Toward Open and Programmable Wireless Network Edge

Increasingly, the last hop connecting users to their enterprise and home networks is wireless. Wireless is becoming ubiquitous not only in homes and enterprises but in public venues such as coffee shops, hospitals, and airports. However, most of the publicly and privately available wireless networks are proprietary and closed in operation. Also, there is little effort from industries to move forward on a path to greater openness for the requirement of innovation. Therefore, we believe it is the domain of university researchers to enable innovation through openness. In this thesis work, we introduce and defines the importance of open framework in addressing the complexity of the wireless network. The Software Defined Network (SDN) framework has emerged as a popular solution for the data center network. However, the promise of the SDN framework is to make the network open, flexible and programmable. In order to deliver on the promise, SDN must work for all users and across all networks, both wired and wireless. Therefore, we proposed to create new modules and APIs to extend the standard SDN framework all the way to the end-devices (i.e., mobile devices, APs). Thus, we want to provide an extensible and programmable abstraction of the wireless network as part of the current SDN-based solution. In this thesis work, we design and develop a framework, weSDN (wireless extension of SDN), that extends the SDN control capability all the way to the end devices to support client-network interaction capabilities and new services. weSDN enables the control-plane of wireless networks to be extended to mobile devices and allows for top-level decisions to be made from an SDN controller with knowledge of the network as a whole, rather than device centric configurations. In addition, weSDN easily obtains user application information, as well as the ability to monitor and control application flows dynamically. Based on the weSDN framework, we demonstrate new services such as application-aware traffic management, WLAN virtualization, and security management

Incentive based Residential Demand Aggregation

From the beginning of the twenty-first century, the electrical power industry has moved from traditional power systems toward smart grids. However, with the increasing amount of renewable energy resources integrated into the grid, there is a significant challenge in power system operation due to the intermittency and variability of the renewables. Therefore, the utilization of flexible and controllable demand-side resources to maintain power system efficiency and stability has become a fundamental goal of smart grid initiatives. Meanwhile, due to the development of communication and sensing technologies, intelligent demand-side management with automatic controls enables residential loads to participate in demand response programs. Therefore, the aggregate control of residential appliances is anticipated to be feasible technique in the near future, which will bring considerable benefits to both residential consumers and load-serving entities. Hence, this dissertation proposes a comprehensive optimal framework for incentive based residential demand aggregation. The contents of this dissertation include: 1) a hardware design of smart home energy management system, 2) a new model to assess the responsive residential demand to financial incentives, and 3) an online algorithm for scheduling residential appliances. The proposed framework is expected to generate optimal control strategies over residential appliances enrolled in incentive based DR programs in real time. To residential consumers, this framework will 1) provide easy-to-use smart energy management solution, 2) distribute financial rewards by their quantified contribution in DR events, and 3) maintain residents’ comfort-level expectations based on their energy usage preferences. To LSEs, this framework can 1) aggregate residential demand to enhance system reliability, stability and efficiency, and 2) minimize the total reward costs for executing incentive based DR programs. Since this framework benefits both load serving entities and residents, it can stimulate the potential capability of residential appliances enrolled in incentive based DR programs. Eventually, with the growing number of DR participants, this framework has the potential to be one of the most vital parts in providing effective demand-side ancillary services for the entire power system

A model personal energy meter

Every day each of us consumes a significant amount of energy, both directly through transport, heating and use of appliances, and indirectly from our needs for the production of food, manufacture of goods and provision of services. This dissertation investigates a personal energy meter which can record and apportion an individual's energy usage in order to supply baseline information and incentives for reducing our environmental impact. If the energy costs of large shared resources are split evenly without regard for individual consumption each person minimises his own losses by taking advantage of others. Context awareness offers the potential to change this balance and apportion energy costs to those who cause them to be incurred. This dissertation explores how sensor systems installed in many buildings today can be used to apportion energy consumption between users, including an evaluation of a range of strategies in a case study and elaboration of the overriding principles that are generally applicable. It also shows how second-order estimators combined with location data can provide a proxy for fine-grained sensing. A key ingredient for apportionment mechanisms is data on energy usage. This may come from metering devices or buildings directly, or from profiling devices and using secondary indicators to infer their power state. A mechanism for profiling devices to determine the energy costs of specific activities, particularly applicable to shared programmable devices is presented which can make this process simpler and more accurate. By combining crowdsourced building-inventory information and a simple building energy model it is possible to estimate an individual's energy use disaggregated by device class with very little direct sensing. Contextual information provides crucial cues for apportioning the use and energy costs of resources, and one of the most valuable sources from which to infer context is location. A key ingredient for a personal energy meter is a low cost, low infrastructure location system that can be deployed on a truly global scale. This dissertation presents a description and evaluation of the new concept of inquiry-free Bluetooth tracking that has the potential to offer indoor location information with significantly less infrastructure and calibration than other systems. Finally, a suitable architecture for a personal energy meter on a global scale is demonstrated using a mobile phone application to aggregate energy feeds based on the case studies and technologies developed

15-05 Infrastructure and Technology for Sustainable Livable Cities

Providing access and mobility for key installations and businesses located in cities become a challenge when there is limited public transport and non-motorized facilities. The challenges are significant in cities that are subjected to severe winter weather conditions. Improving access to sustainable mobility choices is a key aspect of developing livable cities. This project scope is limited to identifying methods and infrastructure to promote walking and cycling. With regards to cycling, bike-share program development and use of location-allocation models as planning tools are presented. To minimize exposure to adverse weather conditions, underground and above ground pedestrian systems are provided. These two infrastructure options are explored during this study. Providing energy efficient lighting systems to make pedestrians and cyclists feel safe to travel within cities is paramount to improve mobility. Energy efficient lighting systems, cost of implementation, and planning tools are discussed. In winter cities, providing snow and ice free streets and walkways promote walking and cycling. Technologies used for such endeavors and implementation case studies are presented. Electricity needed to operate kiosks at bike-share stations, pedestrian lighting, and snow melting systems can be generated through renewable sources. Solar and wind are two such resources discussed in this report. Also, a few tools that can be used for identifying optimal locations for placing solar and wind sensitive infrastructure are presented

Behaviour change techniques: the development and evaluation of a taxonomic method for reporting and describing behaviour change interventions (a suite of five studies involving consensus methods, randomised controlled trials and analysis of qualitative data)

Background Meeting global health challenges requires effective behaviour change interventions (BCIs). This depends on advancing the science of behaviour change which, in turn, depends on accurate intervention reporting. Current reporting often lacks detail, preventing accurate replication and implementation. Recent developments have specified intervention content into behaviour change techniques (BCTs) – the ‘active ingredients’, for example goal-setting, self-monitoring of behaviour. BCTs are ‘the smallest components compatible with retaining the postulated active ingredients, i.e. the proposed mechanisms of change. They can be used alone or in combination with other BCTs’ (Michie S, Johnston M. Theories and techniques of behaviour change: developing a cumulative science of behaviour change. Health Psychol Rev 2012;6:1–6). Domain-specific taxonomies of BCTs have been developed, for example healthy eating and physical activity, smoking cessation and alcohol consumption. We need to build on these to develop an internationally shared language for specifying and developing interventions. This technology can be used for synthesising evidence, implementing effective interventions and testing theory. It has enormous potential added value for science and global health. Objective (1) To develop a method of specifying content of BCIs in terms of component BCTs; (2) to lay a foundation for a comprehensive methodology applicable to different types of complex interventions; (3) to develop resources to support application of the taxonomy; and (4) to achieve multidisciplinary and international acceptance for future development. Design and participants Four hundred participants (systematic reviewers, researchers, practitioners, policy-makers) from 12 countries engaged in investigating, designing and/or delivering BCIs. Development of the taxonomy involved a Delphi procedure, an iterative process of revisions and consultation with 41 international experts; hierarchical structure of the list was developed using inductive ‘bottom-up’ and theory-driven ‘top-down’ open-sort procedures (n = 36); training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161) was evaluated by changes in intercoder reliability and validity (agreement with expert consensus); evaluating the taxonomy for coding interventions was assessed by reliability (intercoder; test–retest) and validity (n = 40 trained coders); and evaluating the taxonomy for writing descriptions was assessed by reliability (intercoder; test–retest) and by experimentally testing its value (n = 190). Results Ninety-three distinct, non-overlapping BCTs with clear labels and definitions formed Behaviour Change Technique Taxonomy version 1 (BCTTv1). BCTs clustered into 16 groupings using a ‘bottom-up’ open-sort procedure; there was overlap between these and groupings produced by a theory-driven, ‘top-down’ procedure. Both training methods improved validity (both p < 0.05), doubled the proportion of coders achieving competence and improved confidence in identifying BCTs in workshops (both p < 0.001) but did not improve intercoder reliability. Good intercoder reliability was observed for 80 of the 93 BCTs. Good within-coder agreement was observed after 1 month (p < 0.001). Validity was good for 14 of 15 BCTs in the descriptions. The usefulness of BCTTv1 to report descriptions of observed interventions had mixed results. Conclusions The developed taxonomy (BCTTv1) provides a methodology for identifying content of complex BCIs and a foundation for international cross-disciplinary collaboration for developing more effective interventions to improve health. Further work is needed to examine its usefulness for reporting interventions. Funding This project was funded by the Medical Research Council Ref: G0901474/1. Funding also came from the Peninsula Collaboration for Leadership in Applied Health Research and Care

Growing a Green Economy for All: From Green Jobs to Green Ownership

This Democracy Collaborative report provides the first comprehensive survey of community wealth building institutions in the green economy. Featuring ten cases, the report identifies how policy and philanthropy can build on these examples to create "green jobs you can own.

A multidisciplinary research approach to energy-related behavior in buildings

Occupant behavior in buildings is one of the key drivers of building energy performance. Closing the “performance gap” in the building sector requires a deeper understanding and consideration of the “human factor” in energy usage. For Europe and US to meet their challenging 2020 and 2050 energy and GHG reduction goals, we need to harness the potential savings of human behavior in buildings, in addition to deployment of energy efficient technologies and energy policies for buildings. Through involvement in international projects such as IEA ECBC Annex 53 and EBC Annex 66, the research conducted in the context of this thesis provided significant contributions to understand occupants’ interactions with building systems and to reduce their energy use in residential and commercial buildings over the entire building life cycle. The primary goal of this Ph.D. study is to explore and highlight the human factor in energy use as a fundamental aspect influencing the energy performance of buildings and maximizing energy efficiency – to the same extent as technological innovation. Scientific literature was reviewed to understand state-of-the-art gaps and limitations of research in the field. Human energy-related behavior in buildings emerges a stochastic and highly complex problem, which cannot be solved by one discipline alone. Typically, a technological-social dichotomy pertains to the human factor in reducing energy use in buildings. Progressing past that, this research integrates occupant behavior in a multidisciplinary approach that combines insights from the technical, analytical and social dimension. This is achieved by combining building physics (occupant behavior simulation in building energy models to quantify impact on building performance) and data science (data mining, analytics, modeling and profiling of behavioral patterns in buildings) with behavioral theories (engaging occupants and motivating energy-saving occupant behaviors) to provide multidisciplinary, innovative insights on human-centered energy efficiency in buildings. The systematic interconnection of these three dimensions is adopted at different scales. The building system is observed at the residential and commercial level. Data is gathered, then analyzed, modeled, standardized and simulated from the zone to the building level, up to the district scale. Concerning occupant behavior, this research focuses on individual, group and collective actions. Various stakeholders can benefit from this Ph.D. dissertation results. Audience of the research includes energy modelers, architects, HVAC engineers, operators, owners, policymakers, building technology vendors, as well as simulation program designers, implementers and evaluators. The connection between these different levels, research foci and targeted audience is not linear among the three observed systems. Rather, the multidisciplinary research approach to energy-related behavior in buildings proposed by this Ph.D. study has been adopted to explore solutions that could overcome the limitations and shortcomings in the state-of-the-art research