Ruogu Zhou

Beyond co-existence: Exploiting WiFi white space for Zigbee performance assurance

Recent years have witnessed the increasing adoption of ZigBee technology for performance-sensitive applications such as wireless patient monitoring in hospitals. However, operating in unlicensed ISM bands, ZigBee devices often yield unpredictable throughput and packet delivery ratio due to the interference from ever increasing WiFi hotspots in 2.4 GHz band. Our empirical results show that, although WiFi traffic contains abundant white space, the existing coexistence mechanisms such as CSMA are surprisingly inadequate for exploiting it. In this paper, we propose a novel approach that enables ZigBee links to achieve assured performance in the presence of heavy WiFi interference. First, based on statistical analysis of real-life network traces, we present a Pareto model to accurately characterize the white space in WiFi traffic. Second, we analytically model the performance of a ZigBee link in the presence of WiFi interference. Third, based on the white space model and our analysis, we develop a new ZigBee frame control protocol called WISE, which can achieve desired trade-offs between link throughput and delivery ratio. Our extensive experiments on a testbed of 802.11 netbooks and 802.15.4 TelosB motes show that, in the presence of heavy WiFi interference, WISE achieves 4× and 2× performance gains over B-MAC and a recent reliable transmission protocol, respectively, while only incurring 10.9% and 39.5% of their overhead.

COBRA: color barcode streaming for smartphone systems

This paper presents COBRA - a visible light communication (VLC) system for off-the-shelf smartphones. COBRA encodes information into specially designed 2D color barcodes and streams them between screen and camera of smartphones. Due to the directionality and short range of visible light, COBRA can preserve user privacy and security in many near field communication scenarios such as opportunistic data exchange between smartphones. We develop a new 2D color barcode for COBRA that is optimized for streaming between small-size screen and low-speed camera of smartphones. COBRA adapts the size and layout of code blocks in streamed barcodes to deal with the significant image blur in mobile environments, and adopts new image processing techniques to achieve real-time barcode stream decoding. Our approach is evaluated through extensive experiments on Android smartphones.

ZiFi: wireless LAN discovery via ZigBee interference signatures

WiFi networks have enjoyed an unprecedent penetration rate in recent years. However, due to the limited coverage, existing WiFi infrastructure only provides intermittent connectivity for mobile users. Once leaving the current network coverage, WiFi clients must actively discover new WiFi access points (APs), which wastes the precious energy of mobile devices. Although several solutions have been proposed to address this issue, they either require significant modifications to existing network infrastructures or rely on context information that is not available in unknown environments. In this work, we develop a system called ZiFi that utilizes ZigBee radios to identify the existence of WiFi networks through unique interference signatures generated by WiFi beacons. We develop a new digital signal processing algorithm called Common Multiple Folding (CMF) that accurately amplifies periodic beacons in WiFi interference signals. ZiFi also adopts a constant false alarm rate (CFAR) detector that can minimize the false negative (FN) rate of WiFi beacon detection while satisfying the user-specified upper bound on false positive (FP) rate. We have implemented ZiFi on two platforms, a Linux netbook integrating a TelosB mote through the USB interface, and a Nokia N73 smartphone integrating a ZigBee card through the miniSD interface. Our experiments show that, under typical settings, ZiFi can detect WiFi APs with high accuracy (<5% total FP and FN rate), short delay (~780 ms), and little computation overhead

Volcanic earthquake timing using wireless sensor networks

Recent years have witnessed pilot deployments of inexpensive wireless sensor networks (WSNs) for active volcano monitoring. This paper studies the problem of picking arrival times of primary waves (i.e., P-phases) received by seismic sensors, one of the most critical tasks in volcano monitoring. Two fundamental challenges must be addressed. First, it is virtually impossible to download the real-time high-frequency seismic data to a central station for P-phase picking due to limited wireless network bandwidth. Second, accurate P-phase picking is inherently computation-intensive, and is thus prohibitive for many low-power sensor platforms. To address these challenges, we propose a new P-phase picking approach for hierarchical volcano monitoring WSNs where a large number of inexpensive sensors are used to collect fine-grained, real-time seismic signals while a small number of powerful coordinator nodes process collected data and pick accurate P-phases. We develop a suite of new in-network signal processing algorithms for accurate P-phase picking, including lightweight signal pre-processing at sensors, sensor selection at coordinators as well as signal compression and reconstruction algorithms. Testbed experiments and extensive simulations based on real data collected from a volcano show that our approach achieves accurate P-phase picking while only 16% of the sensor data are transmitted.

ZiFind: Exploiting cross-technology interference signatures for energy-efficient indoor localization

Indoor localization becomes increasingly important as context-aware applications gain popularity in mobile users. A promising approach for indoor localization is to leverage the pervasive WiFi infrastructure via fingerprinting-based inference. However, a WiFi device must frequently scan for WiFi signals during localization, leading to high power consumption. Moreover, switching to the scanning mode introduces inevitable disruptions to data communication of WiFi interface. This paper presents a new indoor localization system called ZiFind that exploits the cross-technology interference in the unlicensed 2.4 GHz frequency spectrum. ZiFind utilizes low-power ZigBee interface to collect WiFi interference signals and adopts digital signal processing techniques to extract unique signatures as fingerprints for localization. To deal with the noise in the fingerprints, we design a new learning algorithm called R-KNN that can improve the accuracy of localization by assigning different weights to fingerprint features according to their importance. We implement ZiFind on TelosB motes and evaluate its performance through extensive experiments in a 16,000 ft2 office building floor consisting of 28 rooms. Our results show that ZiFind leads to significant power saving compared with existing approaches based on WiFi interface, and yields satisfactory localization accuracy in a range of realistic settings.

Exploiting FM radio data system for adaptive clock calibration in sensor networks

Clock synchronization is critical for Wireless Sensor Networks (WSNs) due to the need of inter-node coordination and collaborative information processing. Although many message passing protocols can achieve satisfactory clock synchronization accuracy, they incur prohibitively high overhead when the network scales to more than tens of nodes. An alternative approach is to take advantage of the global time reference induced by existing infrastructures including GPS, timekeeping radio stations, or power grid. However, high power consumption and geographic constraints present them from being widely adopted in WSNs. In this paper, we propose ROCS, a new clock synchronization approach exploiting the Radio Data System (RDS) of FM radios. First, we design a new hardware FM receiver that can extract a periodic pulse from FM broadcasts, referred to as RDS clock. We then conduct a large-scale measurement study of RDS clock in our lab for a period of six days and on a vehicle driving through a metropolitan area of over 40

Nemo: a high-fidelity noninvasive power meter system for wireless sensor networks

km^2

nShield: a noninvasive NFC security system for mobiledevices

. Our results show that RDS clock is highly stable and hence is a viable means to calibrate the clocks of large-scale city-wide sensor networks. To reduce the high power consumption of FM receiver, ROCS intelligently predicts the time error due to drift, and adaptively calibrates the native clock via the RDS clock. We implement ROCS in TinyOS on our hardware FM receiver and a TelosB-compatible WSN platform. Our extensive experiments using a 12-node testbed and our driving measurement traces show that ROCS achieves accurate and precise clock synchronization with low power consumption.

Spatiotemporal Aquatic Field Reconstruction Using Robotic Sensor Swarm

In this paper, we present the design and implementation of Nemo - a practical in situ power metering system for wireless sensor networks. Nemo features a new circuit design called shunt resistor switch that can dynamically adjust the resistance of shunt resistors based on the current load. This allows Nemo to achieve a wide dynamic current range and high measurement accuracy. Nemo transmits real-time power measurements to the host node solely through the power line, by modulating the current load and the supply voltage. This feature leads to a noninvasive, plug & play design that allows Nemo to be easily installed on existing mote platforms without physical wiring or soldering. We have implemented a prototype of Nemo and conducted extensive experimental evaluation. Our results show that Nemo can transmit high-throughput measurement data to the host through voltage/current load modulation. Moreover, it has satisfactory measurement fidelity over a wide range of operating conditions. In particular, Nemo yields a dynamic measurement range of 250,000:1, which is 2.5X and 7X that of two state-of-the-art sensor network power meter systems, while only incurring an average measurement error of 1.34%. We also use a case study to demonstrate that Nemo is able to track the highly dynamic sleep current consumption of TelosB motes, which has important implications for the design of low duty-cycle sensor networks that operate in dynamic environments.

ZiFi: Exploiting Cross-Technology Interference Signatures for Wireless LAN Discovery

The Near Field Communication (NFC) technology is gaining increasing popularity among mobile users. However, as a relatively new and developing technology, NFC may also introduce security threats that make mobile devices vulnerable to various malicious attacks. This work presents the first system study on the feasibility of and defense again passive NFC eavesdropping. Our experiments show that commodity NFC-enabled mobile devices can be eavesdropped from up to 240 cm away, which is at least an order of magnitude of the intended NFC communication distance. This finding challenges the general perception that NFC is largely immune to eavesdropping because of its short working range. We then present the design of a hardware security system called nShield. With a small form factor, nShield can be attached to the back of mobile devices to attenuate the signal strength against passive eavesdropping. At the same time, the absorbed RF energy is scavenged by nShield for its perpetual operation. nShield intelligently determines the right attenuation level that is just enough to sustain reliable data communication. We implement a prototype of nShield, and evaluate its performance via extensive experiments. Our results show that nShield has low power consumption (23 uW), can harvest significant amount of power (55 mW), and adaptively attenuates the signal strength of NFC in a variety of realistic settings, while only introducing insignificant delay (up to 2.2 s).