Wireless real-time networks are a natural step for deployments in industrial automation, automotive, avionics, or robotics targeting features such as improved mobility, reduced wiring costs, and easier more flexible network developments. However, the open transmission medium where wireless networks operate is generally more prone to interference and transmission errors caused by fading. Due to this, real-time communications is in general still provided by wired networks in many of these application fields. At the same time, wired and wireless standards traditionally associated with the consumer electronics application field (e.g., IEEE 802.3 "Ethernet" and IEEE 802.11 “WiFi”) are trying to find their way into industrial automation, automotive, avionics, and robotics use cases, since they provide features like high throughput and cheap hardware. Many times, applications with diverse real-time and reliability requirements have to co-exist, and often in hybrid wired-wireless networks to ensure compatibility with existing systems. Given this scenario, it is essential to provide support for data traffic with requirements ranging from real-time time-triggered and event-driven to non-real-time, and enable high reliability with respect to timing constraints, in the context of hybrid wired-wireless networks. This thesis aims at covering the aforementioned requirements by proposing a medium access control (MAC) solution suitable for wireless communications, with support for real-time traffic with diverse time and reliability requirements. The MAC layer is in charge of providing timely access to the transmission medium, and can be effectively used to increase reliability by means of, e.g., avoiding concurrent transmissions and performing retransmissions. To this end, a set of evaluation criteria is proposed to determine the suitability of a particular MAC method to meet the identified emerging requirements. These criteria include channel access delay, reliability, protocol overhead, capability to integrate with wired networks, and sensitivity to interference from collocated systems. Next, based on these requirements, a MAC protocol with a set of tunable features is proposed, and evaluated in terms of support for data traffic with different loads and distributions, i.e., emanating from different traffic classes, and from different number of senders. The evaluation is made both analytically, by calculating the worst case delay and, with the help of real-time schedulability analysis, determining the effective load required to guarantee real-time deadlines, as well as by means of computer simulations using the INET framework for OMNeT++ to determine the average delay. Finally, the thesis proposes a set of retransmission schemes to be used together with the proposed MAC protocols in order to improve the resistance against interference and transmission errors. For this, a set of interference patterns with different characteristics is proposed and applied in the simulator. The resulting MAC layer solution is designed to be used at the wireless segment of a hybrid wired-wireless network, and is able to schedule data traffic originating from three different classes: time-triggered, rate-constrained and best-effort. To achieve this, an additional collision domain introducing wireless segments is added to the real-time scheduler, as well as support for real-time retransmissions, to enable high reliability while keeping real-time deadlines. / RetNet - The European Industrial Doctorate Programme on Future Real-Time Networks

Differential Evolution (DE) has become one of the most important metaheuristics during the recent years, obtaining attractive results in solving many engineering optimization problems. However, the performance of DE is not always strong when seeking optimal solutions. It has two major problems in real world applications. First, it can easily get stuck in a local optimum or fail to generate better solutions before the population has converged. Secondly, its performance is significantly influenced by the control parameters, which are problem dependent and which vary in different regions of space under exploration.  It usually entails a time consuming trial-and-error procedure to set suitable parameters for DE in a specific problem, particularly for those practioners with limited knowledge and experience of using this technique.   This thesis aims to develop new DE algorithms to address the two aforementioned problems. To mitigate the first problem, we studied the hybridization of DE with local search techniques to enhance the efficiency of search. The main idea is to apply a local search mechanism to the best individual in each generation of DE to exploit the most promising regions during the evolutionary processs so as to speed up the convergence or increase the chance to scape from local optima. Four local search strategies have been integrated  and tested in the global DE framework, leading to variants of the memetic DE algorithms with different properties concerning diversification and intensification. For tackling the second problem, we propose a greedy adaptation method for dynamic adjustment of the control parameters in DE. It is implemented by conducting greedy search repeatedly during the run of DE to reach better parameter assignments in the neighborhood of a current candidate. The candidates are assessed by considering both, the success rate and also fitness improvement of trial solutions against the target ones. The incorporation of this greedy parameter adaptation method into standard DE has led to a new adaptive DE algorithm, referred to as Greedy Adaptive Differential Evolution (GADE).   The methods proposed in this thesis have been tested in different benchmark problems and compared with the state of the art algorithms, obtaining competitive results. Furthermore, the proposed GADE algorithm has been applied in an industrial scenario achieving more accurate results than those obtained by a standard DE algorithm. / Differential Evolution (DE) har blivit en av de viktigaste metaheuristikerna under de senaste åren och har uppnått attraktiva resultat för att lösa många optimeringsproblem inom teknik. Dock är prestationen hos DE inte alltid framgångsrik när man söker optimala lösningar. Det finns två huvudsakliga problem för applikationer i den verkliga världen. Det första är att den lätt kan fastna i lokala optimum eller misslyckas att generera bättre lösningar före det att populationen (en grupp av lösningar) har hunnit konvergera. Det andra är att prestandan påverkas märkvärdigt av kontrollparametrar, vilkas optimala värden beror på problem som ska lösas och varierar mellan regioner i sökrymden. Detta innebär oftast ett tidskrävande trial-and-error förfarande för att hitta lämpliga parametrar till ett specifikt DE-problem, framför allt för utövare med begränsad kunskap och erfarenhet av DE.   Syftet med denna licentiatavhandling är att utveckla nya DE-algoritmer för att behandla de ovannämnda problemen. För att möta det första problemet så studerades hybridisering av DE och lokala söktekniker för att effektivisera sökningen. Tanken är att använda en lokal sökmekanism på den bästa individen i varje generation i DE-algoritmen och utnyttja de mest lovande regionerna under evolutionsprocessen för att snabba på konvergensen eller öka chansen att undvika lokala optimum. Fyra lokala sökstrategier har integrerats och testats i det globala DE-ramverket vilket har lett till fyra varianter av DE-algoritmerna med olika egenskaper beträffande diversifiering och intensifiering. Till det andra problemet föreslås en greedy adaptation method för dynamisk justering av kontrollparametrarna i DE. Den implementeras genom att utföra greedy search upprepade gånger under körningen av DE för att hitta bättre värden till kontrollparametrarna. Utvärderingen av parameterval baseras på både success rate och fitness improvement av trial lösningar jämfört med target lösningar. Sammanslagningen av DE och denna greedy parameter adaptation har lett till en ny adaptiv DE-algoritm som kallas Greedy Adaptive Differential Evolution (GADE).   Den föreslagna metoden i denna licentiatavhandling har testats i olika prestandamätningar och jämförts med state-of-the-art-algoritmer, med goda resultat. Dessutom har den föreslagna GADE-algoritmen använts i ett industriellt scenario och uppnådde då mer exakta resultat än den med en standard DE-algoritm.

Location Based Social Networks has attracted millions of mobile internet users. On their smart phones people can share their locations using social network services. The main purpose of check-ins is to provide other users’ information about places they visit. Location Based Social Network with thousands of check-ins allows users to learn social behavior through spatial-temporal effect, which provides different services such as place recommendation and traffic prediction. Through this information, we can have an idea about important locations in the city and human mobility. The main purpose of this thesis is to evaluate Markov Models in Location Based Social Networks in terms of prediction accuracy. Location Based Social Network features and basic information’s will be analyzed before modeling of human mobility. Afterwards with the use of three methods human mobility will be modeled. In all the models the check-ins are analyzed based on prior category. After estimation the user’s possible next check-in category, and according to the user’s check-ins in the following category, it predicts the next possible check-in location. Finally a comparison will be made considering the models prediction accuracy.

Attacks on critical information infrastructure are increasing in volume and sophistication with destructive consequences according to the 2015 Cyber Supply Chain Security Revisited report from ESG recently (ESG, 2015). In a world of connectivity and data dependency, cyber-crime is on the rise causing many disruptions in our way of living. Our society relies on these critical information infrastructures for our social and economic well-being, and become more complex due to many integrated systems. Over the past years, various research contributions have been made to provide intrusion detection solutions to address these complex attack problems. Even though various research attempts have been made, shortcomings still exists in these solutions to provide attack detection. False positives and false negatives outcomes for attack detection are still known shortcomings that must be addressed. This study contributes research, by finding a solution for the found shortcomings by designing an IT artifact framework based on the Design Science Research Methodology (DSRM). The framework consist of big data analytics technology that provides attack detection. Research outcomes for this study shows a possible solution to the shortcomings by the designed IT artifact framework with use of big data analytics technology. The framework built on open source technology can provide attack detection, and possibly provide a solution to improve the false positives and false negatives for attack detection outcomes. Three main modules have been designed and demonstrated, whereby a hybrid approach for detection is used to address the shortcomings. Therefore, this research can benefit Critical Information Infrastructure Protection (CIIP) in Sweden to detect attacks and can possibly be utilized in various network infrastructures.

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The Onion Router (Tor) is a good way to have privacy and anonymity while using the Internet. However there are several problems it has to deal with, because it is also possible to bypass governmental censorship, which also became goal of the Tor network. By different techniques several governments and other parties who have the capability to, try to block the network completely. One technique is to overwhelm the distribution strategies for bridges – which are an essential part of the Tor network, especially for censored users. Hereby a possible approach for distributing bridges via online social networks (OSN) is presented. It is based on the Proximax distribution but has also the capability to separate and exclude possible adversaries who managed to join the social group. Moreover trustful users get rewarded by a better status and less waiting time for bridges.

The hardware that computers consist of may for dierent reasons be dicult to monitor, the price may be high or the hardware itself may be unavailable. The most apparent reason though is the fact that hardware generally is not transparent, i.e. the hardware does not provide informa- tion on how a task is conducted, only its result. To provide a virtual en- vironment that enables simulation according to specic input parameters eectively solves many of the issues associated with hardware evaluation. Simulation has applications everywhere, not the least in computer science: From the low level of micro code all the way up to interpreting a high level implementation on top of a profound software stack. This thesis entails a virtual environment running a MIPS pipeline, although the simulator is implemented in the high level language C, it executes simulation at the fairly low level of assembler code. When provided with a user specied conguration le, the environment allows simulation of MIPS assembler programs, through the CPU, via interconnecting buses, ending at the level of virtual memory.

This report presents a real-time simulation of a music fountain which is simulated in three dimensions by a particle animation system. In this system, gravity and wind are factors that affect the locus movement of particles. Using kinematic equations, the dynamic behaviors of particles is modeled. A specific contribution of the work presented here is that parameters for the motion equation are estimated from sound playing in real-time which controls the dynamic behavior of animated fountain. An open source programming language called Processing is used to implement the environment. Results of the system are demonstrated in form of its graphical output and performance benchmarks from run-time evaluation. The author investigates the influence of the parameters of particle system and music attributes on the animation of the music fountain simulation. The size, number, color, texture and transparency of particles can influence the quality of music fountain simulation. Using FFT function to get music parameters is the best way to figure out differences between different music.

Smartphone are very common to use by more people and for more purposes, and the interest into the mobile applications development has increased. Many companies, that are exposing their service as web services, intended to enable mobile access to distribute their web resources. This work is about developing a mobile phone application for disseminating operational information to customers and suppliers of the company “100 Procent Media AB”.  This application is based on android as operating system. The company put messages on its server that the mobile application later reads and store data in the database of the mobile application. The customers of the company receive a message that is stored in the server of the developing application.