Browsing by Subject "Internet of Things"

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Application-specific Design and Optimization for Ultra-Low-Power Embedded Systems
    (2019-08) Cherupalli, Hari
    The last few decades have seen a tremendous amount of innovation in computer system design to the point where electronic devices have become very inexpensive. This has brought us on the verge of a new paradigm in computing where there will be hundreds of devices in a person’s environment, ranging from mobile phones to smart home devices to wearables to implantables, all interconnected. This paradigm, called the Internet of Things (IoT), brings new challenges in terms of power, cost, and security. For example, power and energy have become critical design constraints that not only affect the lifetime of an ultra-low-power (ULP) system, but also its size and weight. While many conventional techniques exist that are aimed at energy reduction or that improve energy efficiency, they do so at the cost of performance. As such, their impact is limited in circumstances where energy is very constrained or where significant degradation of performance or functionality is unacceptable. Focusing on the opposing demands to increase both energy efficiency and performance simultaneously in a world where Moore’s law scaling is decelerating, one of the underlying themes of this work has been to identify novel insights that enable new pathways to energy efficiency in computing systems while avoiding the conventional tradeoff that simply sacrifices performance and functionality for energy efficiency. To this end, this work proposes a method to analyze the behavior of an application on the gate-level netlist of a processor for all possible inputs using a novel symbolic hardware-software co-analysis methdology. Using this methodology several techniques have been proposed to optimize a given processor-application pair for power, area and security.
  • Thumbnail Image
    Item
    Conversations (oral history interviews) with members of North Carolina State University Computer Science Department by Carol Lee and Carolyn Miller
    (Department of Computer Science, North Carolina State University, 2017-08-01) Bahler, Dennis; Battestilli, Lina; DeMaria, Mark; Healey, Christopher; Heckman, Sarah; Heil, Margaret; Lester, James; Mott, Bradford; Mealin, Sean; Novitsky, Melissa; Reeves, Douglas; Rouskas, George; Streck, John; Tate, Ken; Vouk, Mladen; Williams, Laurie
    This is a compilation of 16 individual interviews gathered between November 2016 and February 2017 and published in August 2017 to mark the 50th Anniversary of the Department of Computer Science at N.C. State University. Interviewees ranged from undergraduate students to the Department Head. The interviewees included three students, eleven faculty, and two staff members. Their interviewees provide a broad view of the department in the decade ending in 2017. Two standard questions were asked of each interviewee: what computing devices do you use and what is computer science today? The answers reflect the personal computing technology in use at the time, as well as the definition of Computer Science from various points of view and experience. The ubiquity of computers in every facet of contemporary life is a recurring response. The primary themes are: the abundance of opportunity within computer science education and the importance of seizing it; the multi-disciplinary nature of the department, which includes the presence of the Center for the Education and Informatics; the benefit of being located in the Research Triangle Park with all its opportunities for collaboration and future employment; the cutting-edge program for undergraduate research; and the innovative capstone class combining writing and presentation skills with computer science knowledge. There is emphasis on the Professional Teaching Faculty, which includes computer science faculty members who are dedicated exclusively to teaching, with no research or grant-writing responsibilities. Also featured is the Interdisciplinary Faculty Cluster program in which faculty from many disciplines are hired in a cluster to work on a specific theme or research topic.
  • Thumbnail Image
    Item
    IoT Networking via Cross-technology Communication
    (2022-06) Liu, Ruofeng
    The prevalence of Internet of Things (IoT) brings various heterogeneous wireless techniques, such as Wi-Fi, LTE, ZigBee,Bluetooth, and LoRa. Due to the scarcity of spectrum resources, these wireless technologies commonly share the unlicensed industrial, scientific and medical (ISM) radio band. The coexistence scenario motivates the studies of IoT networking among heterogeneous wireless devices, which breaks the boundary between wireless protocols and paves way for a lot of novel applications (e.g., cross-technology data dissemination, data collection, location services, etc.). This dissertation focuses on the key enabler of IoT networking among heterogeneity - cross-technology communication (CTC) which allows heterogeneous wireless devices to directly exchange data without modifying their hardware. To address the critical roadblock of CTC - incompatibility in their physical (PHY) layers, we propose two approaches, demonstrating the feasibility of CTC both from high-speed to low-speed radios and from low-speed to high-speed ones. First, we present LTE2B which enables CTC from high-speed radios (e.g., LTE) to low-speed radios (e.g., ZigBee and Bluetooth). The key technical contribution is a time-domain signal emulation (TDE) approach which allows a LTE transmitter to produce emulated ZigBee or Bluetooth signal by approximating their time-domain waveform. In addition, it addresses other practical constraints (e.g., turbo coding constraint) to achieve transparent CTC with full compatibility with LTE standards. Our experiment result shows that LTE smartphones can directly disseminate messages to ZigBee devices within a 400-meter range. Second, we introduce XFi which shows the feasibility of CTC in the reverse direction, i.e., from low-speed radios (e.g., ZigBee and LoRa) to high-speed Wi-Fi. To address the fundamental limitation of bandwidth disparity, XFi adopts signal hitchhiking - low-speed IoT packets from ZigBee and LoRa devices can hitchhike on the high-speed Wi-Fi traffic and be captured by Wi-Fi radios. The unique discovery is that Wi-Fi devices can obtain the hitchhiking IoT data from the errors in decoded Wi-Fi payloads that are available in the software. The key insight enables CTC with zero modification to Wi-Fi hardware. Our evaluation demonstrates that Wi-Fi can collect data from 8 IoT devices in parallel with an overall throughput of 1.8 Mbps. Finally, we adopt CTC technique in a commercial Bluetooth location service to study and address the challenges of applying cross-technology design in real-world scenarios. We propose WiBeacon which repurposes ubiquitously deployed WiFi access points (AP) into virtual BLE beacons via only moderate software upgrades. This offers fast deployment of BLE LBS with zero additional hardware costs and low maintenance burdens. WiBeacon is carefully integrated with native WiFi services, retaining transparency to WiFi clients. We implement WiBeacon on commodity WiFi APs (with various chipsets such as Qualcomm, Broadcom, and MediaTek) and extensively evaluate it across various scenarios, including a real commercial application for courier check-ins. During the two-week pilot study, WiBeacon provides reliable services, i.e., as robust as conventional BLE beacons, for 697 users with 150 types of smartphones.
  • Thumbnail Image
    Item
    IoT Networking: From Coexistence to Collaboration
    (2016-05) Kim, Song Min
    The new computing paradigm of IoT (Internet of Things) is carried out by globally and massively interconnected devices. This is founded on the unprecedented proliferation of heterogeneous wireless technologies in the last decade, each offering convenience in different aspects of our daily lives – WiFi enables hassle-free Internet access and Bluetooth allows prevalent healthcare with its wireless heart monitors. However, wireless technologies are victims of their own success; dense deployment of wireless devices intensify the interference between them, which recently has become a major cause of performance degradation. My dissertation work is an effort to address the issue with practical and cost-effective solutions. The dissertation consists of two main parts. The first part proposes approaches to achieve high-performance networking under arbitrary interference from unknown sources. Namely, cETX and CorrModel are proposed, where they enable efficient unicast and broadcast under severely interfered channel. This is achieved by observing the different aspects of interference including volume as well as temporal/spatial pattern and dynamics. To maximize the adaptability, both cETX and CorrModel are designed as generic techniques to support networks running different protocols, under a wide range of settings. Indoor and outdoor testbed evaluations performed on twelve unicast and nine broadcast protocols demonstrate that they bring 20-30% performance gain. The second part of the dissertation takes a step further, to explore the opportunity behind the coexistence of heterogeneous wireless technologies. The dissertation introduces FreeBee, which extends direct connectivity beyond wireless technologies to enable collaboration and mutual supplementation. By doing so FreeBee not only enables cross-technology interference mitigation but also brings advanced services such as context-aware smart operation. Evaluations reveals that FreeBee achieves reliable communication in under a second and supports mobility of up to 30mph.
  • Thumbnail Image
    Item
    Localization: re-discovering under-utilized hardware capabilities to create new applications and solutions
    (2022-04) Liu, Song
    Localization is a fundamental service that has enabled a plethora of applications and systems, such as enriching sensor data with location information in Wireless Sensor Networks and tracking device inputs in Human-Computer-Interface systems. The landscape of localization is still constantly evolving and there is currently no single localization method that satisfies all application scenarios and its intended needs. Instead of basing on the well known hardware setups and iterating on another incrementally better localization algorithm, this dissertation aims at creating unprecedented localization-enabled applications and system paradigms through rediscovering of and designing around under-utilized hardware capabilities. Many lessons are learned while the authors wander in the no man's land of utilizing these hardware capabilities to invent new applications/solutions, and hopefully will open up some new opportunities and pave some early roadways for future researchers/engineers interested to advance further. More specifically, we make the following discoveries and advancements: SmartLight: the first 3D digital sensor localization system. Since Spotlight was published in 2005 as the first 2D digital localization solution, the research community has long been looking for a 3D digital localization solution. Through digging into and utilizing the light refraction properties of lenses, we design and prototype ``SmartLight'', as the first 3D digital localization solution that elegantly solves the problems and provides superior robustness. This work won the best paper award at the world's top-tier research conference on sensor-networked systems: 2017 ACM Conference on Embedded Networked Sensor Systems. The system was also patented by US 11,051,270 B2. This is an important topic in the field because existing localization techniques are almost all analog-based, i.e., their accuracy heavily depends on the calibration of the model parameters and measurements of analog metrics such as angle of arrival (AOA) and received signal strength (RSS). It is well known that analog-based approaches usually require tedious calibration and suffer from performance degradation in noisy environments. ``SmartLight'' aims to shed light on the superior robustness and accuracy that digital approaches can offer. In a nutshell, ``SmartLight'' exploits light splitting geometry properties of convex lens to create an one-to-one mapping between a location and the set of orthogonal digital light signals receivable at that location. Advanced designs are also introduced to further improve the system accuracy and scalability beyond the hardware capability. Evaluation shows that it exhibited superior robustness against 1) environmental noise (e.g. sunlight, fluorescent lamps), 2) fluctuation and degradation of light source intensity, 3) receiver orientation, and 4) disturbance along light propagation paths (e.g. reflection and attenuation). BitLight: the first screen-sensor virtual touchscreen application. This is the first to imagine and prototype the conceptual application of sensor-display virtual touchscreen application ``BitLight''. It is only technically possible through utilizing and designing around the ultra-fine temporal division capabilities of DLP hardware. Intuitively it is motivated by the information-carrying property of light signals, and it is a novel paradigm that uses the rapid flashing of a digital light processing (DLP) projector to encode an imperceptible mask temporally that, when sensed by a photo-diode, uniquely specifies where the photo-diode is located on the projected image. This thus creates a ``free'' functionality of sensor localization during concurrent viewing of visual content. ``BitLight'' is inspired by the psycho-physical phenomenon that the human visual system (HVS) cannot resolve rapid temporal changes in optical signals, so redundant optical signals could be inserted for tracking with some or little compromise on the original human perceived visual content. ``BitLight'' is the first to devise a bit-level temporal encoding to display RGB colors while also embedding tracking signals in a digital fashion. Compared to traditional visible-light-communication (VLC) systems that use frame-level encoding techniques such as luminance changes and alpha channel, the bit-level encoding of ``BitLight'' makes better use of the ultra-fine temporal division capabilities of DLP projectors to embed a much higher tracking data throughput and thus achieve faster localization speed. With our current prototype hardware of a low-end micro-controller, cheap photo-diodes, and a commercial off-the-shelf DLP projector, evaluation results have demonstrated an average of only 9.5ms to localize the sensor, versus 200ms by a comparison test-bed that uses simple frame-level encoding. In summary, the innovation of the dissertation is primarily concentrated on finding new localization applications and solutions by rediscovering usages of under-utilized hardware capabilities. We design 1) the first-ever digital 3D light-based localization solution; 2) the first-ever screen-sensor virtual touchscreen application; The techniques proposed in the dissertation should have laid a pioneering and exploratory foundation for any future localization research on these new hardware applications and paradigms.
  • Thumbnail Image
    Item
    Unity-based BCI2000 Application Layer: Virtual Reality and the Internet of Things
    (2017-12) Coogan, Christopher
    Brain-computer interfaces (BCIs) have enabled individuals to control devices such as spellers, robotic arms, drones, and wheelchairs, but often these BCI applications are restricted to research laboratories. With the advent of virtual reality (VR) systems and the internet of things (IoT) we can couple these technologies to offer real-time control of a user’s virtual and physical environment. Likewise, BCI applications are often single-use with user’s having no control outside of the restrictions placed upon the applications at the time of creation. Therefore, there is a need to create a tool that allows users the flexibility to create and modularize aspects of BCI applications for control of IoT devices and VR environments. Using a popular video game engine, Unity, and coupling it with BCI2000, we can create diverse applications that give the end-user additional autonomy during the task at hand. We demonstrate the validity of controlling a Unity-based VR environment and several commercial IoT devices via direct neural interfacing processed through BCI2000.