After decades of digital developments, we are now entering a truly digital era. Digital information and communication technology has become a naturally embedded part ofthe designed environment we live in. Most parts of life are today pervaded by digital products and services. Evidence of such immersion can be noted in, for instance, media consumption. This development is gradually shaping and cultivating a media environment that is ubiquitous. Such ubiquity is manifested in media’s constant presence and thechanges in media consumption in the purview of digital innovation. Indeed, digital innovation is not only a shift in technology. It alters existing value networks and calls forrethinking existing value perceptions. While this disruptive change driven by digitizationcan be found in many industries, this thesis focuses on its impact on value networks in thenewspaper industry.The digitization of newspapers started with the introduction of the internet in the 90´sand soon emerged into new media innovations. While these new media innovations have not replaced existing media, they have been disruptive to newspaper value networks. Recently, the emergence of yet another digital innovation is specifically interesting whenstudying changes to value networks of the newspaper industry: the e-paper. This innovation (a screen technology very close to print on paper) exhibits inherent valuesthat make future replacement of print on paper a possibility. It is therefore regarded as avery promising technology in the newspaper industry. This thesis can be positioned at the intersection of the friction between forces to embarkon a new media trajectory and forces to hang on to the established structures andcontrol. The research question addressed in this thesis is: How are value networks of newspapers influenced by digital innovation? Addressing the research question, a multimethod approach was adopted to gain a broad understanding of how digital innovationinfluences value networks of newspapers. Drawing on digital innovation literature, the thesis presents a theoretical perspective with which to understand how digital innovation influences value networks. This perspective is instantiated as a model of value network configuration. The model emphasizes the multi-layered, dynamic, dialectic, and diametrical character of value networks in digital innovation. The model is offered as abasis and analytical tool to further explore value networks in digital innovation. This tool is useful for newspaper stakeholders when entering the digital era.

The planning of distribution systems consists in determining the optimum site and size of new substations and feeders in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level of reliability. This problem is a combinatorial, non-linear and constrained optimization problem. Several solution methods based on genetic algorithms have been reported in the literature; however, some of these methods have been reported with applications to small systems while others have long solution time. In addition, the vast majority of the developed methods handle planning problems simplifying them as single-objective problems but, there are some planning aspects that can not be combined into a single scalar objective; therefore, they require to be treated separately. The cause of these shortcomings is the poor representation of the potential solutions and their genetic operators This thesis presents the design of a genetic algorithm using a direct representation technique and specialized genetic operators for power distribution system expansion planning problems. These operators effectively preserve and exploit critical configurations that contribute to the optimization of the objective function. The constraints of the problems are efficiently handle with new strategies. The genetic algorithm was tested on several theoretical and real large-scale power distribution systems. Problems of network reconfiguration for loss reduction were also included in order to show the potential of the algorithm to resolve operational problems. Both single-objective and multi-objective formulations were considered in the tests. The results were compared with results from other heuristic methods such as ant colony system algorithms, evolutionary programming, differential evolution and other genetic algorithms reported in the literature. From these comparisons it was concluded that the proposed genetic algorithm is suitable to resolve problems of largescale power distribution system planning. Moreover, the algorithm proved to be effective, efficient and robust with better performance than other previous methods.

While developing networking for games and applications, developers have a list of network specific requirements to be met as well as decide how to meet them. It is not always easy to decide what protocol is best suited for a given network configuration, or what is the best size of a data packet. By performing a comparative analysis, it becomes possible to identify how protocols, packet size, and network configuration impact the one-way travel time and throughput of a given implementation. The result shows how the different implementations compared against each other and the analysis tries to determine why they perform as they do. This gives a good overview of the pros and cons of how TCP, TCP(N), UDP, and RakNet, behave and perform over LANs and WLANs with varying packet size.

Master’s thesis deals be occupied with the transmission of process data with peripheries to control devices. Data transmission with performs through two types of industrial networks. Use with these two Foundation Fieldbus and EtherNet / IP. In work is shows method conversion through gateway between the two networks. Here there is adduced method to connected and configure devices on the networks and also their implementation. Part of this work is also creating a visualization of these peripherals and the gateway. The work is also presents possible use for laboratory task to practice.

abstract: This dissertation investigates congestion mitigation during the ingress of a planned special event (PSE). PSEs would impact the regular operation of the transportation system within certain time periods due to increased travel demand or reduced capacities on certain road segments. For individual attendees, cruising for parking during a PSE could be a struggle given the severe congestion and scarcity of parking spaces in the network. With the development of smartphones-based ridesharing services such as Uber/Lyft, more and more attendees are turning to ridesharing rather than driving by themselves. This study explores congestion mitigation during a planned special event considering parking, ridesharing and network configuration from both attendees and planner’s perspectives. Parking availability (occupancy of parking facility) information is the fundamental building block for both travelers and planners to make parking-related decisions. It is highly valued by travelers and is one of the most important inputs to many parking models. This dissertation proposes a model-based practical framework to predict future occupancy from historical occupancy data alone. The framework consists of two modules: estimation of model parameters, and occupancy prediction. At the core of the predictive framework, a queuing model is employed to describe the stochastic occupancy change of a parking facility. From an attendee’s perspective, the probability of finding parking at a particular parking facility is more treasured than occupancy information for parking search. However, it is hard to estimate parking probabilities even with accurate occupancy data in a dynamic environment. In the second part of this dissertation, taking one step further, the idea of introducing learning algorithms into parking guidance and information systems that employ a central server is investigated, in order to provide estimated optimal parking searching strategies to travelers. With the help of the Markov Decision Process (MDP), the parking searching process on a network with uncertain parking availabilities can be modeled and analyzed. Finally, from a planner’s perspective, a bi-level model is proposed to generate a comprehensive PSE traffic management plan considering parking, ridesharing and route recommendations at the same time. The upper level is an optimization model aiming to minimize total travel time experienced by travelers. In the lower level, a link transmission model incorporating parking and ridesharing is used to evaluate decisions from and provide feedback to the upper level. A congestion relief algorithm is proposed and tested on a real-world network. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019

Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical computers, the configuration of virtual network and the use on different software platforms. It also suggests a workflow for the company to utilize virtual machine and share virtual machine resources across different project phases.

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The Internet has made tremendous progress since its inception. The kingpin has been the transmission control protocol (TCP), which supports a large fraction of communication. With the Internet's wide-spread access, users now have increased expectations. The demands have evolved to an extent which TCP was never designed to support. Since network stacks do not provide the necessary functionality for modern applications, developers are forced to implement them over and over again --- as part of the application or supporting libraries. Consequently, application developers not only bear the burden of developing application features but are also responsible for building networking libraries to support sophisticated scenarios. This leads to considerable duplication of effort. The challenge for TCP in supporting modern use cases is mostly due to limiting assumptions, simplistic communication abstractions, and (once expedient) implementation shortcuts. To further add to the complexity, the limited TCP options space is insufficient to support extensibility and thus, contemporary communication patterns. Some argue that radical changes are required to extend the networks functionality; some researchers believe that a clean slate approach is the only path forward. Others suggest that evolution of the network stack is necessary to ensure wider adoption --- by avoiding a flag day. In either case, we see that the proposed solutions have not been adopted by the community at large. This is perhaps because the cost of transition from the incumbent to the new technology outweighs the value offered. In some cases, the limited scope of the proposed solutions limit their value. In other cases, the lack of backward compatibility or significant porting effort precludes incremental adoption altogether. In this dissertation, we focus on the development of a communication model that explicitly acknowledges the context of the conversation and describes (much of) modern communications. We highlight how the communication stack should be able to discover, interact with and use available resources to compose richer communication constructs. The model is able to do so by using session, flow and endpoint abstractions to describe communications between two or more endpoints. These abstractions provide means to the application developers for setting up and manipulating constructs, while the ability to recognize change in the operating context and reconfigure the constructs allows applications to adapt to the changing requirements. The model considers two or more participants to be involved in the conversation and thus enables most modern communication patterns, which is in contrast with the well-established two-participant model. Our contributions also include an implementation of a framework that realizes such communication methods and enables future innovation. We substantiate our claims by demonstrating case studies where we use the proposed abstractions to highlight the gains. We also show how the proposed model may be implemented in a backwards compatible manner, such that it does not break legacy applications, network stacks, or middleboxes in the network infrastructure. We also present use cases to substantiate our claims about backwards compatibility. This establishes that incremental evolution is possible. We highlight the benefits of context awareness in setting up complex communication constructs by presenting use cases and their evaluation. Finally, we show how the communication model may open the door for new and richer communication patterns. / PHD

Doctor of Philosophy / Department of Computing and Information Sciences / Xinming (Simon) Ou / Enterprise network security management is a vitally important task, more so now than ever before. Networks grow ever larger and more complex, and corporations, universities, government agencies, etc. rely heavily on the availability of these networks. Security in enterprise networks is constantly threatened by thousands of known software vulnerabilities, with thousands more discovered annually in a wide variety of applications. An overwhelming amount of data is relevant to the ongoing protection of an enterprise network. Previous works have addressed the identification of vulnerabilities in a given network and the aggregated collection of these vulnerabilities in an attack graph, clearly showing how an attacker might gain access to or control over network resources. These works, however, do little to address how to evaluate or properly utilize this information. I have developed a comprehensive approach to enterprise network security management. Compared with previous methods, my approach realizes these issues as a uniform desire for provable mitigation of risk within an enterprise network. Attack graph simplification is used to improve user comprehension of the graph data and to enable more efficient use of the data in risk assessment. A sound and effective quantification of risk within the network produces values that can form a basis for valuation policies necessary for the application of a SAT solving technique. SAT solving resolves policy conflicts and produces an optimal reconfiguration, based on the provided values, which can be verified by a knowledgeable human user for accuracy and applicability within the context of the enterprise network. Empirical study shows the effectiveness and efficiency of these approaches, and also indicates promising directions for improvements to be explored in future works. Overall, this research comprises an important step toward a more automated security management initiative.

Cette thèse vise à améliorer la pile de protocoles pour réseaux de capteurs sans fil à récupération d'énergie afin de les rendre autonomes dans un contexte multi-saut. Elle s'inscrit dans le projet GreenNet de STMicroelectronics qui a pour objectif de concevoir et développer une nouvelle génération d'objets intelligent basés sur la récupération d'énergie ambiente en vue de l'intégration dans l'Internet des Objets. L'originalité de la plateforme GreenNet repose sur sa petite taille qui implique une faible capacité de stockage d'énergie ainsi qu'une faible capacité de récupération d'énergie. Avec un si faible budget d'énergie, les protocoles standards ou les solutions proposées par les communautés académique/industrielle ne permettant pas d'assurer un fonctionnement autonome de ces réseaux. Dans cette thèse, nous analysons les protocoles standards et les solutions existantes pour identifier leurs limites avec la plateforme GreenNet. Ensuite, nous proposons 3 contributions afin de permettre cette autonomie. La première contribution est MCBT, un protocole permettant d'accélérer la découverte et le rattachement de nouveaux noeuds à un réseau multi saut et multi-canaux en formation ou existent. Ce protocole réduit efficacement l'énergie dépensée dans cette phase fortement consommatrice. La deuxième contribution est STADA, un algorithme adaptant l'activité des capteurs en fonction des conditions locales de trafic et d'énergie disponible. STADA est basé sur une fonction de pondération qui tient compte de l'énergie présente dans la batterie, du taux de récupération d'énergie et du trafic local. Enfin, notre troisième contribution propose une nouvelle métrique de routage basée sur Expected Delay synthétisant en une seule variable monotone des facteurs tels que l'éloignement au puits, les chemins bénéficiant d'un ordonnancement de relayage de paquet privilégié et de périodes cumulées d'activité des radios sur le chemin favorable. Toutes les solutions proposées sont conçues pour fonctionner avec la norme IEEE 802.15.4 slotté et sont facilement transposables à son évolution définie par la norme IEEE 802.15.4e. Nous avons validé les protocoles proposés grâce à un simulateur émulant des noeuds réels (Cooja) et au simulateur WSNet. Les résultats ont montré de meilleures performances en termes de consommation d'énergie et de qualité de service par rapport à l'existant. / This thesis concerns energy efficient protocols for harvested wireless sensor networks. It is a part of an industrial Internet of Things project. STMicroelectronics started the GreenNet project with the objective to develop and design a new generation of harvesting smart objects to be integrated in the Internet of Things. The GreenNet platform is novel with respect to the existing solutions due to its small size that implies a small energy buffer and small harvesting capabilities. This aspect makes the standard protocols and precedent solutions not directly applicable on this extremely low power platform. In this dissertation, we analyse standard protocols and existing solutions to identify their issues in the gn platform. Then, we provide protocol and algorithm adaptations to make feasible the concept of auto configurable and sustainable networks of GreenNet nodes. We proposed MCBT, an energy efficient protocol for the bootstrap procedure. It enables low power nodes to be enrolled in mh mc wireless sensor networks thanks to the network support for enrolling new nodes. It represents an energy efficient solution that extends the standard protocol. We proposed STADA, a sustainable algorithm to adapt the node activity according to the available energy and traffic conditions. STADA is based on a weighted function that takes into account the energy present in the battery, the energy harvesting rate, and network traffic. In this way, the algorithm takes into account all main parameters to adapt the energy consumption and improve the node performance. To make the harvested network more efficient according to light variations, we proposed a novel metric that makes the path choice a simple process. With the Expected Delay, we synthesize all network parameters in a single monotonic variable that facilitates the path choice in mh harvesting wireless sensor networks. All proposed solutions are designed to work with standard beacon-enabled IEEE 802.15.4 protocols and are easily portable on the future version of IEEE 802.15.4e. We validated the proposed protocols with emulations and simulations. The evaluation results shown better performance in terms of energy consumption and quality of service.