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.

/pdf/advances-in-cognitive-radio-networks-a-survey-3gp2nvo27m.pdf

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

Dynamic spectrum auction is an effective solution to provide spectrum on-demand to many small wireless networks. As the number of participants grows, bidder collusion becomes a serious threat. In this paper, we study bidder collusion in large-scale spectrum auctions, investigating its impact on auction outcomes. We found that the nature of the complex interference constraints among bidders provides a fertile breeding ground for colluders, causing significant damage in auction efficiency and revenue. In particular, collusion group of small size plays a dominant role since it is easy to form and hard to be detected.We propose Athena, a new collusion-resistant auction framework for large-scale dynamic spectrum auction. Athena implements a soft collusion resistance, allowing the auctioneer to exploit the tradeoff between the level of collusion resistance and the cost of achieving such level of resistance. Unlike existing solutions, Athena enables spectrum reuse across bidders, achieves soft collusion resistance against any form of collusive bidding strategy, maintains provable revenue guarantee, and does so with polynomial-time complexity. To provide a comprehensive evaluation, we first analytically prove Athena's collusion resistance and revenue guarantee (under any bids), and then experimentally verify our analytical conclusions using empirical bid distributions.

https://www.cs.dartmouth.edu/~xia/papers/athena_slides.pdf

Breaking bidder collusion in large-scale spectrum auctions

SmartGPA: How Smartphones Can Assess and Predict Academic Performance of College Students

Much of the stress and strain of student life remains hidden. The StudentLife continuous sensing app assesses the day-to-day and week-by-week impact of workload on stress, sleep, activity, mood, sociability, mental well-being and academic performance of a single class of 48 students across a 10 weeks term at Dartmouth College using Android phones. Results from the StudentLife study show a number of significant correlations between the automatic objective sensor data from smartphones and mental health and educational outcomes of the student body. We propose a simple model based on linear regression with lasso regularization that can accurately predict cumulative GPA. We also identify a Dartmouth term lifecycle in the data that shows students start the term with high positive affect and conversation levels, low stress, and healthy sleep and daily activity patterns. As the term progresses and the workload increases, stress appreciably rises while positive affect, sleep, conversation and activity drops off. The StudentLife dataset is publicly available on the web.

StudentLife: Using Smartphones to Assess Mental Health and Academic Performance of College Students

We describe our efforts to empirically validate a distributed spectrum monitoring system built on commodity smartphones and embedded low-cost spectrum sensors. This system enables real-time spectrum sensing, identifies and locates active transmitters, and generates alarm events when detecting anomalous transmitters. To evaluate the feasibility of such a platform, we perform detailed experiments using a prototype hardware platform using smartphones and RTL dongles. We identify multiple sources of error in the sensing results and the end-user overhead (i.e. smartphone energy draw). We propose and implement a variety of techniques to identify and overcome errors and uncertainty in the data, and to reduce energy consumption. Our work demonstrates the basic viability of user-driven spectrum monitoring on commodity devices.

Empirical Validation of Commodity Spectrum Monitoring

The minimization of the amount of power consumed by an electronic device in acquiring or maintaining network connectivity with a network may extend the battery life of the electronic device. When the electronic device has established a communication connection with a wireless access point, the electronic device cycles a network interface controller of the electronic device between a power on state and a power off state without terminating the communication connection. Accordingly, the electronic device powers on a main processor of the electronic device when the network interface controller detects a beacon during the power on state that indicates the wireless access point has a buffered data frame for the electronic device.

Xia Zhou

Papers

Breaking bidder collusion in large-scale spectrum auctions

SmartGPA: How Smartphones Can Assess and Predict Academic Performance of College Students

StudentLife: Using Smartphones to Assess Mental Health and Academic Performance of College Students

Empirical Validation of Commodity Spectrum Monitoring

Energy efficient maximization of network connectivity