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Wireless network technology has advanced to the point that it is possible to use Internet connectivity to perform job tasks while moving in a city. We simulate and experimentally evaluate Dunham&rsquo / s Kangaroo Transaction (KT) model, and a modified version of it. Our results show that the modified-KT model does not have much communication overhead (although more than the original KT model) and it is more resilient to failures of base stations.

The aim of this paper is to find an algorithm to establish and maintain a virtual enclosure around a mobile unit. The area may take any form and should be scalable up to and including national borders. The enclosure is managed on the mobile unit. The target system is Android. Smartphones, tablets and more recently, cameras is examples of mobile units. A modern mobile unit is part of a computer network. It is designed to be connected all the time. A mobile unit have the capability to handle large volumes of data, data that might be both sensitive and possess an economic value. Management of mobile units is vital to protect the data and insure security for the entire network. A mobile unit is a resource in the network. Each resource is defined by a set of parameters. One parameter that make a mobile unit special is the lack of physical boundaries to world. Typically, the first step in security is access control to resources. Therefore, the lack of physical access control has to be replaced by other means such as tracking the location of the mobile unit. In this paper I have studied the possibility of creating a virtual fence around the mobile unit. The mobile unit is free to move within the area enclosed by the virtual fence. The mobile unit alert all concerned parties if it crossed the fence and thus leave the enclosed area. The aim was to find a practical algorithm to establish and maintain a virtual fence around the mobile device. A grid-based algorithm was selected because it can handle small to very large areas. All data are collected in a table which makes the algorithm fast, regardless the size of the area. A grid enables management of multiple enclosures and relationships between them. Deeper analysis revealed that the mobile device is not able to position sufficiently often and accurately for the grid-based algorithm to handle small areas. A complementary method is needed for minimizing the need for positioning. To manage properties, such as geographical information, the selected algorithm is deemed to be well suited. / Telefon: 0734 097 404 Skype: di98jgu

Made available in DSpace on 2014-12-17T14:53:02Z (GMT). No. of bitstreams: 1 JoaoPLN_DISSERT.pdf: 2086259 bytes, checksum: 2a57554e118e00d9a44cdf572e29af7a (MD5) Previous issue date: 2010-12-23 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This paper presents metaheuristic strategies based on the framework of evolutionary algorithms (Genetic and Memetic) with the addition of Technical Vocabulary Building for solving the Problem of Optimizing the Use of Multiple Mobile Units Recovery of Oil (MRO units). Because it is an NP-hard problem, a mathematical model is formulated for the problem, allowing the construction of test instances that are used to validate the evolutionary metaheuristics developed / O presente trabalho apresenta estrat?gias metaheur?sticas baseadas no framework dos Algoritmos Evolutivos (Gen?ticos e Mem?ticos) com a adi??o da t?cnica Vocabulary Building para a resolu??o do Problema de Otimiza??o do Emprego de Unidades M?veis de Pistoneio (UMPs). Por se tratar de um problema NP-?rduo, uma modelagem matem?tica ? formulada para o problema, permitindo a constru??o de inst?ncias testes que s?o utilizadas para validar as metaheur?sticas evolutivas desenvolvidas