using that device, often at the cost of a significant energy drain. Further, often the location information is not returned promptly enough. To address this problem, we design a framework for mobile devices, called Geo-fencing. The proposed framework is based on the observation that users move from one place to another and then stay at that place for a while. These places can be, for example, airports, shopping centers, home, offices and so on. Geo-fencing defines such places as geographic areas bounded by polygons. It assumes people simply move from fence to fence and stay inside fences for a while. The framework is coordinated with available communication chips and sensors based on their energy usage and accuracy provided. The essential goal is to determine when users check in or out of fences in an energy effiecient fashion so that appropriate LBS can be triggered. Windows based smartphones are used to prototype Geo-fencing. Validations are conducted with the resulting traces of outdoor and indoor activities of several users for several months. The results show that Geo-fencing provides an effective framework for use with LBSs with a significant energy saving for mobile devices.

Design and implementation of an end-to-end architecture for 3.5 GHz shared spectrum

The paradigm of shared spectrum that allows spectrum bands that are underutilized by primary owners to be exploited opportunistically by secondary devices has been a subject of intense research in recent years. The 2008 FCC rule-making allowing unlicensed use of underutilized DTV white space represented the first step in that direction and elicited similar efforts in other countries. The 2012 PCAST report [5] in the U.S. pushed this new trend further by advocating shared use of 1000 MHz of federal government spectrum with commercial systems and set the goal to release 500 MHz of spectrum by 2022. As a first step towards this goal, the FCC targeted 3550-3700 MHz band used primarily by naval radars and fixed satellite station for release. As of writing of this paper, the FCC has announced the first set of rules for this band to enable deployment of low-powered network technologies like small cells. The proposed rules require a Spectrum Access System (SAS), akin to a TV Database (TVDB) to implement an innovative three-tiered spectrum management system - dynamic incumbents in the top tier, Priority Access License (PAL) users in the second tier and Generalized Authorized Access (GAA) users in the third tier. Realizing this vision requires a new end-to-end architecture, component protocols and novel radio systems. Our paper represents a step in this direction. Specifically, we present our candidate architecture and its end-to-end implementation that includes a scalable SAS to activate dynamic exclusion zones for incumbent protection, manage primary/secondary devices and dynamically assign spectrum. We present a new protocol Protocol for Tiered Access to Shared Spectrum (PTASS) for transactions between network entities in the architecture. We also describe in detail our prototype end-to-end 3.5 GHz LTE/Wi-Fi testbed. To the best of our knowledge, this is the first paper about the 3.5 GHz shared spectrum access system and the first end-to-end trial of a live 3.5 GHz wireless communications in practice.

Multi-sector multi-range control for self-organizing wireless networks

In this paper, we propose a distributed multi-sector multi-range (MSMR) control algorithm for supporting self-organizing wireless networks. The algorithm enables us to reduce the unnecessary coverage with fine-tuned range control and also to increase the network-wide capacity with enhanced spatial reusability. The proposed algorithm discovers neighboring nodes within the maximum transmission range at every node, divides its transmission area into multiple non-overlapping angular sectors of a given degree, chooses the home sector for each neighboring node according to its relative position, and constructs a spanning subgraph per sector by determining appropriate transmission range to maintain connectivity. Since the range control influences on network connectivity directly, we prove in the first place that the proposed algorithm preserves both network-wide and local connectivity as far as both connectivity exist in the network that uses the maximum transmission range. In order to investigate the performance of the proposed algorithm, we implemented it in the ns-2 simulator, and performed an extensive set of simulation study in comparison with other transmission range control schemes. The simulation results indicate that the proposed scheme is superior to other schemes with respect to the network-wide throughput and its normalized value per energy in various simulation configurations. In specific, the algorithm achieves minimally one order and maximally two orders of magnitude improvement in those performance evaluations. The improvement becomes more salient as the number of nodes increases and is immune to traffic type, network size, node distribution, or node density.

Phase-based Ranging of RFID Tags with Applications to Shopping Cart Localization

In this work, we investigate the problem of localizing RFID tags using a ranging method used in frequency-modulated radars. The idea is to exploit the phase change of the tag response due to frequency changes that normally happen as the RFID reader frequency hops. We demonstrate the general feasibility of this technique in ranging standard RFID tags using commodity readers. We then use it for a localization application - localizing shopping carts in supermarket aisles. We show that the ranging and localization accuracies are very good (median errors 5cm and 10cm respectively) even at distances over 4m making the technique competitive with existing techniques that require more complex set up.

Link-Aware Reconfigurable Point-to-Point Video Streaming for Mobile Devices

Even though people of all social standings use current mobile devices in the wide spectrum of purpose from entertainment tools to communication means, some issues with real-time video streaming in hostile wireless environment still exist. In this article, we introduce CoSA, a link-aware real-time video streaming system for mobile devices. The proposed system utilizes a 3D camera to distinguish the region of importance (ROI) and non-ROI region within the video frame. Based on the link-state feedback from the receiver, the proposed system allocates a higher bandwidth for the region that is classified as ROI and a lower bandwidth for non-ROI in the video stream by reducing the videos bit rate. We implemented CoSA in a real test-bed where the IEEE 802.11 is employed as a medium for wireless networking. Furthermore, we verified the effectiveness of the proposed system by conducting a thorough empirical study. The results indicate that the proposed system enables real-time video streaming while maintaining a consistent visual quality by dynamically reconfiguring video coding parameters according to the link quality.

CoSA: Adaptive link-aware real-time streaming for mobile devices

Programmable wireless devices which can perceive the current radio environment, decide available spectra, and dynamically change the radio access method, and networking protocols have been proposed to improve spectrum usage, interference mitigation, and connectivity. However, these transitions are currently lacking at upper layers. In this paper, we propose an upper layer cognitive system beyond channel sensing effectiveness and spectrum utilization achieved in adjusting PHY and MAC parameter settings. The proposed cognitive video streaming system achieves end-to-end goals at an upper video layer: quality of experience, service continuity, and survivability. Based on the link state of the receiver, the proposed system identifies areas of importance in the image stream, allocates higher bandwidth for the important areas compared to the other areas which is adjusted to use the less bandwidth with CoSA encoder and decoder, and receive the link state feedback from the receiver. To further understand the CoSAs benefit, we implemented two real test-beds for the cognitive video streaming system where the one uses conventional IEEE 802.11 networking technologies and the other employs a software defined radio platform, and performed a performance evaluation study in order to see the effectiveness of the proposed scheme. The results indicate that the proposed system can dynamically change actual data rates according to SINR feedback, which results in at least 180% improvement of transmission time compared to conventional method, while maintaining PSNR range between 30 to 40 dB with eminently reduced data size.

Sequential Monte Carlo Filtering for Location Estimation in Indoor Wireless Environments

In this paper, we propose a distributed, infrastructure-free algorithm for supporting self-localization and location-tracking of portable devices in home networks that do not rely on any positioning infrastructure, such as GPS (Global Positioning System). The proposed algorithm employs the received signal strength (RSS) to estimate the current position of each portable device and then elaborates the position with the box-based sequential Monte Carlo (BSMC) method. Simulation results indicate that the proposed algorithm is superior to the well-received Centroid algorithm [1] in terms of the distance estimation error.

WiSDom: A model-driven solitary death prevention system based on WiFi signals and real-time supervised training

A primary concern of many elders is ‘solitary death,’ being found as a rancid corpse long after they had passed away. In numerous cases, bodies are left unattended for days, months, or even years. These unfortunate cases have increased every year and have become a major social problem in many nations. Current warning systems utilize sensors or smartwatches, which are often costly, ineffective, and uncomfortable. This paper proposes WiSDom, a model-driven solitary death prevention system based on WiFi signals and real-time supervised training. The proposed methodology utilizes WiFis Channel State Information (CSI) for the primary activity identification estimation, represents the system by a discrete event state transition model, maps the estimated activities into the external events of the model, validates its estimation with the forthcoming events, and labels the validated samples for the supervised training of its clustering algorithm in real-time closed-loop. Through the experimental results, we show that the system effectively warns emergency cases and swiftly detects fatal situations.

Proactive searching period determination on singular radio mobile devices

Mobile devices with a singular radio cannot avoid the connection-off period when they move around in different transmission ranges of neighboring devices. In order to minimize the connection-off duration on singular radio mobile devices, we propose the Proactive Searching-Period Determination (PSPD) algorithm, which determines an optimal period for information exchange among neighboring nodes in the presence of mobile nodes. In order to verify the effectiveness of the PSPD, we carried out a simulation study with ns-2. The simulation results shows that the proposed algorithm correctly determines an optimal period and minimizes the connection-off duration for mobile nodes.