Constrained Task Assignment and Scheduling on Networks of Arbitrary Topology.

This dissertation develops a framework to address centralized and distributed constrained task assignment and task scheduling problems. This framework is used to prove properties of these problems that can be exploited, develop effective solution algorithms, and to prove important properties such as correctness, completeness and optimality. The centralized task assignment and task scheduling problem treated here is expressed as a vehicle routing problem with the goal of optimizing mission time subject to mission constraints on task precedence and agent capability. The algorithm developed to solve this problem is able to coordinate vehicle (agent) timing for task completion. This class of problems is NP-hard and analytical guarantees on solution quality are often unavailable. This dissertation develops a technique for determining solution quality that can be used on a large class of problems and does not rely on traditional analytical guarantees. For distributed problems several agents must communicate to collectively solve a distributed task assignment and task scheduling problem. The distributed task assignment and task scheduling algorithms developed here allow for the optimization of constrained military missions in situations where the communication network may be incomplete and only locally known. Two problems are developed. The distributed task assignment problem incorporates communication constraints that must be satisfied; this is the Communication-Constrained Distributed Assignment Problem. A novel distributed assignment algorithm, the Stochastic Bidding Algorithm, solves this problem. The algorithm is correct, probabilistically complete, and has linear average-case time complexity. The distributed task scheduling problem addressed here is to minimize mission time subject to arbitrary predicate mission constraints; this is the Minimum-time Arbitrarily-constrained Distributed Scheduling Problem. The Optimal Distributed Non-sequential Backtracking Algorithm solves this problem. The algorithm is correct, complete, outputs time optimal schedules, and has low average-case time complexity. Separation of the task assignment and task scheduling problems is exploited here to ameliorate the effects of an incomplete communication network. The mission-modeling conditions that allow this and the benefits gained are discussed in detail. It is shown that the distributed task assignment and task scheduling algorithms developed here can operate concurrently and maintain their correctness, completeness, and optimality properties.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91527/1/jpjack_1.pd

Myriad : a distributed machine vision application framework

This thesis examines the potential for the application of distributed computing frameworks to industrial and also lightweight consumer-level Machine Vision (MV) applications. Traditional, stand-alone MV systems have many benefits in well-defined, tightly- controlled industrial settings, but expose limitations in interactive, de-localised and small-task applications that seek to utilise vision techniques. In these situations, single-computer solutions fail to suffice and greater flexibility in terms of system construction, interactivity and localisation are required. Network-connected and distributed vision systems are proposed as a remedy to these problems, providing dynamic, componentised systems that may optionally be independent of location, or take advantage of networked computing tools and techniques, such as web servers, databases, proxies, wireless networking, secure connectivity, distributed computing clusters, web services and load balancing. The thesis discusses a system named Myriad, a distributed computing framework for Machine Vision applications. Myriad is composed components, such as image processing engines and equipment controllers, which behave as enhanced web servers and communicate using simple HTTP requests. The roles of HTTP-based distributed computing servers in simplifying rapid development of networked applications and integrating those applications with existing networked tools and business processes are explored. Prototypes of Myriad components, written in Java, along with supporting PHP, Perl and Prolog scripts and user interfaces in C , Java, VB and C++/Qt are examined. Each component includes a scripting language named MCS, enabling remote clients (or other Myriad components) to issue single commands or execute sequences of commands locally to the component in a sustained session. The advantages of server- side scripting in this manner for distributed computing tasks are outlined with emphasis on Machine Vision applications, as a means to overcome network connection issues and address problems where consistent processing is required. Furthermore, the opportunities to utilise scripting to form complex distributed computing network topologies and fully-autonomous federated networked applications are described, and examples given on how to achieve functionality such as clusters of image processing nodes. Through the medium of experimentation involving the remote control of a model train set, cameras and lights, the ability of Myriad to perform traditional roles of fixed, stand-alone Machine Vision systems is supported, along with discussion of opportunities to incorporate these elements into network-based dynamic collaborative inspection applications. In an example of 2D packing of remotely-acquired shapes, distributed computing extensions to Machine Vision tasks are explored, along with integration into larger business processes. Finally, the thesis examines the use of Machine Vision techniques and Myriad components to construct distributed computing applications with the addition of vision capabilities, leading to a new class of image-data-driven applications that exploit mobile computing and Pervasive Computing trends

Contributions to the energy management of industrial refrigeration systems: a data-driven perspective

Nowadays, energy management has gained attention due to the constant increment of energy consumption in industry and the pollution problems that this fact supposes. On this subject, one of the main industrial sectors, the food and beverage, attributes a great percentage of its energy expenditure to the refrigeration systems. Such systems are highly affected by operation conditions and are commonly composed by different machines that are continually interacting. These particularities difficult the successful application of efficient energy management methodologies requiring further research efforts in order to improve the current approaches. In this regard, with the current framework of the Industry 4.0, the manufacturing industry is moving towards a complete digitalization of its process information. Is in this context, where the promising capabilities of the data-driven techniques can be applied to energy management. Such technology can push forward the energy management to new horizons, since these techniques take advantage of the common data acquired in the refrigeration systems for its inner operation to develop new methodologies able to reach higher efficiencies. Accordingly, this thesis focuses its attention on the research of novel energy management methodologies applied to refrigeration systems by means of data-driven strategies. To address this broad topic and with the aim to improve the efficiency of the industrial refrigeration systems, the current thesis considers three main aspects of any energy management methodology: the system performance assessment, the machinery operation improvement and the load management. Therefore, this thesis presents a novel methodology for each one of the three main aspects considered. The proposed methodologies should contemplate the necessary robustness and reliability to be applicable in real refrigeration systems. The experimental results obtained from the validation tests in the industrial refrigeration system, show the significant improvement capabilities in regard with the energy efficiency. Each one of the proposed methodologies present a promising result and can be employed individually or as a whole, composing a great basis for a data-driven based energy management framework.Avui en dia la gestió energètica ha guanyat interès degut a l'increment constant de consum per part de la indústria i els problemes de contaminació que això suposa. En aquest tema, un dels principals sectors industrials, el d'alimentació i begudes, atribueix bona part de percentatge del seu consum als sistemes de refrigeració. Aquests sistemes es veuen altament afectats per les condicions d'operació i habitualment estan formats per diverses màquines que estan continuament interactuant. Aquestes particularitats dificulten l'aplicació exitosa de metodologies d'eficiència energètica, requerint més esforços en recerca per millorar els enfocs actuals. En aquest tema, amb l'actual marc de la Indústria 4.0, la indústria està avançant cap una digitalització total de la informació dels seus processos. És en aquest context, on les capacitats prometedores de les tècniques basades en dades poden ser aplicades per a la gestió energètica. Aquesta tecnologia pot impulsar la gestió energètica cap a nous horitzons, ja que aquestes tècniques aprofiten les dades adquirides usualment en els sistemes de refrigeració per el seu propi funcionament, per a desenvolupar noves metodologies capaces d'obtenir eficiències més elevades. En conseqüència, aquesta tesi centra la seva atenció en la recerca de noves metodologies per a la gestió energètica, aplicades als sistemes de refrigeració i mitjançant estratègies basades en dades. Per abordar aquest ampli tema i amb el propòsit de millorar l'eficiència dels sistemes de refrigeració industrial, la present tesi considera els tres aspectes principals de qualsevol metodologia de gestió energètica: l'avaluació del rendiment del sistema, la millora de l'operació de la maquinària i la gestió de les càrregues. Per tant, aquesta tesi presenta una metodologia nova per a cadascun dels tres aspectes considerats. Les metodologies proposades han de contemplar la robustesa i fiabilitat necessàries per a ser aplicades en un sistema de refrigeració real. Els resultats experimentals obtinguts dels tests de validació fets en un sistema de refrigeració industrial mostren unes capacitats de millora significatives referent a l'eficiència energètica. Cadascuna de les metodologies proposades presenta un resultat prometedor i pot ser aplicada independentment o juntament amb les altres, formant una bona base per un marc de gestió energètica basat en dades

Self management of high density wireless networks

IEEE 802.11 wireless networks are very popular in today’s world. This popularity has been stimulated due to the use of mobile computing devices such as laptops, tablets, and Wi-Fi enabled phones. We can get 802.11 connectivity in schools, squares, parks and other public places. All of these places can have a high concentration of users. Moreover, there are other nonpublic places like lecture halls, hotel ballrooms, and convention centers that are common examples of spaces with high concentration of users in a high-density wireless communications environment. Dense deployments of wireless networks suffer from increased interference and, as a result, bad user experience. The interference caused by the co-channel and adjacent channel interference driven by co-located devices is one of the main issues to address to improve network performance. The limited number of nonoverlapping channels may lead to severe interference scenarios if no appropriated spectrum planning is employed. In this work, we present an in-depth review of research work for the channel allocation strategies. Then, we formalize the channel allocation as a minimization problem of the interference level and we propose three different manners to optimize channel assignment between participating Access Points with the aim to improve network performance. The algorithms that we propose can be classified as local and uncoordinated, coordinated and distributed, and centralized. The local and uncoordinated solution behaves well in our testbed but present oscillatory issues that we tackle with a feedback control technique. Finally, this work presents an evaluation of the strategies, on a testbed and on a simulation environment. In the testbed we demonstrate the practical deployability of the solutions and lead to the conclusion that the local and uncoordinated implementation is worthy to be considered as a good strategy for the channels allocation problem where Access Points works in isolated manner. In the simulation, we test the scalability of both, the coordinated and centralized solution, and we show that they can be deployed in networks with more than thirty Access Points and as a results, we conclude that the centralized implementation is the best strategy to perform optimization decisions for channel allocation in connected networks.Las redes inalámbricas IEEE 802.11 son muy populares en el mundo actual. Esta popularidad ha sido estimulada debido al uso de dispositivos móviles tales como laptops, tablets y teléfonos Wi-Fi compatibles. Se puede tener conectividad 802.11 en escuelas, plazas, parques y otros lugares públicos. Todos estos lugares pueden tener una gran concentración de usuarios. Más aún, hay otros lugares no públicos como las bibliotecas, centros de convenciones, salas de conferencias en hoteles, los cuales también son ejemplo de espacios comunes con una gran concentración de usuarios en entornos de comunicación inalámbrica de alta densidad. Instalaciones de redes cámbricas densas experimentan una interferencia creciente, y como resultado, una mala experiencia de usuario. Las interferencias co-canal y de canal adyacente producidas por dispositivos próximos entre sí, son uno de los principales problemas a abordar para mejorar la performance de la red. El número limitado de canales que no se superponen pueden conducir a escenarios de severa interferencia si no se emplea una planificaci´on apropiada del espectro. En este trabajo, se presenta una revisi´on profunda de los trabajos de investigación para estrategias de asignaci´on de canales. Luego, se formaliza la asignación de canales como un problema de minimización del nivel de interferencia y se proponen tres diferentes maneras para optimizar la asignación de canales entre los Puntos de Acceso participantes con el objetivo de mejorar la performance de la red. Los algoritmos propuestos pueden clasificarse como local y no-coordinado, coordinado y distribuido, y centralizado. La solución local y no- coordinada se comparta de manera aceptable en el prototipo pero presenta problemas de oscilación que se aborda con una técnica de control por retro alimentación. Finalmente, este trabajo presenta una evaluación de las estrategias, en un prototipo y en un entorno de simulación. En el prototipo se demuestra el despliegue práctico de las soluciones y se llega a la conclusi´on que la implementación local y no-coordinada es digna de ser considerada como una buena estrategia para el problema de asignación de canales cuando los Puntos de Acceso trabajan en forma aislada. En la simulación, se prueban la escalabilidad de las soluciones coordinada y centralizada, y se muestra que pueden ser desplegadas en redes con más de treinta Puntos de Acceso y como resultado, se concluye que la implementación centralizada es la mejor estrategia para realizar decisiones de optimizaci´on para la asignaci´on de canales en redes conectadas