With a nation-wide aim toward reducing operational energy costs in buildings, it is important to understand the dynamics of controlled heating, cooling, and air circulation of an individual room, the "One-Room Model Problem." By understanding how one most efficiently regulates a room's climate, one can use this knowledge to help develop overall best-practice power reduction strategies. A key toward effectively analyzing the "One-Room Model Problem" is to understand the capabilities and limitations of existing commercial tools designed for similar problems. In this thesis we develop methodology to link commercial Computational Fluid Dynamics (CFD) software COMSOL with standard computational mathematics software MATLAB, and design controllers that apply inlet airflow and heating or cooling to a room and investigate their effects. First, an appropriate continuum model, the Boussinesq System, is described within the framework of this problem. Next, abstract and weak formulations of the problem are described and tied to a Finite Element Method (FEM) approximation as implemented in the interface between COMSOL and MATLAB. A methodology is developed to design Linear Quadratic Regulator (LQR) controllers and associated functional gains in MATLAB which can be implemented in COMSOL. These "closed-loop" methods are then tested numerically in COMSOL and compared against "open-loop" and average state closed-loop controllers. / Ph. D.

With the progression of computer networks extending boundaries and joining distant locations, wireless sensor networks (WSNs) emerge as the new frontier in developing opportunities to collect and process data from remote locations. WSNs rely on hardware simplicity to make sensor field deployments both affordable and long-lasting without maintenance support. WSN designers strive to extend network lifetimes while meeting application-specific throughput and latency requirements. Effective power management places sensor nodes into one of the available energy-saving modes based upon the sleep period duration and the current state of the radio. This research investigates energy-efficient medium access control (MAC) protocols designed to extend both the lifetime and range of wireless sensor networks. These networks are deployed in remote locations with limited processor capabilities, memory capacities, and battery supplies. The purpose of this research is to develop a new medium access control protocol which performs both cluster management and inter-network gateway functions in an energy-efficient manner. This new protocol, Gateway MAC (GMAC), improves on existing sensor MAC protocols by not only creating additional opportunities to place the sensor platforms into lower power-saving modes, but also by establishing a traffic rhythm which extends the sleep duration to minimize power mode transition costs. Additionally, this research develops a radio power management (RPM) algorithm to provide a new mechanism for all WSN MAC protocols to optimize sleep transition decisions based upon the power and response characteristics of the sensor platform's transceiver. Finally, to extend access to sensor data in remote locations, this research also validates an innovative wireless distribution system which integrates wireless sensor networks, mobile ad hoc networks (MANET), and the Internet. This research makes two significant contributions to the state-of-the-art wireless sensor networks. First, GMAC's centralized network management function offers significant energy savings and network lifetime extensions over existing wireless sensor network protocols. The second contribution is the introduction of a wireless sensor radio power management algorithm designed to exploit additional power-saving opportunities introduced with the newest generation of faster sensor platform transceivers. / Ph. D.

This research investigated methods to determine appropriate security protocols for specific wireless network applications. The specific problem being addressed was that there are tradeoffs between security, performance, and efficiency among current and proposed security protocols. Performance and efficiency issues are particularly important in wireless networks which tend to have constrained network capacity and connect to resource-limited nodes. Existing security protocols address problems such as authentication, availability, confidentiality, integrity, and non-repudiation. However, these protocols use resources and limit the efficient use of node resources. Thus, the overall objective of this research is to improve the efficiency of security mechanisms for wireless networks. A methodology was constructed to satisfy this objective and is an important contribution of this research. The methodology can be used to define the relevant operational parameters of different wireless network applications, classify wireless networks into distinct categories, incorporate appropriate security protocols to a category, and analyze the security protocols through metrics. Three groups of operational parameters were created to classify wireless networks; these are equipment, network topology, and communication characteristics. The wireless network categories include, but are not limited to, fixed broadband wireless networks, wireless local area networks, mobile ad hoc networks, and small device sensor networks. The metrics in the methodology are used to measure end-to-end data throughput and delay, efficiency and overhead, power and energy consumption, and energy consumed per packet transferred. The main advantage of this methodology is the flexibility of how constraints are considered and suitability is analyzed. This approach can identify problems from manageable categories of networks and find or create solutions for each of them. Another advantage of this methodology is that after suitable security protocols are found or created for each category, any new wireless network application that falls into an existing category may be able to use the security protocols from that category and find that they are the most suitable. Another key contribution of this research was the implementation and evaluation of a context aware and adaptive security manager (CASM) that selects appropriate protocols in real-time. CASM was developed using the methodology as a guide. Results from a resource analysis of four encryption algorithms were utilized for the design of CASM. A feasibility study of CASM was then completed. Three different experimental scenarios were used to evaluate CASM's operation. The results and analysis of the experiments indicate that the security manager functions properly and security is provided efficiently with different user settings and environments. Three schemes were deemed the best to use for the decision module of CASM. / Ph. D.

The slowdown of Moore's Law opened a new era of computer research and development. Researchers started exploring alternatives to the traditional CPU design. A constant increase in consumer demands led to the development of CMPs, GPUs, and FPGAs. Recent research proposed the development of heterogeneous-ISA systems and implemented the necessary systems software to make such systems functional. Evaluations have shown that heterogeneous-ISA systems can offer better throughput and energy efficiency than homogeneous-ISA systems. Due to their low cost, ARM servers are now being adopted in data centers (e.g., AWS Graviton). While prior work provided the infrastructure necessary to run applications on heterogeneous-ISA systems, their dependency on a specialized kernel and a custom compiler increases deployment and maintenance costs. This thesis presents HetMigrate, a framework to live-migrate Linux processes over heterogeneous-ISA systems. HetMigrate integrates with CRIU, a Linux mechanism for process migration, and runs on stock Linux operating systems which improves its deployability. Furthermore, HetMigrate transforms the process's state externally without instrumenting state transformation code into the process binaries which has security benefits and also improves deployability. Our evaluations on Redis server and NAS Parallel Benchmarks show that HetMigrate takes an average of 720ms to fully migrate a process across ISAs while maintaining its state. Moreover, live-migrating with HetMigrate reduces the attack surface of a process by up to 72.8% compared to prior work. Additionally, HetMigrate is easier to deploy in real-world systems compared to prior work. To prove the deployability we ran HetMigrate on a variety of environments like cloud instances (e.g. Cloud Lab), local setups virtualized with QEMU/KVM, and a server-embedded board pair. Similar to works in the past, we also evaluated the energy and throughput benefits that heterogeneous-ISA systems can offer by connecting a Xeon server to three embedded boards over the network. We observed that selectively offloading compute-intensive workloads to embedded boards can increase energy efficiency by up to 39% and throughput by up to 52% while increasing the cost by just 10%. / Master of Science / In 1965 Gordon Moore predicted that the number of transistors in a chip will double every two years. Commonly referred to as "Moore's Law" it no longer holds true and its slowdown opened a new era of computer research and development. Researchers started exploring alternatives to traditional computer designs. A constant increase in consumer demands led to the development of portable, faster, and cheaper computers. Some researchers also started exploring the performance and energy benefits of computing systems that had heterogeneous architecture. Instruction Set Architecture (ISA) is the interface between software and hardware. Recent research proposed the development of systems that had cores of different ISA and implemented the necessary software to make such systems functional. Evaluations have shown that heterogeneous-ISA systems can offer better throughput and energy efficiency than traditional systems. To decrease their cost-to-performance ratio data centers have started adopting servers belonging to diverse architectures making them heterogeneous in nature. While prior work provided the infrastructure necessary to run applications on heterogeneous systems, it suffered from deployability limitations. This thesis presents HetMigrate, a framework that enables stateful program migration in heterogeneous systems. HetMigrate runs on stock open-source operating systems which makes it easy to deploy. Our evaluations show that while HetMigrate performs two orders of magnitude slower than prior work, it can be deployed with ease.

Climate change, uncertainties in energy prices, and the Covid-19 pandemic have significantly reshaped building management, highlighting the need for energy-efficient, safe, and comfortable indoor environments. With advancements in Internet of Things (IoT) sensors and Artificial Intelligence (AI) techniques, optimising building performance now includes forecasting key parameters and intelligently controlling Heating, Ventilation and Air Conditioning (HVAC) systems. However, existing studies often lack practical applicability in real-world scenarios, typically relying on extensive data collection or tailored physical/mathematical models, with limited focus on deployment, scalability, and long-term performance. This thesis addresses the problem from a different angle, proposing an adaptive and practical AI-based solution for energy-efficient comfort optimisation in indoor environments. The designed approach continuously learns from the monitored environment through collected data and requires minimal human effort for configuration and maintenance. The contributions are as follows: i) a method for accurately predicting key parameters using a limited window of data, with a dynamic mechanism to keep the AI model current with environmental changes and operational in a short time frame, and ii) a novel algorithm called EECO for automated and intelligent HVAC control, driven by continuous short-term decisions based on long-term predictions to balance thermal comfort and energy consumption, with no need for preliminary knowledge of the local environment. Evaluation results demonstrate that the proposed approach achieves high prediction accuracy, ensures desired thermal comfort, and reduces the energy footprint by up to approximately 16% in a real-world environment, in addition to potentially saving on operating costs.

Buildings account for 40% of energy consumption in the US. Despite all improvements in buildings shell, equipment, and design, CO2 emissions from buildings are increasing as a result of increased energy consumption. Since occupants spend more than 90% of their time indoors, they are inseparable and significant elements of building system dynamics. Hence, there is a great potential for energy efficiency in buildings using a wide range of programs such as education, intervention, energy feedback, etc. Due to advancement of technology and accessibility of high resolution energy consumption data, utility companies are enabled to focus on implementing energy feedback programs to induce energy efficiency and reduce the peak energy load in the commercial and residential sector. In order to better understand various aspects of energy feedback programs, in the first chapter of this dissertation, I conduct a comprehensive literature review on the state-of-the-art energy feedback study methods and identify gaps of knowledge and challenges faced by researchers in the field. Accordingly, the future research vision is laid out at the intersection of methods and gaps of knowledge used in energy feedback studies and future research opportunities and questions are provided. One of the major gaps of knowledge I identified in the literature review is the lack of quantitative analyses used to investigate the variability of occupant responses to commercial buildings energy feedback programs to evaluate the need for targeted and tailored energy feedback programs. In the second chapter, I conducted a comprehensive analysis on occupant energy-use responses under the influence of a uniform energy feedback program. Furthermore, I investigated the effectiveness of notifications on increasing the level of engagement of the occupants in these studies. The results supported the existence of a variability in responses and engagement level in a uniform energy feedback program which may be due to intra-class variability of occupant behavior. In the third chapter, based on the established need for a targeted energy feedback program, I investigate the predictability of occupant energy consumption behavior and its correlation with energy consumption. The results report that 46% of occupants may be good candidates for targeted energy feedback programs due to their combination of higher levels of energy-use and predictability of their energy consumption behavior. / Ph. D.

This study explored a 130-passenger advanced turboprop commercial airliner with the purposes of economic feasibility and energy efficiency. A baseline vehicle and a derivative vehicle were researched and analyzed in detail. Based on the findings of this analysis, an advanced future airliner was designed. For the advanced airliner, advanced technologies were suggested and projections of these technology benefits were implemented. Detailed performance analysis was conducted for all three aircraft. The energy efficiency of each vehicle was compared to current and future N+3 aircraft. Lastly, cost analysis was performed to observe the impact of these energy savings. The three existing and future concepts evaluated were: 1) Bombardier 80- passenger Q400 baseline, 2) An expanded 130-passenger Bombardier Q400 termed the Q400XL, and 3) an N+3 advanced 130-passenger turboprop airliner termed the N+3 Airliner. The N+3 Airliner was compared to the SUGAR High, a Boeing/NASA N+3 aircraft, in both fuel efficiency and economic feasibility. The N+3 Airliner was 22 percent more energy efficient. At current oil prices, the N+3 Airliner had nearly identical operating cost. However, at two times current oil prices, the N+3 Airliner has a slight advantage economically. Therefore, as long as the price of oil is above 2011 oil prices, $3.03 per barrel, the N+3 Airliner will be an economically viable option. / Ph. D.

Wireless Sensor Networks (WSNs) are wireless networks that have recently drawn significant research attention since they offer unique benefits and versatility with respect to sensing, allowing low-power and low-cost rapid deployment for many applications that do not need human supervision. WSNs are self-created and self-organized by the collection of a large number of sensor nodes interconnected by multi-hop wireless paths. The sensor nodes are network embedded systems with Integrated Chips (ICs) to allow signal processing and micro-sensing. Each wireless sensor node is a micro-electro-mechanical device and can only be equipped with a limited power reserve. While energy consumption occurs in sensing, data processing and communications, care should be exercised to make the most of the expendable power source for the node. Though considerable research is being done in the area of energy saving techniques for WSNs, most of the proposed techniques have focused on energy awareness at different network layers in WSNs. Furthermore, most of the proposed techniques are based on protocols for mobile ad hoc networks that do not look into the possibility of a cross-layer design strategy that can exploit the unique features of WSNs. There still exists the need for a universal protocol that can be applied to such networks in general. In this thesis, we focus such a research on optimizing the energy consumption by suggesting a novel cross-layer architecture at the network/data-link layer for sensor networks. We have developed a scheme for better and improved energy efficiency in WSNs by combining the ideas of energy-efficient cluster formation and medium access together. Our cross-layer scheme provides good performance in terms of WSN-lifetime, scalability and minimizing network-wide energy consumption. The scheme is based on a collaborative approach supported by formation of dynamic clusters functioning with a traffic aware MAC (medium access control) scheme. Our MAC scheme incorporates a self-learning, traffic adaptive algorithm for varying traffic conditions inherent to the WSNs. The design methodology and results in this thesis aim at producing a reliable and scalable energy-aware sensing network, in spite of node failures, minimizing energy consumption at the same time. / Master of Science

Water infrastructure systems worldwide use large amounts of energy to operate. Energy efficiency efforts are relevant because even relatively small gains in efficiency have the potential to bring significant benefits to these utilities in terms of financial savings and enhanced sustainability and resiliency. In order to achieve higher efficiency levels, energy usage must be measured and controlled. A common tool used to measure energy efficiency in water utilities and perform comparisons between utilities is metric benchmarking. Energy benchmarking scores are intended to measure how efficient water systems are among their peers, in a simple and accurate fashion. Although many different benchmarking methods are currently used, we chose to use the segregated benchmarking scores proposed by Carlson on his research report from 2007 (Carlson, 2007). The research objective is to improve these production energy use and treatment energy use benchmarking scores by analyzing the system's particular characteristics that might skew the results, such as topology, water loss and raw water quality. We propose that benchmarking metrics should be always used within a particular context for each specific utility being analyzed. A complementary score (Thermodynamic Score) was developed to provide context on how energy efficient is the utility not only compared with other utilities, but also compared with the potential maximum efficiency the utility can reach itself. We analyzed eight utilities from Virginia to obtain production and treatment energy use benchmarking scores and also thermodynamic scores using the minimum required energy approach. Benchmarking scores were skewed in 50% of the studied utilities. This means that benchmarking scores should never be used as a black box. The thermodynamic score proved to be useful for measurement of energy efficiency of a water utility on its production phase. In addition, some utilities can detect significant financial saving opportunities using the minimum required energy analysis for production operations. / Master of Science

Yes / Next-generation cellular systems like fth generation (5G) is are expected to experience tremendous tra c growth. To accommodate such tra c demand, there is a need to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a signi cant amount of energy. As a result, cloud radio access networks (C-RAN) have been proposed as anenergy e cient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation technique model is to switch o idle baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low tra c periods and 12% during peak tra c periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.