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.

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.

One of the fundamental building blocks of a mobile application is the ability to persist program data between different invocations. Referred to as persistence, this functionality is commonly implemented by means of persistence frameworks. When choosing a particular framework, Android-the most popular mobile platform-offers a wide variety of options to developers. Unfortunately, the energy, performance, and programming effort trade-offs of these frameworks are poorly understood, leaving the Android developer in the dark trying to select the most appropriate option for their applications. To address this problem, this thesis reports on the results of the first systematic study of six Android persistence frameworks (i.e., ActiveAndroid, greenDAO, OrmLite, Sugar ORM, Android SQLite, and Realm Java) in their application to and performance with popular benchmarks, such as DaCapo. Having measured and analyzed the energy, performance, and programming effort trade-offs for each framework, we present a set of practical guidelines for the developer to choose between Android persistence frameworks. Our findings can also help the framework developers to optimize their products to meet the desired design objectives. / Master of Science

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.

The environmental and economic consequences of climate change are severe and are being exacerbated by increased global carbon emissions. In the United States, buildings account for over 40% of all domestic and 7.4% of all global CO2 emissions and therefore represent an important target for energy conservation initiatives. Even marginal energy savings across all buildings could have a profound effect on carbon emission mitigation. In order to realize the full potential of energy savings in the building sector, it is essential to maximize the energy efficiency of both buildings and the behavior of occupants who occupy them. In this vein, systems that collect and communicate building energy-use information to occupants (i.e. eco-feedback systems) have been demonstrated to motivate building occupants to significantly reduce overall building energy consumption. Furthermore, advancements in building sensor technologies and data processing capabilities have enabled the development of advanced eco-feedback systems that also allow building occupants to share energy-use data with one another and to collectively act to reduce energy consumption. In addition to monitoring building occupant energy-use, these systems are capable of collecting data about specific conservation actions taken by occupants and their interactions with different features of the eco-feedback system. However, despite recent advancements in eco-feedback and building sensor technologies, very few systems have been specifically designed to enable research on the effectiveness of different behavior-based energy conservation strategies in commercial buildings. Consequently, very little research has been conducted on how access to such systems impacts the energy-use behavior of building occupants. In this dissertation, I describe how my research over the past three years has advanced an understanding of how eco-feedback systems can impact the energy-use behavior of commercial building occupants. First, I present a novel eco-feedback system that I developed to connect building occupants over energy-use data and empower them to conserve energy while also collecting data that enables controlled studies to quantify the impacts of a wide variety of energy conservation strategies. Next, I present a commercial building study in which this eco-feedback system was used to investigate the effects of organizational network dynamics on the energy-use of individuals. I then introduce a new set of metrics based on individual energy-use data that enables the classification of individuals and building occupant networks based on their energy-use efficiency and predictability. I describe the principles behind the construction of these metrics and demonstrate how these quantitative measures can be used to increase the efficacy of behavior-based conservation campaigns by enabling targeted interventions. I conclude the dissertation with a discussion about the limitations of my research and the new research avenues that it has enabled. / 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.

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.

This thesis investigates the energy efficiency of the Java collection HashMap withregard to insertions and lookups. Analyzing the default collision resolution technique which is a smart implementation of separate chaining, it also implementstwo other collision resolution techniques — double hashing and coalesced hashing — and compares the three in terms of their energy efficiency. The comparisons are done on their insertions and lookup algorithm both through an empirical study and of their time complexities. One of the findings of this thesis isthe preferred initial table size for energy efficiency which is between 2-5 times larger than the amount of insertions. The results show that during insertion thedefault implementation is more energy efficient especially at higher load factors. With lookups the coalesced hashing algorithm is more efficient but it is sucha small difference compared to the default implementation it is almost negligible. Overall the default implementation is the most energy efficient of the threeand it is not impacted much by load factor. These factors make the default implementation the preferable implementation for most applications, however incases where the load factor does not exceed 0.3, double hashing is the preferableoption as it consumes less energy than the other three.