An elementary proposition on the dynamic routing problem in wireless networks of sensors

The routing problem (finding an optimal route from one point in a computer network to another) is surrounded by impossibility results. These results are usually expressed as lower and upper bounds on the set of nodes (or the set of links) of a network and represent the complexity of a solution to the routing problem (a routing function). The routing problem dealt with here, in particular, is a dynamic one (it accounts for network dynamics) and concerns wireless networks of sensors. Sensors form wireless links of limited capacity and time-variable quality to route messages amongst themselves. It is desired that sensors self-organize ad hoc in order to successfully carry out a routing task, e.g. provide daily soil erosion reports for a monitored watershed, or provide immediate indications of an imminent volcanic eruption, in spite of network dynamics. Link dynamics are the first barrier to finding an optimal route between a node x and a node y in a sensor network. The uncertainty of the outcome (the best next hop) of a routing function lies partially with the quality fluctuations of wireless links. Take, for example, a static network. It is known that, given the set of nodes and their link weights (or costs), a node can compute optimal routes by running, say, Dijkstra's algorithm. Link dynamics however suggest that costs are not static. Hence, sensors need a metric (a measurable quantity of uncertainty) to monitor for fluctuations, either improvements or degradations of quality or load; when a fluctuation is sufficiently large (say, by Delta), sensors ought to update their costs and seek another route. Therein lies the other fundamental barrier to find an optimal route - complexity. A crude argument would suggest that sensors (and their links) have an upper bound on the number of messages they can transmit, receive and store due to resource constraints. Such messages can be application traffic, in which case it is desirable, or control traffic, in which case it should be kept minimal. The first type of traffic is demand, and a user should provision for it accordingly. The second type of traffic is overhead, and it is necessary if a routing system (or scheme) is to ensure its fidelity to the application requirements (policy). It is possible for a routing scheme to approximate optimal routes (by Delta) by reducing its message and/or memory complexity. The common denominator of the routing problem and the desire to minimize overhead while approximating optimal routes is Delta, the deviation (or stretch) of a computed route from an optimal one, as computed by a node that has instantaneous knowledge of the set of all nodes and their interaction costs (an oracle). This dissertation deals with both problems in unison. To do so, it needs to translate the policy space (the user objectives) into a metric space (routing objectives). It does so by means of a cost function that normalizes metrics into a number of hops. Then it proceeds to devise, design, and implement a scheme that computes minimum-hop-count routes with manageable complexity. The theory presented is founded on (well-ordered) sets with respect to an elementary proposition, that a route from a source x to a destination y can be computed either by y sending an advertisement to the set of all nodes, or by x sending a query to the set of all nodes; henceforth the proactive method (of y) and the reactive method (of x), respectively. The debate between proactive and reactive routing protocols appears in many instances of the routing problem (e.g. routing in mobile networks, routing in delay-tolerant networks, compact routing), and it is focussed on whether nodes should know a priori all routes and then select the best one (with the proactive method), or each node could simply search for a (hopefully best) route on demand (with the reactive method). The proactive method is stateful, as it requires the entire metric space - the set of nodes and their interaction costs - in memory (in a routing table). The routes computed by the proactive method are optimal and the lower and upper bounds of proactive schemes match those of an oracle. Any attempt to reduce the proactive overhead, e.g. by introducing hierarchies, will result in sub-optimal routes (of known stretch). The reactive method is stateless, as it requires no information whatsoever to compute a route. Reactive schemes - at least as they are presently understood - compute sub-optimal routes (and thus far, of unknown stretch). This dissertation attempts to answer the following question: "what is the least amount of state required to compute an optimal route from a source to a destination?" A hybrid routing scheme is used to investigate this question, one that uses the proactive method to compute routes to near destinations and the reactive method for distant destinations. It is shown that there are cases where hybrid schemes can converge to optimal routes, despite possessing incomplete routing state, and that the necessary and sufficient condition to compute optimal routes with local state alone is related neither to the size nor the density of a network; it is rather the circumference (the size of the largest cycle) of a network that matters. Counterexamples, where local state is insufficient, are discussed to derive the worst-case stretch. The theory is augmented with simulation results and a small experimental testbed to motivate the discussion on how policy space (user requirements) can translate into metric spaces and how different metrics affect performance. On the debate between proactive and reactive protocols, it is shown that the two classes are equivalent. The dissertation concludes with a discussion on the applicability of its results and poses some open problems

A move-step analysis of the concluding chapters in computer science phd theses

[EN] This paper describes how computer science doctoral writers construct the closing chapters of their PhD theses. The data are drawn from the chapters playing a concluding role of 48 PhD theses defended at the University of Glasgow from 2008 to 2014. The analysis applied a qualitative-quantitative approach. The titles of the concluding chapters of the theses were first examined and also their divisions into sections and sub-sections. Then the chapters were subjected to a move-step analysis: Move 1 (M1) “Revisiting the study”; Move 2 (M2) “Consolidating research space”; Move 3 (M3) “Proposing practical applications and implications”, Move 4 (M4) “Recommending future work” and Move 5 (M5) “Recapitulating the study”. The results revealed that most of the computer science PhD theses have one final concluding chapter with three main moves: M1, M2 and M4. The most frequent steps are “reviewing the work carried out” and “summarizing the specific work reported in every thesis chapter” in M1, “presenting results and contributions”, “answering the initial research questions or hypotheses”, and “making claims” in M2, and “acknowledging limitations” and “suggesting further research” in M4. Movestep patterns appear in recurrent cycles throughout the concluding chapters. Several suggestions for pedagogical purposes are provided.[ES] Este artículo describe cómo los autores de tesis doctorales en el área de la informática elaboran los capítulos de conclusión. Los datos proceden de los capítulos finales de 48 tesis doctorales defendidas en la Universidad de Glasgow entre 2008 y 2014. Para el análisis se siguió un enfoque cualitativo y cuantitativo. En una primera etapa, se examinaron los títulos de los capítulos de conclusión de las tesis así como sus divisiones en secciones y subsecciones. Posteriormente, se analizaron los capítulos atendiendo a unidades informativas organizadas en movimientos y pasos: Movimiento 1 (M1) “Revisión del estudio”; Movimiento 2 (M2) “Consolidación del espacio de investigación”; Movimiento 3 (M3) “Propuesta de aplicaciones prácticas e implicaciones”, Movimiento 4 (M4) “Recomendaciones para futuras investigaciones” y Movimiento 5 (M5) “Recapitulación del estudio”. Los resultados indican que la mayoría de las tesis de este corpus de informática tiene un único capítulo final de conclusiones con tres movimientos principales: M1, M2 y M4. Los pasos más frecuentes consisten en “revisar el trabajo llevado a cabo” y “resumir el trabajo específico desarrollado en cada capítulo de la tesis” en M1, “enunciar los resultados y las contribuciones en respuesta a las hipótesis y preguntas iniciales” y “reivindicar su aportación” en M2, y “reconocer limitaciones de la investigación” y “sugerir investigaciones futuras” en M4. La práctica habitual consiste en utilizar patrones de movimientos y pasos en ciclos recurrentes a lo largo de la conclusión. Se aportan sugerencias con fines pedagógicos.Soler Monreal, C. (2016). A move-step analysis of the concluding chapters in computer science phd theses. Ibérica. (32):105-132. http://hdl.handle.net/10251/80709S1051323

Rhetorical strategies in PhD conclusions of computer science: From the review of the study to consolidation of research space

[ES] Este artículo analiza los patrones de movimientos que predominan en los capítulos finales de conclusión de 48 tesis doctorales de informática en una universidad británica. Se centra en la naturaleza y frecuencia de las conexiones entre pasos del Movimiento 1 sobre la revisión del trabajo de investigación y los pasos del Movimiento 2, de consolidación del espacio investigador. Las combinaciones más comunes relacionan (1) el resumen del trabajo de la tesis con el producto y su evaluación, (2) el propósito y la hipótesis inicial con los resultados, (3) las preguntas de investigación con la metodología, el producto y la reivindicación, (4) un problema o necesidad con una metodología específica, un nuevo producto y/o una reivindicación, y (5) un resumen del trabajo realizado en cada capítulo con los resultados y reivindicaciones. Algunos de los resultados obtenidos son específicos del área de la informática. Del estudio se desprenden implicaciones pedagógicas para cursos de inglés para fines específicos (IFA).[EN] This study investigates the predominant moves and move patterns used in the separate final conclusion chapters of 48 PhD theses of computer science at a UK university. The focus is on the most salient connections of steps in the review of the study (Move 1) with steps for the consolidation of research space (Move 2). The most common combinations relate (1) a summary of the thesis work to the product and the evaluation of the product, (2) the purpose, thesis statement or hypothesis to the findings or results, (3) the research questions to the methodology, product or claim, (4) a problem or need to a specific methodology, a new product and/or a claim, and (5) a summary of the work done in each thesis chapter to the findings and claims. Some findings are specific of the field of computer science. 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