Cyber-Physical Co-Design of Wireless Control Systems

Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption in process industries because of its advantages in lowering deployment and maintenance cost in challenging environments. While early success of industrial WSANs has been recognized, significant potential remains in exploring WSANs as unified networks for industrial plants. This thesis research explores a cyber-physical co-design approach to design wireless control systems. To enable holistic studies of wireless control systems, we have developed the Wireless Cyber-Physical Simulator (WCPS), an integrated co-simulation environment that integrates Simulink and our implementation of WSANs based on the industrial WirelessHART standard. We further develop novel WSAN protocols tailored for advanced control designs for networked control systems. WCPS now works as the first simulator that features both linear and nonlinear physical plant models, state-of-art WirelessHART protocol stack, and realistic wireless network characteristics. A realistic wireless structural control study sheds light on the challenges of WSC and the limitations of a traditional structural control approach under realistic wireless conditions. Systematic emergency control results demonstrate that our real-time emergency communication approach enables timely emergency handling, while allowing regular feedback control loops to effectively share resources in WSANs during normal operations. A co-joint study of wireless routing and control highlights the importance of the co-design approach of wireless networks and control

Innovative energy-efficient wireless sensor network applications and MAC sub-layer protocols employing RTS-CTS with packet concatenation

of energy-efficiency as well as the number of available applications. As a consequence there are challenges that need to be tackled for the future generation of WSNs. The research work from this Ph.D. thesis has involved the actual development of innovative WSN applications contributing to different research projects. In the Smart-Clothing project contributions have been given in the development of a Wireless Body Area Network (WBAN) to monitor the foetal movements of a pregnant woman in the last four weeks of pregnancy. The creation of an automatic wireless measurement system for remotely monitoring concrete structures was an contribution for the INSYSM project. This was accomplished by using an IEEE 802.15.4 network enabling for remotely monitoring the temperature and humidity within civil engineering structures. In the framework of the PROENEGY-WSN project contributions have been given in the identification the spectrum opportunities for Radio Frequency (RF) energy harvesting through power density measurements from 350 MHz to 3 GHz. The design of the circuits to harvest RF energy and the requirements needed for creating a WBAN with electromagnetic energy harvesting and Cognitive Radio (CR) capabilities have also been addressed. A performance evaluation of the state-of-the art of the hardware WSN platforms has also been addressed. This is explained by the fact that, even by using optimized Medium Access Control (MAC) protocols, if the WSNs platforms do not allow for minimizing the energy consumption in the idle and sleeping states, energy efficiency and long network lifetime will not be achieved. The research also involved the development of new innovative mechanisms that tries and solves overhead, one of the fundamental reasons for the IEEE 802.15.4 standard MAC inefficiency. In particular, this Ph.D. thesis proposes an IEEE 802.15.4 MAC layer performance enhancement by employing RTS/CTS combined with packet concatenation. The results have shown that the use of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before transmitting a data packet. In addition, the Sensor Block Acknowledgment MAC (SBACK-MAC) protocol has been proposed that allows the aggregation of several acknowledgment responses in one special Block Acknowledgment (BACK) Response packet. Two different solutions are considered. The first one considers the SBACK-MAC protocol in the presence of BACK Request (concatenation) while the second one considers the SBACK-MAC in the absence of BACK Request (piggyback). The proposed solutions address a distributed scenario with single-destination and single-rate frame aggregation. The throughput and delay performance is mathematically derived under both ideal conditions (a channel environment with no transmission errors) and non ideal conditions (a channel environment with transmission errors). An analytical model is proposed, capable of taking into account the retransmission delays and the maximum number of backoff stages. The simulation results successfully validate our analytical model. For more than 7 TX (aggregated packets) all the MAC sub-layer protocols employing RTS/CTS with packet concatenation allows for the optimization of channel use in WSNs, v8-48 % improvement in the maximum average throughput and minimum average delay, and decrease energy consumption

Towards reliable communication in low-power wireless body area networks

Es wird zunehmend die Ansicht vertreten, dass tragbare Computer und Sensoren neue Anwendungen in den Bereichen Gesundheitswesen, personalisierte Fitness oder erweiterte Realität ermöglichen werden. Die am Körper getragenen Geräte sind dabei mithilfe eines Wireless Body Area Network (WBAN) verbunden, d.h. es wird drahtlose Kommunikation statt eines drahtgebundenen Kanals eingesetzt. Der drahtlose Kanal ist jedoch typischerweise ein eher instabiles Kommunikationsmedium und die Einsatzbedingungen von WBANs sind besonders schwierig: Einerseits wird die Kanalqualität stark von den physischen Bewegungen der Person beeinflusst, andererseits werden WBANs häufig in lizenzfreien Funkbändern eingesetzt und sind daher Störungen von anderen drahtlosen Geräten ausgesetzt. Oft benötigen WBAN Anwendungen aber eine zuverlässige Datenübertragung. Das erste Ziel dieser Arbeit ist es, ein besseres Verständnis dafür zu schaffen, wie sich die spezifischen Einsatzbedingungen von WBANs auf die intra-WBAN Kommunikation auswirken. So wird zum Beispiel analysiert, welchen Einfluss die Platzierung der Geräte auf der Oberfläche des menschlichen Körpers und die Mobilität des Benutzers haben. Es wird nachgewiesen, dass während regelmäßiger Aktivitäten wie Laufen die empfangene Signalstärke stark schwankt, gleichzeitig aber Signalstärke-Spitzen oft einem regulären Muster folgen. Außerdem wird gezeigt, dass in urbanen Umgebungen die Effekte von 2.4 GHz Radio Frequency (RF) Interferenz im Vergleich zu den Auswirkungen von fading (Schwankungen der empfangenen Signalstärke) eher gering sind. Allerdings führt RF Interferenz dazu, dass häufiger Bündelfehler auftreten, d.h. Fehler zeitlich korrelieren. Dies kann insbesondere in Anwendungen, die eine geringe Übertragungslatenz benötigen, problematisch sein. Der zweite Teil dieser Arbeit beschäftigt sich mit der Analyse von Verfahren, die potentiell die Zuverlässigkeit der Kommunikation in WBANs erhöhen, ohne dass wesentlich mehr Energie verbraucht wird. Zunächst wird der Trade-off zwischen Übertragungslatenz und der Zuverlässigkeit der Kommunikation analysiert. Diese Analyse basiert auf einem neuen Paket-Scheduling Algorithmus, der einen Beschleunigungssensor nutzt, um die WBAN Kommunikation auf die physischen Bewegungen der Person abzustimmen. Die Analyse zeigt, dass unzuverlässige Kommunikationsverbindungen oft zuverlässig werden, wenn Pakete während vorhergesagter Signalstärke-Spitzen gesendet werden. Ferner wird analysiert, inwiefern die Robustheit gegen 2.4 GHz RF Interferenz verbessert werden kann. Dazu werden zwei Verfahren betrachtet: Ein bereits existierendes Verfahren, das periodisch einen Wechsel der Übertragungsfrequenz durchführt (channel hopping) und ein neues Verfahren, das durch RF Interferenz entstandene Bitfehler reparieren kann, indem der Inhalt mehrerer fehlerhafter Pakete kombiniert wird (packet combining). Eine Schlussfolgerung ist, dass Frequenzdiversität zwar das Auftreten von Bündelfehlern reduzieren kann, dass jedoch die statische Auswahl eines Kanals am oberen Ende des 2.4 GHz Bandes häufig schon eine akzeptable Abhilfe gegen RF Interferenz darstellt.There is a growing belief that wearable computers and sensors will enable new applications in areas such as healthcare, personal fitness or augmented reality. The devices are attached to a person and connected through a Wireless Body Area Network (WBAN), which replaces the wires of traditional monitoring systems by wireless communication. This comes, however, at the cost of turning a reliable communication channel into an unreliable one. The wireless channel is typically a rather unstable medium for communication and the conditions under which WBANs have to operate are particularly harsh: not only is the channel strongly influenced by the movements of the person, but WBANs also often operate in unlicensed frequency bands and may therefore be exposed to a significant amount of interference from other wireless devices. Yet, many envisioned WBAN applications require reliable data transmission. The goals of this thesis are twofold: first, we aim at establishing a better understanding of how the specific WBAN operating conditions, such as node placement on the human body surface and user mobility, impact intra-WBAN communication. We show that during periodic activities like walking the received signal strength on an on-body communication link fluctuates strongly, but signal strength peaks often follow a regular pattern. Furthermore, we find that in comparison to the effects of fading 2.4 GHz Radio Frequency (RF) interference causes relatively little packet loss - however, urban 2.4 GHz RF noise is bursty (correlated in time), which may be problematic for applications with low latency bounds. The second goal of this thesis is to analyze how communication reliability in WBANs can be improved without sacrificing a significant amount of additional energy. To this end, we first explore the trade-off between communication latency and communication reliability. This analysis is based on a novel packet scheduling algorithm, which makes use of an accelerometer to couple WBAN communication with the movement patterns of the user. The analysis shows that unreliable links can often be made reliable if packets are transmitted at predicted signal strength peaks. In addition, we analyze to what extent two mechanisms can improve robustness against 2.4 GHz RF interference when adopted in a WBAN context: we analyze the benefits of channel hopping, and we examine how the packet retransmission process can be made more efficient by using a novel packet combining algorithm that allows to repair packets corrupted by RF interference. One of the conclusions is that while frequency agility may decrease "burstiness" of errors the static selection of a channel at the upper end of the 2.4 GHz band often already represents a good remedy against RF interference

Integration of robotics and 3D visualization to modernize the Expeditionary Warfare Demonstrator (EWD)

In the summer of 2008, the Commandant of the Marine Corps (CMC) released a message to all Marines and Sailors detailing plans to revitalize U.S. naval amphibious competency. Current responsibilities in Iraq and Afghanistan have significantly reduced available training time causing overall amphibious readiness to suffer. In response, this thesis evaluates 3D visualization techniques and other virtual environment technologies available to support these mission-critical training goals. The focus of this research is to modernize the Expeditionary Warfare Demonstrator (EWD) located aboard Naval Amphibious Base (NAB) Little Creek, Virginia. The EWD has been used to demonstrate doctrine, tactics, and procedures for all phases of amphibious operations to large groups of Navy, Marine Corps, Joint, Coalition and civilian personnel for the last 55 years. However, it no longer reflects current doctrine and is therefore losing credibility and effectiveness. In its current configuration, the EWD is limited to a single training scenario since the display’s ship models rely on a static pulley system to show movement and the terrain display ashore is fixed. To address these shortfalls, this thesis first recommends the usage of the wireless communication capability within Sun’s Small Programmable Object Technology (SunSPOT) to create robotic vehicles to replace the current ship models. This enables large-group visualization and situational awareness of the numerous coordinated surface maneuvers needed to support Marines as they move from ship to shore. The second recommendation is to improve visualization ashore through the creation of Extensible 3D Graphics (X3D) scenes depicting high-fidelity 3D models and enhanced 3D terrain displays for any location. This thesis shows how to create these scenes and project them from overhead in order to modernize the gymnasium-sized EWD into an amphibious wargaming table suitable for both amphibious staff training and operational planning. Complimentary use of BASE-IT projection tables and digital 3D holography can further provide smallgroup, close-up views of key battlespace locations. It is now possible to upgrade an aging training tool by implementing the technologies recommended in this thesis to support the critical training and tactical needs of the integrated Navy and Marine Corps amphibious fighting force.http://archive.org/details/integrationofrob109454520Outstanding ThesisUS Marine Corps (USMC) author.Approved for public release; distribution is unlimited

Early Abstraction of Inertial Sensor Data for Long-Term Deployments

Advances in microelectronics over the last decades have led to miniaturization of computing devices and sensors. A driving force to use these in various application scenarios is the desire to grasp physical phenomena from the environment, objects and living entities. We investigate sensing in two particularly challenging applications: one where small sensor modules are worn by people to detect their activities, and one where wirelessly networked sensors observe events over an area. This thesis takes a data-driven approach, focusing on human motion and vibrations caused by trains that are captured by accelerometer sensors as time series and shall be analyzed for characteristic patterns. For both, the acceleration sensor must be sampled at relatively high rates in order to capture the essence of the phenomena, and remain active for long stretches of time. The large amounts of gathered sensor data demand novel approaches that are able to swiftly process the data while guaranteeing accurate classification results. The following contributions are made in particular: * A data logger that would suit the requirements of long-term deployments is designed and evaluated. In a power profiling study both hardware components and firmware parameters are thoroughly tested, revealing that the sensor is able to log acceleration data at a sampling rate of 100 Hertz for up to 14 full days on a single battery charge. * A technique is proposed that swiftly and accurately abstracts an original signal with a set of linear segments, thus preserving its shape, while being twice as fast as a similar method. This allows for more efficient pattern matching, since for each pattern only a fraction of data points must be considered. A second study shows that this algorithm can perform data abstraction directly on a data logger with limited resources. * The railway monitoring scenario requires streaming vibration data to be analyzed for particular sparse and complex events directly on the sensor node, extracting relevant information such as train type or length from the shape of the vibration footprint. In a study conducted on real-world data, a set of efficient shape features is identified that facilitates train type prediction and length estimation with very high accuracies. * To achieve fast and accurate activity recognition for long-term bipolar patients monitoring scenarios, we present an approach that relies on the salience of motion patterns (motifs) that are characteristic for the target activity. These motifs are accumulated by using a symbolic abstraction that encodes the shape of the original signal. A large-scale study shows that a simple bag-of-words classifier trained with extracted motifs is on par with traditional approaches regarding the accuracy, while being much faster. * Some activities are hard to predict from acceleration data alone with the aforementioned approach. We argue that human-object interactions, captured as human motion and grasped objects through RFID, are an ideal supplement. A custom bracelet-like antenna to detect objects from up to 14 cm is proposed, along with a novel benchmark to evaluate such wearable setups. By aiming for wearable and wirelessly networked sensor systems, these contributions apply for particularly challenging applications that require long-term deployments of miniature sensors in general. They form the basis of a framework towards efficient event detection that relies heavily on early data abstraction and shape-based features for time series, while focusing less on the classification techniques

Optimization-Based Methodology for the Exploration of Cyber-Physical System Architectures

In this thesis, we address the design space exploration of cyber-physical system architectures to select correct-by-construction configuration and interconnection of system components taken from pre-defined libraries. We formulate the exploration problem as a mapping problem and use optimization to solve it by searching for a minimum cost architecture that meets system requirements. Using a graph-based representation of a system architecture, we define a set of generic mixed integer linear constraints over graph vertices, edges and paths, and use these constraints to instantiate a variety of design requirements (e.g., interconnection, flow, workload, timing, reliability, routing). We implement a comprehensive toolbox that supports all steps of the proposed methodology. It provides a pattern-based formal language to facilitate requirements specification and a set of scalable algorithms for encoding and solving exploration problems. We prove our concepts on a set of case studies for different cyber-physical system domains, such as electrical power distribution networks, reconfigurable industrial production lines and wireless sensor networks

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

An investigation of mobile ad-hoc network performance with cognitive attributes applied

Mobile Ad-Hoc Networks (MANETs) are known for their versatility, which is they are capable of supporting many applications. In addition to this versatility MANETs are quick to deploy without need for an existing predefined communications infrastructure. However, although the lack of infrastructure allows for the quick deployment of the data communications network, it adds many factors that hinder packet delivery. Such hindrances occur because of the dynamic topology caused by the mobility of the nodes which results in link breakages. Routing protocols exist that attempt to refresh available routes; however, this is after link breakages have occurred. The nodes also usually have constrained resources (i.e. energy source and limited bandwidth). This thesis presents a novel approach of network behaviour and management by implementing cognitive attributes into a MANET environment. This allows an application to better meet its mission objectives, decreases the end-to-end delay, and increases packet delivery ratio. The network is able to make observations, consider previous actions and consequences of the actions, and make changes based on the prior knowledge and experience. This work also shows how the network can better utilise limited resources such as bandwidth allocation by applying cognitive attributes. Simulations conducted show promising results and prove that an increase in network performance is possible if adopting a cross-layered approach and allow the network to manage and to ‘think’ for itself. Various simulations were run with various scenarios and results are presented without cognition applied, with partial cognition applied and with full cognition applied. A total of 52 simulations were run and from this the results were compared and contrasted. The analysis shows that cognitive attributes does increase network performance in the majority of applications