In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data storage, and data analysis. For each phase, we introduce the general background, discuss the technical challenges, and review the latest advances. We finally examine the several representative applications of big data, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid. These discussions aim to provide a comprehensive overview and big-picture to readers of this exciting area. This survey is concluded with a discussion of open problems and future directions.

Big Data: A Survey

With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.

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Advances in cognitive radio networks: A survey

The Grid 2: Blueprint for a New Computing Infrastructure

The solid-state lighting is revolutionizing the indoor illumination. Current incandescent and fluorescent lamps are being replaced by the LEDs at a rapid pace. Apart from extremely high energy efficiency, the LEDs have other advantages such as longer lifespan, lower heat generation, and improved color rendering without using harmful chemicals. One additional benefit of LEDs is that they are capable of switching to different light intensity at a very fast rate. This functionality has given rise to a novel communication technology (known as visible light communication—VLC) where LED luminaires can be used for high speed data transfer. This survey provides a technology overview and review of existing literature of visible light communication and sensing. This paper provides a detailed survey of 1) visible light communication system and characteristics of its various components such as transmitter and receiver; 2) physical layer properties of visible light communication channel, modulation methods, and MIMO techniques; 3) medium access techniques; 4) system design and programmable platforms; and 5) visible light sensing and application such as indoor localization, gesture recognition, screen-camera communication, and vehicular networking. We also outline important challenges that need to be addressed in order to design high-speed mobile networks using visible light communication.

Visible Light Communication, Networking, and Sensing: A Survey, Potential and Challenges

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Art of electronics

We present a new visible light communication (VLC) primitive: VLC in the dark, where the communication sustains even when the LED light appears dark. We achieve the goal by reducing the duty cycle of the light source to an extremely low level (0.0019%) such that the illuminance is imperceptible to human eyes and yet can still be sensed by photodiodes to decode data. VLC in the dark consumes much lower energy than the conventional VLC links and thus is appealing for enabling VLC uplink or communication among Internet-of-Things devices with tight energy budget. We build a preliminary prototype to demonstrate its feasibility. Our current single link achieves 190.7 bps data rate with 46.8 microwatts power consumption at the LED.

Poster: Visible Light Communication in the Dark

We present HiLight, a new form of screen-camera communication without the need of any coded images (e.g. barcodes) for off-the-shelf smart devices. HiLight hides information underlying any images shown on a LED or an OLED screen, so that camera-equipped smart devices can fetch the information by turning their cameras to the screen. HiLight achieves this by leveraging the orthogonal transparency (alpha) channel, a well-known concept in computer graphics, to embed bits into pixel translucency changes without the need of modifying pixel color values. We demonstrated HiLight's feasibility using smartphones. By offering an unobtrusive, flexible, and lightweight communication channel between screens and cameras, HiLight opens up opportunities for new HCI and context-aware applications to emerge, e.g. smart glass communicates with screens for additional personalized information to realize augmented reality.

Poster: HiLight: hiding bits in pixel translucency changes

Locating underwater robots is fundamental for enabling important underwater applications. The current mainstream method requires a physical infrastructure with relays on the water surface, which is largely ad-hoc, introduces a significant logistical overhead, and entails limited scalability. Our work, Sunflower, presents the first demonstration of wireless, 3D localization across the air-water interface - eliminating the need for additional infrastructure on the water surface. Specifically, we propose a laser-based sensing system to enable aerial drones to directly locate underwater robots. The Sunflower system consists of a queen and a worker component on a drone and each tracked underwater robot, respectively. To achieve robust sensing, key system elements include (1) a pinhole-based sensing mechanism to address the sensing skew at air-water boundary and determine the incident angle on the worker, (2) a novel optical-fiber sensing ring to sense weak retroreflected light, (3) a laser-optimized backscatter communication design that exploits laser polarization to maximize retroreflected energy, and (4) the necessary models and algorithms for underwater sensing. Real-world experiments demonstrate that our Sunflower system achieves average localization error of 9.7 cm with ranges up to 3.8 m and is robust against ambient light interference and wave conditions.

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Sunflower: locating underwater robots from the air

Rate adaptation, as a challenging issue for wireless network design, has been an active research topic for years. Existing schemes either assume perfect channel information, or conduct rate adaptation in a black box way, hence can not achieve desirable performance. In this paper, we propose a novel scheme called correlation based rate adaptation (CORA) to address the rate adjustment problem. Unlike previous schemes, CORA splits rate into more atomic components and adjusts them according to the correlation between rate adaptation actions and transmission results. We use IEEE 802.11n as the context for CORA design, where transmission mode has been expanded to spatial dimension in addition to the usual modulation and convolution coding mechanisms. Performance evaluation shows that CORA can conduct rate adaptation in a more logical way and significantly outperform the comparison scheme.

Correlation Based Rate Adaptation via Insights from Incomplete Observations in 802.11 Networks

LiGaze is a low-cost, low-power approach to gaze tracking tailored to virtual reality (VR). It relies on a few low-cost photodiodes, eliminating the need for cameras and active infrared emitters. Reusing light from the VR screen, LiGaze leverages photodiodes around a VR lens to measure reflected screen light in different directions. It then infers gaze direction by exploiting the pupil's light absorption property. The core of LiGaze is to deal with screen light dynamics and extract changes in reflected light related to pupil movement. LiGaze infers a 3D gaze vector on the fly using a lightweight regression algorithm. Compared to the eye tracker of an existing VR headset (FOVE), LiGaze achieves 6.3° and 10.1° mean within-user and cross-user accuracy. Its sensing and computation consume 791 W in total and thus can be completely powered by a credit card-size solar cell harvesting energy from indoor lighting. LiGaze's simplicity and ultra-low power make it applicable in a wide range of VR headsets to better unleash VR's potential.

Xia Zhou

Papers

Poster: Visible Light Communication in the Dark

Poster: HiLight: hiding bits in pixel translucency changes

Sunflower: locating underwater robots from the air

Correlation Based Rate Adaptation via Insights from Incomplete Observations in 802.11 Networks

Ultra-Low-Power Gaze Tracking for Virtual Reality