Visualisasi Trafik Jaringan Dengan Metode Support Vector Machine (SVM) (Studi Kasus: Universitas Indo Global Mandiri)

Limited network resources and the increasing number of internet users in the current digital era have an impact on high traffic which results in decreased access speed to internet services. This is also a problem that occurs at the Indo Global Mandiri University (UIGM) Palembang, causing access to academic services to be slow. The purpose of this research is to identify the types of network traffic patterns which are then carried out by the process of grouping and visualizing these types of traffic. The data in this study were taken in real-time at the UIGM campus. The data obtained is the result of responses which are then extracted. The extraction results are processed using the Support Vector Machine (SVM) method for the process of grouping and visualizing data. The results of this study can distinguish types of traffic based on communication protocols, namely tcp and udp, where the results of the experiment were carried out six times with the results being the first experiment where 99.7% TCP and 0.1% for UDP, the second experiment 97.6% for TCP and 1.1% for UDP , trial three 99.7 % TCP and 0.2% UDP, trial four 97.5% and 1.3% UDP, trial five 99.5 TCP and 02% UDP, and the sixth or final try 97.7% TCP and 1.1% UDP. The data from the use of the SVM method obtained several types of traffic such as games by 0.4%, mail 0.2%, multimedia 0.4% and the web by 82.8% and this research still produces data that the pattern is not yet recognized by 15.5% Keywords : Network Traffic, Classification, Support Vector Mesi

Diagnóstico em nível de sistema para redes de sensores sem fio : uma heurística

Orientadora : Profª. Drª. Andréa WeberDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 27/08/2015Inclui referências : f. 75-81Resumo: Diagnóstico em nível de sistema e uma sub-área de tolerância a falhas. O objetivo de um algoritmo de diagnostico em nível de sistema e reportar, para todas as unidades sem-falha de um sistema distribuído, o estado das demais unidades do sistema. A di- agnosticabilidade do sistema depende de algumas propriedades topologicas do grafo de diagnostico. Nesse contexto, um assinalamento de testes e um conjunto de testes mótuos entre as n unidades de um sistema. Um sistema com n unidades e dito t-diagnosticavel se o numero de unidades falhas nao ultrapassar t e satisfizer as seguintes condicões: (i) n > 2t + 1; e (ii) cada unidade for testada por, no mínimo, t outras unidades. Um sistema t-diagnosticóvel e definido como ótimo se n = 2t + 1. Considera-se o problema da definicao de um assinalamento de testes para a identificaçao de nós com falha em uma Rede de Sensores Sem Fio - RSSF. Dado um conjunto de 2t +1 sensores, a abordagem Optimal Design Testing Assignment - ODTA [36] gera um assinalamento de testes ótimo do ponto de vista da diagnosticabilidade do sistema. Entretanto, o problema da escolha em termos da distancia dos 2t +1 sensores que farao parte do assinalamento de testes tem características de um problema computacionalmente intratavel. Devido a ausencia de tal prova, apresenta-se o aprimoramento da heurística do ODTA para a escolha deste conjunto de sensores. Por meio da heurística Set of Sensors Chosen by Centroid and Radius - SSCCR apresentada, e possível selecionar em tempo polinomial tal conjunto nao somente otimo em termos de número de sensores, mas com uma considerável melhora dos resultados em termos de distancia geográfica entre os sensores. Por fim, apresenta-se a comparacõo das duas heurísticas abordadas com a solucõo ítima obtida pela formulacao do problema em programacao linear inteira, na qual pode-se confirmar que a heurística SSCCR apresenta melhor desempenho em relacao a heurística ODTA na escolha do conjunto de sensores com relacao a distancia entre eles e ate mesmo, em algumas situacoes, pode proporcionar o alcance de valores íotimos e consequentemente obter a reduçcõao do consumo de energia na execucao do diagnostico de falhas.Abstract: System-level diagnosis is a subset of fault tolerance. The goal of a system-level diagnosis algorithm is to report the state of the units of a distributed system to all fault-free units of the system. The diagnosability of the system depends on some topological properties of the diagnostic graph. In this context, a test assignment is a set of mutual tests between n units of a system. A system with n units is called t-diagnosable if the number of faulty units does not exceed t and it satisfies the following conditions: (i) n > 2t +1; and (ii) each unit is tested at least by t other units. A t-diagnosable system is said to be optimal if n = 2t +1. Consider the problem of defining a test assignment to identify faults in a wireless sensor network (WSN). Given a set of 2t +1 sensors, the approach Optimal Design Testing Assignment - ODTA [36] generates an optimal test assignment for the diagnosability of the system. However, the problem of the choice of 2t + 1 sensors that will take part of the testing assignment has characteristics of a computationally intractable problem. Due to the absence of such proof, the improvement of ODTA heuristics is presented. According to the heuristic Set of Sensors Chosen by Centroid and Radius - SSCCR it is possible to select that set in polynomial time, optimal not only in terms of number of sensors, but with a considerable improvement of results in terms of geographical distance between the sensors. Finally, a comparison of the two heuristics with the optimal solution obtained by the problem formulated in integer linear programming is presented, which confirms that the heuristic SSCCR has better performance compared with ODTA heuristic, and in many cases achieves optimal values, and consequently achieve the reduction of energy consumption in the implementation of fault diagnosis

Exploring map-based interfaces for mobile solutions in emergency work

This thesis investigates challenges and requirements related to both domain area and usability principles through investigating task-support for incident commanders in the police. To this end, domain knowledge has been collected through field studies, interviews and observation, and a prototype combining these requirements with state of the art mobile technology has been developed. The prototype has been developed to support tasks related to resource allocations. It combines the use of a map-based interface with icons with lists and forms, and uses direct manipulation as a part of the interaction. Evaluations have been conducted with both usability and domain experts, and results from the evaluations are categorized, discussed and finally used to put forward design implications. The findings of this thesis include a set of design implications deduced from (1) careful investigation of the domain area, (2) usability theories and design guidelines, and (3) evaluations of a developed prototype. The study has proven that the uniqueness and characteristics of emergency situations does not allow us to rely on design theory alone, and a combination of usability and domain expert is essential. The results from the evaluations and the design implication put forward show that the work in this field is highly feasible, yet more knowledge about the domain area is required to further facilitate for added value when solving tasks. Results also confirm that state of the art mobile devices are well-suited for decision-support within emergency response. Furthermore, the challenges, requirements and alternative solutions presented in this thesis are highly transferrable to other emergency agencies