Conflict-Aware Real-Time Routing for Industrial Wireless Sensor-Actuator Networks

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. Real-time scheduling and delay analysis have been studied for WSAN extensively. End-to-end delay in WSANs highly depends on routing, which is still open problem. This paper presents the first real-time routing design for WSAN. We first discuss end-to-end delays of WSANs, then present our real-time routing design. We have implemented and experimented our routing designs on a wireless testbed of 69 nodes. Both experimental results and simulations show that our routing design can improve the real-time performance significantly

Maximizing Network Lifetime of Wireless Sensor-Actuator Networks under Graph Routing

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. The dynamics of industrial environments and stringent reliability requirements necessitate high degrees of fault tolerance in routing. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. WirelessHART employs graph routing schemes to achieve network reliability through multiple paths. Since many industrial devices operate on batteries in harsh environments where changing batteries are prohibitively labor-intensive, WSANs need to achieve long network lifetime. To meet industrial demand for long-term reliable communication, this paper studies the problem of maximizing network lifetime for WSANs under graph routing. We formulate the network lifetime maximization problem for WirelessHART networks under graph routing. Then, we propose the optimal algorithm and two more efficient algorithms to prolong the network lifetime of WSANs. Experiments in a physical testbed and simulations show our linear programming relaxation and greedy heuristics can improve the network lifetime by up to 50% while preserving the reliability benefits of graph routing

Neighbor discovery for industrial wireless sensor networks with mobile nodes

Industrial wireless sensor networks can facilitate the deployment of a wide range of novel industrial applications, including mobile applications that connect mobile robots, vehicles, goods and workers to industrial networks. Current industrial wireless sensor standards have been mainly designed for static deployments, and their performance significantly degrades when introducing mobile devices. One of the major reasons for such degradation is the neighbor discovery process. This paper presents and evaluates two novel neighbor discovery protocols that improve the capability of mobile devices to remain connected to the industrial wireless sensor networks as they move. The proposed protocols exploit topology information and the nature of devices (static or mobile) to reliably and rapidly discover neighbor devices. This is achieved in some cases at the expense of increasing the number of radio resources utilized and the energy consumed in the discovery process. The proposed solutions have been designed and evaluated considering the WirelessHART standard given its widespread industrial adoption. However, they can also be adapted for the ISA100.11a and IEEE 802.15.4e standards.This work was supported in part by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the project TEC2014-57146-Rby the Local Government of Valencia with reference ACIF/2013/060 and by the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 723909 (AUTOWARE project)

Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing

Bio-Inspired Multi-Spectral Imaging Sensors and Algorithms for Image Guided Surgery

Image guided surgery (IGS) utilizes emerging imaging technologies to provide additional structural and functional information to the physician in clinical settings. This additional visual information can help physicians delineate cancerous tissue during resection as well as avoid damage to near-by healthy tissue. Near-infrared (NIR) fluorescence imaging (700 nm to 900 nm wavelengths) is a promising imaging modality for IGS, namely for the following reasons: First, tissue absorption and scattering in the NIR window is very low, which allows for deeper imaging and localization of tumor tissue in the range of several millimeters to a centimeter depending on the tissue surrounding the tumor. Second, spontaneous tissue fluorescence emission is minimal in the NIR region, allowing for high signal-to-background ratio imaging compared to visible spectrum fluorescence imaging. Third, decoupling the fluorescence signal from the visible spectrum allows for optimization of NIR fluorescence while attaining high quality color images. Fourth, there are two FDA approved fluorescent dyes in the NIR region—namely methylene blue (MB) and indocyanine green—which can help to identify tumor tissue due to passive accumulation in human subjects. The aforementioned advantages have led to the development of NIR fluorescence imaging systems for a variety of clinical applications, such as sentinel lymph node imaging, angiography, and tumor margin assessment. With these technological advances, secondary surgeries due to positive tumor margins or damage to healthy organs can be largely mitigated, reducing the emotional and financial toll on the patient. Currently, several NIR fluorescence imaging systems (NFIS) are available commercially or are undergoing clinical trials, such as FLARE, SPY, PDE, Fluobeam, and others. These systems capture multi-spectral images using complex optical equipment and are combined with real-time image processing to present an augmented view to the surgeon. The information is presented on a standard monitor above the operating bed, which requires the physician to stop the surgical procedure and look up at the monitor. The break in the surgical flow sometimes outweighs the benefits of fluorescence based IGS, especially in time-critical surgical situations. Furthermore, these instruments tend to be very bulky and have a large foot print, which significantly complicates their adoption in an already crowded operating room. In this document, I present the development of a compact and wearable goggle system capable of real-time sensing of both NIR fluorescence and color information. The imaging system is inspired by the ommatidia of the monarch butterfly, in which pixelated spectral filters are integrated with light sensitive elements. The pixelated spectral filters are fabricated via a carefully optimized nanofabrication procedure and integrated with a CMOS imaging array. The entire imaging system has been optimized for high signal-to-background fluorescence imaging using an analytical approach, and the efficacy of the system has been experimentally verified. The bio-inspired spectral imaging sensor is integrated with an FPGA for compact and real-time signal processing and a wearable goggle for easy integration in the operating room. The complete imaging system is undergoing clinical trials at Washington University in the St. Louis Medical School for imaging sentinel lymph nodes in both breast cancer patients and melanoma patients