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The download duration of peer-to-peer overlay networks is highly dependent upon the client's selection of candidate node-servers and the algorithms used in that process. Recent findings suggest that as node-server network capacity increases the deviation from the average total download time can vary as much as 300 percent between selection algorithms. This work investigated the current selection algorithms based upon chunk size, parallel connections, permanent connection, and time based switching. The time based switching algorithm is a variation of the chunk based algorithm. Time based switching enables a client to randomly select a new node-server regardless of connection speed at predetermined time slots. Simulations indicate a 41% percent decrease in download time when compared to chunk based switching. The effects of inserting chokepoints in the time based switching algorithm were investigated. This work investigated improving a client's download performance by preemptively releasing a client from a poor performing node-server. To achieve this, the client will gather a peer-to-peer network overlay capacity from a global catalog. This information will be used to seed a client choke algorithm. Clients will then be able to continually update a local capacity average based upon past download sessions. This local average will be used to make a comparison between the current download session and the previously calculated average. A margin has been introduced to allow the client to vary from the average calculated capacity. The client will perform comparisons against chokepoints and make performance decisions to depart a node-server that does not meet minimum capacity standards. Experimental results in this research demonstrated the effectiveness of applying a choking algorithm to improve upon client download duration as well as increasing the accuracy of download duration estimates. In the single downloader scenario, the choke based algorithm improved performance up to 44% in extreme congestion and a more modest 13% under normal conditions. The multiple client scenarios yielded on average a 1% decrease in client download duration along with a 44% increase download homogeneity. Furthermore, the results indicate that a client based choking algorithm can decrease overall peer-to-peer network congestion buy improving upon client selection of node-servers.

Management of systemic risk in financial markets is traditionally associated with setting (higher) capital requirements for market participants. There are indications that while equity ratios have been increased massively since the financial crisis, systemic risk levels might not have lowered, but even increased (see ECB data 1 ; SRISK time series 2 ). It has been shown that systemic risk is to a large extent related to the underlying network topology of financial exposures. A natural question arising is how much systemic risk can be eliminated by optimally rearranging these networks and without increasing capital requirements. Overlapping portfolios with minimized systemic risk which provide the same market functionality as empir- ical ones have been studied by Pichler et al. (2018). Here we propose a similar method for direct exposure networks, and apply it to cross-sectional interbank loan networks, consisting of 10 quarterly observations of the Austrian interbank market. We show that the suggested framework rearranges the network topol- ogy, such that systemic risk is reduced by a factor of approximately 3.5, and leaves the relevant economic features of the optimized network and its agents unchanged. The presented optimization procedure is not intended to actually re-configure interbank markets, but to demonstrate the huge potential for systemic risk management through rearranging exposure networks, in contrast to increasing capital requirements that were shown to have only marginal effects on systemic risk (Poledna et al., 2017). Ways to actually incentivize a self-organized formation toward optimal network configurations were introduced in Thurner and Poledna (2013) and Poledna and Thurner (2016). For regulatory policies concerning financial market stability the knowledge of minimal systemic risk for a given economic environment can serve as a benchmark for monitoring actual systemic risk in markets.

Esta dissertação apresenta uma metodologia de otimização do fluxo de potência em sistemas elétricos de subtransmissão utilizando duas técnicas da Computação Evolutiva, os Algoritmos Genéticos e as Estratégias Evolutivas. A metodologia decompõe o problema em duas partes e o trata seqüencialmente. A primeira parte procede com a otimização do fluxo de potência ativa e a segunda com a otimização do fluxo de potência reativa. São apresentadas as características e estruturas básicas dos Algoritmos Genéticos e das Estratégias Evolutivas. A técnica dos Algoritmos Genéticos é implementada no modelo de otimização do fluxo de potência ativa e a técnica das Estratégias Evolutivas no modelo de otimização do fluxo de potência reativa. As variáveis de controle dos modelos desenvolvidos são, respectivamente, os estados dos dispositivos de seccionamento e os níveis de tensão dos barramentos dos pontos de fronteira, associadas ao sistema analisado. Analisam-se os sistemas elétricos de subtransmissão que contêm múltiplos pontos de fronteira (conexão) com a Rede Básica e diversas possibilidades de configuração operativa. A metodologia proposta é aplicada a um sistema elétrico de subtransmissão real a fim de minimizar o custo dos encargos de uso dos sistemas de transmissão. Os resultados obtidos mostram a eficácia dos algoritmos desenvolvidos na busca das soluções desejadas. / This dissertation presents a power flow optimization methodology on subtransmission electric systems using two techniques of Evolutionary Computation, namely the Genetic Algorithms and the Evolution Strategies. The methodology splits the problem into two parts and treats it separately. On the first step it proceeds to optimize the active power flow and on the second step to optimize the reactive power flow. Characteristics and basic structures of the Genetic Algorithms and the Evolution Strategies are shown. The Genetic Algorithms technique is implemented on the active power flow optimization model and the Evolution Strategies technique on the reactive power flow optimization model. The control variables of developed models are, respectively, the switch states and the border point bar voltage levels, associated to the analyzed system. The subtransmission electric systems that have multiple border (connection) points to the Basic Network and many operative configuration possibilities are analyzed. The proposed methodology is applied to a real subtransmission electric system in order to minimizes the transmission system use duty costs. The obtained results show the efficacy of the developed algorithms in the search of desired solutions.

First issue that this thesis tries to address is setting up a practical framework of foliated transportation network. Scope of this thesis limited to several cities in Sweden to illustrate that this organization can be set up and it can perform under corresponding regulations. Beside the possibility of performance it was of high importance to consider its positive effects on whole network factors from both social and industrial perspectives. For this purpose a comparison between network results for different truck fill rates carried out but practical use of results is completely dependent of the stakeholder who is going to utilize them.

Effective distribution of hydrogen in refinery hydrogen networks is a major concern for refiners tackling the stringent specifications on maximum sulphur levels in middle distillates and the increasing global demand of diesel fuel. A major challenge is the implementation of a shift from conventional to ultra-deep methods of desulphurisation. Meanwhile, the capacity of secondary conversion processes such as fluid catalytic cracking (FCC) and hydrocracking in refineries has steadily increased in converting the bottom of the barrel into high-value lighter products resulting in increased levels of hydroprocessing, which exerts a higher demand on refinery hydrogen systems. Previous methodologies on hydrogen network optimization have been developed mainly based on the assumption of fixed hydroprocessing performance with constant hydrogen consumption and light hydrocarbon yields, in order to reduce the complexity of the optimisation problem. Consequently, critical interactions among feed and catalyst properties, hydroprocessor operating conditions, product quality and yields, and hydrogen consumption are usually neglected. This research work involves three major aspects: 1. Development of semi-empirical nonlinear lumped hydrodesulphurisation (HDS) and hydrocracker models that are robust and sufficiently detailed to capture the behaviour of the process with changes in feed characteristics and operating conditions. The formation of light hydrocarbons during HDS reactions have been accounted for. Hydrocracker conversion models and five/six-lumped product yield models for vacuum gas oil (VGO) and vacuum residue (VR) feedstocks have been developed from a combination of first principles and empirical methods based on several process parameters. The proposed models are validated with different feedstocks and shows good agreement with industrial data. 2. Integration of HDS and hydrocracker performance models into refinery hydrogen network models to explore existing interactions between processes and the hydrogen network, and their combined effect on the overall network objective. 3. Optimization of the overall superstructure under different operating scenarios to facilitate the efficient distribution and utilization of hydrogen and the maximization of clean high-value products. The integrated superstructure network model is developed and optimized within the General Algebraic Modelling System (GAMS). The model is representative of the dynamic interactions between hydrodesulphurisation and hydrocracking processes in the refinery hydrogen network as demonstrated by the reproducibility of industrial refinery data. Thus, this work presents a holistic and realistic implementation of refinery hydrogen management technique.

The rapid growth of the Internet, in the last few years, has generated a need to enhance the existing IP networks in the areas of availability, dependability and scalability in order to provide a mission critical networking environment. In contemporary IP networks, data packets are routed as a function of the destination address and a single metric such as hop-count or delay. This approach tends to cause message traffic to converge onto the same link, which significantly increases congestion and leads to unbalanced network resource utilization. One solution to this problem is provided by Traffic Engineering (TE), which uses, bandwidth guaranteed, Explicitly Routed Label Switched Paths (ER-LSPs). Due to the dramatic increase in the backbone speeds, current research focuses more on traffic engineering with LSPs for clear control over the traffic distribution in the network. However, the growing popularity of the Internet is driving the Internet Service Providers to adapt new technologies in order to support multiple classes of applications with different characteristics and performance requirements. Multi-Protocol Label Switching (MPLS), which was proposed by the IETF provides essential facilities for traffic engineering and reliable QoS services for the Internet. MPLS networks provide the required flexibility for operators to manage their traffic with ER-LSPs. Even though conventional routing algorithms support the ER-LSP setup in MPLS networks, they are not efficient in link residual capacity information updates and limit resource utilization, which eventually leads to LSP failures and unbalanced network resource utilization. This thesis proposes a new architecture with a cluster based distributed routing algorithm to setup bandwidth guaranteed ER-LSPs in MPLS backbone networks. The proposed routing algorithm confines the route discovery region in order to reduce the routing overhead and computes all possible routes from ingress node to egress node. Based on LSP requirements and network load conditions, the egress node selects the most suitable path from the available paths in order to setup the LSP. This routing scheme optimizes network resource utilization by evenly distributing traffic throughout the network. The Resource Reservation Protocol (RSVP) works in conjunction with the routing protocol for resource reservation and label distribution along the LSP.

Wireless sensor network (WSN) has emerged as a promising technology thanks to the recent advances in electronics, networking, and information processing. A wide range of WSN applications have been proposed such as habitat monitoring, environmental observations and forecasting systems, health monitoring, etc. In these applications, many low power and inexpensive sensor nodes are deployed in a vast space to cooperate as a network. Although WSN is a promising technology, there is still a great deal of additional research required before it finally becomes a mature technology. This dissertation concentrates on three factors which are holding back the development of WSNs. Firstly, there is a lack of traffic analysis & modeling for WSNs. Secondly, network optimization for WSNs needs more investigation. Thirdly, the development of anomaly detection techniques for WSNs remains a seldomly touched area. In the field of traffic analysis & modeling for WSNs, this dissertation presents several ways of modeling different aspects relating to WSN traffic, including the modeling of sequence relations among arriving packets, the modeling of a data traffic arrival process for an event-driven WSN, and the modeling of a traffic load distribution for a symmetric dense WSN. These research results enrich the current understanding regarding the traffic dynamics within WSNs, and provide a basis for further work on network optimization and anomaly detection for WSNs. In the field of network optimization for WSNs, this dissertation presents network optimization models from which network performance bounds can be derived. This dissertation also investigates network performances constrained by the energy resources available in an indentified bottleneck zone. For a symmetric dense WSN, an optimal energy allocation scheme is proposed to minimize the energy waste due to the uneven energy drain among sensor nodes. By modeling the interrelationships among communication traffic, energy consumption and WSN performances, these presented results have efficiently integrated the knowledge on WSN traffic dynamics into the field of network optimization for WSNs. Finally, in the field of anomaly detection for WSNs, this dissertation uses two examples to demonstrate the feasibility and the ease of detecting sensor network anomalies through the analysis of network traffic. The presented results will serve as an inspiration for the research community to develop more secure and more fault-tolerant WSNs. / STC

To achieve a cost-effective network deployment, employing state-of-art technical advances provides a practical and effective way to enhance system performance and quality of service provisioning. Cooperative transmission has been recognized as one of the most effective paradigms to achieve higher system performance in terms of lower bit-error rate, higher throughput, larger coverage, more efficient energy utilization, and higher network reliability. This dissertation studies the location planning for the deployment of broadband access networks and explores the great potential of cooperative transmission in the context of single-cell cooperative relaying and multi-cell cooperative transmission, respectively. The placement problem is investigated in two categories of network deployment environment, i.e., an existing wireless access network and a perspective broadband access network, respectively. In an existing wireless access network, to solve some practical problems such as the requirements of capacity enhancement and coverage extension, relay stations (RSs) are introduced in the network architecture. We propose two optimization frameworks with the design objectives of maximizing cell capacity and minimizing number of RSs for deployment, respectively. Mathematical formulations are provided to precisely capture the characteristics of the placement problems. The corresponding solution algorithms are developed to obtain the optimal (or near-optimal) results in polynomial time. Numerical analysis and case studies are conducted to validate the performance benefits due to RS placement and the computation efficiency of the proposed algorithms. To deploy a new metropolitan-area broadband access network, we explore the integration of passive optical network (PON) and wireless cooperative networks (WCN) under the multi-cell cooperative transmission technology. An optimization framework is provided to solve the problem of dimensioning and site planning. The issues of node placement, BS-user association, wireless bandwidth and power breakdown assignment are jointly considered in a single stage to achieve better performance. We also propose a solution to the complex optimization problem based on decomposition and linear approximation. Numerical analysis and case studies are conducted to verify the proposed framework. The results demonstrate the performance gains and economic benefits. Given a set of network parameters, the proposed optimization frameworks and solutions proposed in this dissertation can provide design guidelines for practical network deployment and cost estimations. And the constructed broadband access networks show a more cost-effective deployment by taking advantage of the cooperative transmission technology.

To achieve a cost-effective network deployment, employing state-of-art technical advances provides a practical and effective way to enhance system performance and quality of service provisioning. Cooperative transmission has been recognized as one of the most effective paradigms to achieve higher system performance in terms of lower bit-error rate, higher throughput, larger coverage, more efficient energy utilization, and higher network reliability. This dissertation studies the location planning for the deployment of broadband access networks and explores the great potential of cooperative transmission in the context of single-cell cooperative relaying and multi-cell cooperative transmission, respectively. The placement problem is investigated in two categories of network deployment environment, i.e., an existing wireless access network and a perspective broadband access network, respectively. In an existing wireless access network, to solve some practical problems such as the requirements of capacity enhancement and coverage extension, relay stations (RSs) are introduced in the network architecture. We propose two optimization frameworks with the design objectives of maximizing cell capacity and minimizing number of RSs for deployment, respectively. Mathematical formulations are provided to precisely capture the characteristics of the placement problems. The corresponding solution algorithms are developed to obtain the optimal (or near-optimal) results in polynomial time. Numerical analysis and case studies are conducted to validate the performance benefits due to RS placement and the computation efficiency of the proposed algorithms. To deploy a new metropolitan-area broadband access network, we explore the integration of passive optical network (PON) and wireless cooperative networks (WCN) under the multi-cell cooperative transmission technology. An optimization framework is provided to solve the problem of dimensioning and site planning. The issues of node placement, BS-user association, wireless bandwidth and power breakdown assignment are jointly considered in a single stage to achieve better performance. We also propose a solution to the complex optimization problem based on decomposition and linear approximation. Numerical analysis and case studies are conducted to verify the proposed framework. The results demonstrate the performance gains and economic benefits. Given a set of network parameters, the proposed optimization frameworks and solutions proposed in this dissertation can provide design guidelines for practical network deployment and cost estimations. And the constructed broadband access networks show a more cost-effective deployment by taking advantage of the cooperative transmission technology.