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 propose a compact noninvasive glucose monitoring system using polarized light, where a user simply needs to place her palm on the device for measuring her current glucose concentration level. The primary innovation of our system is the ability to minimize light scattering from the skin and extract weak changes in light polarization to estimate glucose concentration, all using low-cost hardware. Our system exploits multiple wavelengths and light intensity levels to mitigate the effect of user diversity and confounding factors (e.g., collagen and elastin in the dermis). It then infers glucose concentration using a generic learning model, thus no additional calibration is needed. We design and fabricate a compact (17 cm x 10 cm x 5 cm) and low-cost (i.e., r and p values of the Pearson correlation coefficients between our predicted glucose concentration and reference glucose concentration are 0.91 and 1.6 x 10-143, respectively. These errors are comparable with FDA-approved glucose sensors, which achieve ≈90% clinical accuracy with a 10% mean ARD.

Noninvasive glucose monitoring using polarized light

During recent years, research in smart cities and internet of the things has acquired a notable relevance. Current research is mainly focused on wireless sensor networks and data analysis. However, it is still necessary to provide new solutions for social problems based on mobile intelligent devices connected to the city. Mobility is a key factor for social environments in smart cities in which humans wear intelligent devices that can also be installed in vehicles and continuously vary their positions in the city. Social computing envisions a new kind of computation where humans and machines collaborate to compute and resolve a social problem. The role of mobile intelligent actors in social computing is still a challenge and require new solutions. In this paper, we present a multi-agent architecture that incorporates a new mobile sensing agent model and virtual organizations of agents for information fusion and machine learning, as well as contextual information to enrich the social knowledge representation.

Mobile Sensing Agents for Social Computing Environments

Pervasive Wi-Fi connectivity is attractive for users in places not covered by cellular services (e.g., when traveling abroad). However, the power drain of frequent Wi-Fi scans undermines the device's battery life, preventing users from staying always connected and fetching synced emails and instant message notifications (e.g., WhatsApp). We study the energy overhead of scan and roaming in detail and refer to it as the scan tax problem. Our findings show that the main processor is the primary culprit of the energy overhead. We propose a simple and effective architectural change of offloading scans to the Wi-Fi radio. We design and build WiScan to fully exploit the gain of scan offloading. Our experiments demonstrate that WiScan achieves 90%+ of the maximal connectivity, while saving 50-62% energy for seeking connectivity.

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Low-power pervasive wi-fi connectivity using WiScan

Longitudinal analysis of a campus Wi-Fi network

Wireless signals and networks are ubiquitous. Though more reliable than ever, wireless networks still struggle with weak coverage, blind spots, and interference. Having a strong understanding of wireless signal propagation is essential for increasing coverage, optimizing performance, and minimizing interference for wireless networks. Extensive studies have analyzed the propagation of wireless signals and proposed theoretical models to simulate wireless signal propagation. Unfortunately, models of signal propagation are often not accurate in reality. Real-world signal measurements are required for validation.Existing methods for collecting wireless measurements either involve researchers walking to each location of interest and manually collecting measurements, or place sensors at each measurement location. As such, they require large amounts of time and effort and can be costly. We propose DroneSense, a system for measuring wireless signals in the 3D space using autonomous drones. Drone-Sense reduces the time and effort required for measurement collection, and is affordable and accessible to all users. It provides researchers with an efficient method to quickly analyze wireless coverage and test their wireless propagation models.

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Xia Zhou

Papers

Noninvasive glucose monitoring using polarized light

Mobile Sensing Agents for Social Computing Environments

Low-power pervasive wi-fi connectivity using WiScan

Longitudinal analysis of a campus Wi-Fi network

Automating 3D wireless measurements with drones