Networking protocols for long life wireless sensor networks

My original contribution to knowledge is the creation of a WSN system that further improves the functionality of existing technology, whilst achieving improved power consumption and reliability. This thesis concerns the development of industrially applicable wireless sensor networks that are low-power, reliable and latency aware. This work aims to improve upon the state of the art in networking protocols for low-rate multi-hop wireless sensor networks. Presented is an application-driven co-design approach to the development of such a system. Starting with the physical layer, hardware was designed to meet industry specified requirements. The end system required further investigation of communications protocols that could achieve the derived application-level system performance specifications. A CSMA/TDMA hybrid MAC protocol was developed, leveraging numerous techniques from the literature and novel optimisations. It extends the current art with respect to power consumption for radio duty-cycled applications, and reliability, in dense wireless sensor networks, whilst respecting latency bounds. Specifically, it provides 100% packet delivery for 11 concurrent senders transmitting towards a single radio duty cycled sink-node. This is representative of an order of magnitude improvement over the comparable art, considering MAC-only mechanisms. A novel latency-aware routing protocol was developed to exploit the developed hardware and MAC protocol. It is based on a new weighted objective function with multiple fail safe mechanisms to ensure extremely high reliability and robustness. The system was empirically evaluated on two hardware platforms. These are the application-specific custom 868 MHz node and the de facto community-standard TelosB. Extensive empirical comparative performance analyses were conducted against the relevant art to demonstrate the advances made. The resultant system is capable of exceeding 10-year battery life, and exhibits reliability performance in excess of 99.9%.

Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.

A policy analysis of key employability interventions for the educationally disadvantaged in further education: Comparative insights for Irish education

The aim of this study is to garner comparative insights so as to aid the development of the discourse on further education (FE) conceptualisation and the relationship of FE with educational disadvantage and employability. This aim is particularly relevant in Irish education parlance amidst the historical ambiguity surrounding the functioning of FE. The study sets out to critically engage with the education/employability/economy link (eee link). This involves a critique of issues relevant to participation (which extends beyond student activity alone to social relations generally and the dialogic participation of the disadvantaged), accountability (which extends beyond performance measures alone to encompass equality of condition towards a socially just end) and human capital (which extends to both collective and individual aspects within an educational culture). As a comparative study, there is a strong focus on providing a way of conceptualising and comparatively analysing FE policy internationally. The study strikes a balance between conceptual and practical concerns. A critical comparative policy analysis is the methodology that structures the study which is informed and progressed by a genealogical method to establish the context of each of the jurisdictions of England, the United States and the European Union. Genealogy allows the use of history to diagnose the present rather than explaining how the past has caused the present. The discussion accentuates the power struggles within education policy practice using what Fairclough calls a strategic critique as well as an ideological critique. The comparative nature of the study means that there is a need to be cognizant of the diverse cultural influences on policy deliberation. The study uses the theoretical concept of paradigmatic change to critically analyse the jurisdictions. To aid with the critical analysis, a conceptual framework for legislative functions is developed so as to provide a metalanguage for educational legislation. The specific contribution of the study, while providing a manner for understanding and progressing FE policy development in a globalized Ireland, is to clear the ground for a more well-defined and critically reflexive FE sector to operate and suggests a number of issues for further deliberation.

A comparative study of the structural, mechanical and tribological characteristics of TiSiC-Cr coatings prepared in CH4 and C2H2 reactive atmosphere by cathodic vacuum arc

TiSiC-Cr coatings, with Cr and Si as additional elements, were deposited on Si, C 45 and 316 L steel substrates via cathodic arc evaporation. Two series of coatings with thicknesses in the range of 3.6–3.9 μm were produced, using either CH4 or C2H2 as carbon containing gas. For each series, different coatings were prepared by varying the carbon rich gas flow rate between 90 and 130 sccm, while maintaining constant cathode currents (110 and 100 A at TiSi and Cr cathodes, respectively), substrate bias (–200 V) and substrate temperature (∼320 °C). The coatings were analyzed for their mechanical characteristics (hardness, adhesion) and tribological performance (friction, wear), along with their elemental and phase composition, chemical bonds, crystalline structure and cross-sectional morphology. The coatings were found to be formed with nano-scale composite structures consisting of carbide crystallites (grain size of 3.1–8.2 nm) and amorphous hydrogenated carbon. The experimental results showed significant differences between the two coating series, where the films formed from C2H2 exhibited markedly superior characteristics in terms of microstructure, morphology, hardness, friction behaviour and wear resistance. For the coatings prepared using CH4, the measured values of crystallite size, hardness, friction coefficient and wear rate were in the ranges of 7.2–8.2 nm, 26–30 GPa, 0.3–0.4 and 2.1–4.8 × 10−6 mm3 N−1 m−1, respectively, while for the coatings grown in C2H2, the values of these characteristics were found to be in the ranges of 3.1–3.7 nm, 41–45 GPa, 0.1–0.2 and 1.4–3.0 × 10−6 mm3 N−1 m−1, respectively. Among the investigated coatings, the one produced using C2H2 at the highest flow rate (130 sccm) exhibited the highest hardness (45.1 GPa), the lowest friction coefficient (0.10) and the best wear resistance (wear rate of 1.4 × 10−6 mm3 N−1 m−1).