A Wrapper-Based Approach to Sustained Time Synchronization in Wireless Sensor Networks

Time synchronization is an important service for wireless sensor network applications. Nodes in the network stay synchronized by exchanging periodic messages that carry local timestamps. Several algorithms have been proposed in the literature that are suited to different kinds of application scenarios. A common problem across these time synchronization algorithms is that the energy cost of message exchange is high. In fact, the cost of radio communication far outstrips the cost of performing local operations on the processor. If the message exchanges were stopped, nodes will fall out of sync, and may no longer be able to meet application requirements. This thesis presents a wrapper-based approach to sustained time synchronization for wireless sensor networks. As such, this solution Booster for Time Synchronization Protocol (BTSP) will act as a wrapper around a given time synchronization protocol, and will apply local corrector operations to extend the time duration between two message exchanges between nodes. The wrapper performs at least as good as the original protocol provided, reduces the number of message exchanges on average, and consequently the energy consumed, significantly. BTSP has been implemented for TinyOS and evaluated on XSM motes in conjunction with TPSN, a popular time synchronization protocol for sensor network

A Wrapper-Based Approach to Sustained Time Synchronization in Wireless Sensor Networks

Time synchronization is an important service for wireless sensor network applications. Nodes in the network stay synchronized by exchanging periodic messages that carry local timestamps. Several algorithms have been proposed in the literature that are suited to different kinds of application scenarios. A common problem across these time synchronization algorithms is that the energy cost of message exchange is high. In fact, the cost of radio communication far outstrips the cost of performing local operations on the processor. If the message exchanges were stopped, nodes will fall out of sync, and may no longer be able to meet application requirements. This thesis presents a wrapper-based approach to sustained time synchronization for wireless sensor networks. As such, this solution Booster for Time Synchronization Protocol (BTSP) will act as a wrapper around a given time synchronization protocol, and will apply local corrector operations to extend the time duration between two message exchanges between nodes. The wrapper performs at least as good as the original protocol provided, reduces the number of message exchanges on average, and consequently the energy consumed, significantly. BTSP has been implemented for TinyOS and evaluated on XSM motes in conjunction with TPSN, a popular time synchronization protocol for sensor network

Wireless Sensor Networking in Challenging Environments

Recent years have witnessed growing interest in deploying wireless sensing applications in real-world environments. For example, home automation systems provide fine-grained metering and control of home appliances in residential settings. Similarly, assisted living applications employ wireless sensors to provide continuous health and wellness monitoring in homes. However, real deployments of Wireless Sensor Networks (WSNs) pose significant challenges due to their low-power radios and uncontrolled ambient environments. Our empirical study in over 15 real-world apartments shows that low-power WSNs based on the IEEE 802.15.4 standard are highly susceptible to external interference beyond user control, such as Wi-Fi access points, Bluetooth peripherals, cordless phones, and numerous other devices prevalent in residential environments that share the unlicensed 2.4 GHz ISM band with IEEE 802.15.4 radios. To address these real-world challenges, we developed two practical wireless network protocols including the Adaptive and Robust Channel Hopping (ARCH) protocol and the Adaptive Energy Detection Protocol (AEDP). ARCH enhances network reliability through opportunistically changing radio\u27s frequency to avoid interference and environmental noise and AEDP reduces false wakeups in noisy wireless environments by dynamically adjusting the wakeup threshold of low-power radios. Another major trend in WSNs is the convergence with smart phones. To deal with the dynamic wireless conditions and varying application requirements of mobile users, we developed the Self-Adapting MAC Layer (SAML) to support adaptive communication between smart phones and wireless sensors. SAML dynamically selects and switches Medium Access Control protocols to accommodate changes in ambient conditions and application requirements. Compared with the residential and personal wireless systems, industrial applications pose unique challenges due to their critical demands on reliability and real-time performance. We developed an experimental testbed by realizing key network mechanisms of industrial Wireless Sensor and Actuator Networks (WSANs) and conducted an empirical study that revealed the limitations and potential enhancements of those mechanisms. Our study shows that graph routing is more resilient to interference and its backup routes may be heavily used in noisy environments, which demonstrate the necessity of path diversity for reliable WSANs. Our study also suggests that combining channel diversity with retransmission may effectively reduce the burstiness of transmission failures and judicious allocation of multiple transmissions in a shared slot can effectively improve network capacity without significantly impacting reliability

Innovative technologies of wireless sensor network: The applications of WBAN system and environment

Wireless Body Area Networks (WBAN) have risen as a key innovation for providing real-time patient health care and diagnosing many life-threatening diseases. The principle adopted by health service providers is providing convenience for patients in need of health care, allowing them comfortable with the movement and constant monitoring with a reduction in health care costs. This study presented the basic concept and general background of the main WBAN system with applications. The current models for on-body and embedded WBANs, sensor node features, and sensor schemes for information via negation are used in the WBAN

A Sensor Network System for Monitoring Short-Term Construction Work Zones

Safety hazards encountered near construction work zones are high, both in number and in the kind. There is a need to monitor traffic in such construction zones in order to improve driver and vehicle safetyIn the past traffic monitoring systems were built with high cost equipment such as inductive plates, video cameras etc. These solutions are too cost{prohibitive and invasive to be used in the large. Wireless sensor networks provide an opportunity space that can be used to address this problem. This thesis specifically targets temporary or short-term construction work zones. We present the design and implementation of a sensor network system targeted at monitoring the flow of traffic through these temporary construction work zones. As opposed to long-term work zones which are common on highways, short-term or temporary work zones remain active for a few hours or a few days at most. As such, instrumenting temporary work zones with monitoring equipment similar to those used in long-term work zones is not practical. Yet, these temporary work zones present an important problem in terms of crashes occurring in and around them. The design for this sensornet-based system for monitoring traffic is (a) inexpensive, (b) rapidly deployable, (c) requires minimal maintenance and (d) non-invasive. In this thesis we present our experiences in building this system, and testing this system in live work zones in the Greater Cleveland are

Triggering of Ambulatory Blood Pressure Measurement Based on Patient Status: Software Architecture and Implementation

Blood pressure is an important physiological parameter that is used for both assessing immediate health status of hospitalized patients and providing indications of various cardiovascular diseases. Invasive blood pressure measurement has stayed as gold standard of blood pressure measurement while oscillometric measurement has established its position as the primary measurement method in hospital wards and home care. However, research around continuous non-invasive blood pressure measurement (CNIBP) methodologies have been growing, and blood pressure monitoring devices using CNIBP have developed recently. Applied CNIBP methods include, but are not limited to, pulse wave velocity and pulse wave analysis. In this thesis, a prototype software system for detecting significant and sustained changes in a patient’s blood pressure was designed and implemented. The system is based on pulse wave analysis based continuous blood pressure measurement algorithm. The goal was to either trigger a cuff-based measurement automatically or to prompt the user to take a new cuff measurement when needed. Characteristics of the applied CNIBP method set requirements for the system. CNIBP measurement is affected by the patient’s posture as well as movement, and therefore, information about the activity of the patient was needed. Furthermore, the ambulatory patient monitoring system, in which the prototype was integrated, set architectural requirements for the developed system. Signal fault conditions were essential to recognize and handle by the implemented software. The implemented system consists of four parts: continuous blood pressure estimation, patient activity detection, evaluation of the need for the blood pressure measurement, and notifier. The system uses a photoplethysmographic signal from an oxygen saturation sensor as an input for the blood pressure estimator. Accelerometer signals from the patient’s chest and wrist are used to detect the patient’s posture and activity. Continuous blood pressure estimate and patient activity information are used in assessing the need for a cuff-based blood pressure measurement. The system is designed to operate alongside auto-cycling ambulatory blood pressure monitoring. The algorithm that estimates blood pressure changes was provided by an external partner while the algorithm classifying the patient’s activity was developed in GE Healthcare. The algorithm that estimates the need for the blood pressure measurement was developed in a collaboration with a team of engineers working on the project. The parts of the system mentioned above were combined into the functional system and integrated into the ambulatory monitoring system. It was demonstrated that the system can detect significant and sustained blood pressure changes reliably, while at the same time discarding false readings in continuous blood pressure, as well as the blood pressure changes caused by the subject’s activity. Therefore, the system can provide actionable information about the changes in patient blood pressure and adds new value to patient monitoring

Biology-Inspired Approach for Communal Behavior in Massively Deployed Sensor Networks

Research in wireless sensor networks has accelerated rapidly in recent years. The promise of ubiquitous control of the physical environment opens the way for new applications that will redefine the way we live and work. Due to the small size and low cost of sensor devices, visionaries promise smart systems enabled by deployment of massive numbers of sensors working in concert. To date, most of the research effort has concentrated on forming ad hoc networks under centralized control, which is not scalable to massive deployments. This thesis proposes an alternative approach based on models inspired by biological systems and reports significant results based on this new approach. This perspective views sensor devices as autonomous organisms in a community interacting as part of an ecosystem rather than as nodes in a computing network. The networks that result from this design make local decisions based on local information in order for the network to achieve global goals, thus we must engineer for emergent behavior in wireless sensor networks. First we implemented a simulator based on cellular automata to be used in algorithm development and assessment. Then we developed efficient algorithms to exploit emergent behavior for finding the average of distributed values, synchronizing distributed clocks, and conducting distributed binary voting. These algorithms are shown to be convergent and efficient by analysis and simulation. Finally, an extension of this perspective is used and demonstrated to provide significant progress on the noise abatement problem for jet aircraft. Using local information and actions, optimal impedance values for an acoustic liner are determined in situ providing the basis for an adaptive noise abatement system that provides superior noise reduction compared with current technology and previous research efforts

Architecting a One-to-many Traffic-Aware and Secure Millimeter-Wave Wireless Network-in-Package Interconnect for Multichip Systems

With the aggressive scaling of device geometries, the yield of complex Multi Core Single Chip(MCSC) systems with many cores will decrease due to the higher probability of manufacturing defects especially, in dies with a large area. Disintegration of large System-on-Chips(SoCs) into smaller chips called chiplets has shown to improve the yield and cost of complex systems. Therefore, platform-based computing modules such as embedded systems and micro-servers have already adopted Multi Core Multi Chip (MCMC) architectures overMCSC architectures. Due to the scaling of memory intensive parallel applications in such systems, data is more likely to be shared among various cores residing in different chips resulting in a significant increase in chip-to-chip traffic, especially one-to-many traffic. This one-to-many traffic is originated mainly to maintain cache-coherence between many cores residing in multiple chips. Besides, one-to-many traffics are also exploited by many parallel programming models, system-level synchronization mechanisms, and control signals. How-ever, state-of-the-art Network-on-Chip (NoC)-based wired interconnection architectures do not provide enough support as they handle such one-to-many traffic as multiple unicast trafficusing a multi-hop MCMC communication fabric. As a result, even a small portion of such one-to-many traffic can significantly reduce system performance as traditional NoC-basedinterconnect cannot mask the high latency and energy consumption caused by chip-to-chipwired I/Os. Moreover, with the increase in memory intensive applications and scaling of MCMC systems, traditional NoC-based wired interconnects fail to provide a scalable inter-connection solution required to support the increased cache-coherence and synchronization generated one-to-many traffic in future MCMC-based High-Performance Computing (HPC) nodes. Therefore, these computation and memory intensive MCMC systems need an energy-efficient, low latency, and scalable one-to-many (broadcast/multicast) traffic-aware interconnection infrastructure to ensure high-performance. Research in recent years has shown that Wireless Network-in-Package (WiNiP) architectures with CMOS compatible Millimeter-Wave (mm-wave) transceivers can provide a scalable, low latency, and energy-efficient interconnect solution for on and off-chip communication. In this dissertation, a one-to-many traffic-aware WiNiP interconnection architecture with a starvation-free hybrid Medium Access Control (MAC), an asymmetric topology, and a novel flow control has been proposed. The different components of the proposed architecture are individually one-to-many traffic-aware and as a system, they collaborate with each other to provide required support for one-to-many traffic communication in a MCMC environment. It has been shown that such interconnection architecture can reduce energy consumption and average packet latency by 46.96% and 47.08% respectively for MCMC systems. Despite providing performance enhancements, wireless channel, being an unguided medium, is vulnerable to various security attacks such as jamming induced Denial-of-Service (DoS), eavesdropping, and spoofing. Further, to minimize the time-to-market and design costs, modern SoCs often use Third Party IPs (3PIPs) from untrusted organizations. An adversary either at the foundry or at the 3PIP design house can introduce a malicious circuitry, to jeopardize an SoC. Such malicious circuitry is known as a Hardware Trojan (HT). An HTplanted in the WiNiP from a vulnerable design or manufacturing process can compromise a Wireless Interface (WI) to enable illegitimate transmission through the infected WI resulting in a potential DoS attack for other WIs in the MCMC system. Moreover, HTs can be used for various other malicious purposes, including battery exhaustion, functionality subversion, and information leakage. This information when leaked to a malicious external attackercan reveals important information regarding the application suites running on the system, thereby compromising the user profile. To address persistent jamming-based DoS attack in WiNiP, in this dissertation, a secure WiNiP interconnection architecture for MCMC systems has been proposed that re-uses the one-to-many traffic-aware MAC and existing Design for Testability (DFT) hardware along with Machine Learning (ML) approach. Furthermore, a novel Simulated Annealing (SA)-based routing obfuscation mechanism was also proposed toprotect against an HT-assisted novel traffic analysis attack. Simulation results show that,the ML classifiers can achieve an accuracy of 99.87% for DoS attack detection while SA-basedrouting obfuscation could reduce application detection accuracy to only 15% for HT-assistedtraffic analysis attack and hence, secure the WiNiP fabric from age-old and emerging attacks

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices