Service Function Chaining (SFC) enriches the network functionalities to fulfill the increasing demand of value-added services. By leveraging SDN and NFV for SFC, it becomes possible to meet the demand fluctuation and construct a dynamic SFc. However, the integration of SDN with NFV requires packet header modifications, generates excessive network traffics, and induces additional I/O overheads for packet processing. These additional overheads result in a lower system performance, scalability, and agility. To improve the system performance, a co-optimized solution is proposed to implemented NF to achieve a better performance for software-based network functions. To improve the system scalability, a many-field packet classification is proposed to support a more complex ruleset. To improve the system agility, a network function-enabled switch is proposed to lower the network function content switching time. The experiment results show that the performance of a network function is improved by 8 times by leveraging GPU as a parallel computation platform. Moreover, the matching speed to steer network traffics with many-field ruleset is improved by 4 times with the proposed many-field packet classification algorithm. Finally, the proposed system is able to improve system bandwidth 5 times better compared the native solution and maintain the content switch time with the proposed SFC implementation using SDN and NFV.

In this thesis, we address the problem of service function chaining in a network. Currently, problems of chaining services in a network (i.e. service function chaining) can be broadly categorised into middlebox placement in a network and packet steering through middleboxes. In this work, we present a packet steering approach - One Pass Packet Steering (OPPS) - for use in multi-subscriber environments, with the aim that subscribers having similar policy chain composition should experience the same network performance. We develop and show algorithms with a proof of concept implementation using emulations performed with Mininet. We identify challenges and examine how OPPS could benefit from the Software Defined Data Center architecture to overcome these challenges. Our results show that, given a fixed topology and different sets of policy chains containing the same middleboxes, the end-to-end delay and throughput performance of subscribers using similar policy chains remains approximately the same. Also, we show how OPPS can use a smaller number of middleboxes and yet, achieve the same hop count as that of a reference model described in a previous work as ideal, without violating the subscribers' policy chains.

5G and beyond mobile network technology promises to deliver unprecedented ultra-low latency and high data rates, paving the way for many novel applications and services. Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) are two technologies expected to play a vital role in achieving ambitious Quality of Service requirements of such applications. While NFV provides flexibility by enabling network functions to be dynamically deployed and inter-connected to realize Service Function Chains (SFC), MEC brings the computing capability to the mobile network's edges, thus reducing latency and alleviating the transport network load. However, adequate mechanisms are needed to meet the dynamically changing network service demands (i.e., in single and multiple domains) and optimally utilize the network resources while ensuring that the end-to-end latency requirement of services is always satisfied. In this dissertation work, we break the problem into three separate stages and present the solutions for each one of them.Firstly, we apply Artificial Intelligence (AI) techniques to drive NFV resource orchestration in MEC-enabled 5G architectures for single and multi-domain scenarios. We propose three deep learning approaches to perform horizontal and vertical Virtual Network Function (VNF) auto-scaling: (i) Multilayer Perceptron (MLP) classification and regression (single-domain), (ii) Centralized Artificial Neural Network (ANN), centralized Long-Short Term Memory (LSTM) and centralized Convolutional Neural Network-LSTM (CNN-LSTM) (single-domain), and (iii) Federated ANN, federated LSTM and federated CNN-LSTM (multi-domain). We evaluate the performance of each of these deep learning models trained over a commercial network operator dataset and investigate the pros and cons of different approaches for VNF auto-scaling. For the first approach, our results show that both MLP classifier and MLP regressor models have strong predicting capability for auto-scaling. However, MLP regressor outperforms MLP classifier in terms of accuracy. For the second approach (one-step prediction), CNN-LSTM performs the best for the QoS-prioritized objective and LSTM performs the best for the cost-prioritized objective. For the second approach (multi-step prediction), the encoder-decoder CNN-LSTM model outperforms the encoder-decoder LSTM model for both QoS and Cost prioritized objectives. For the third approach, both federated LSTM and federated CNN-LSTM models perform equally better than the federated ANN model. It was also noted that in general federated learning approaches performs poorly compared to centralized learning approaches. Secondly, we employ Integer Linear Programming (ILP) techniques to formulate and solve a joint user association and SFC placement problem, where each SFC represents a service requested by a user with end-to-end latency and data rate requirements. We also develop a comprehensive end-to-end latency model considering radio delay, backhaul network delay and SFC processing delay for 5G mobile networks. We evaluated the proposed model using simulations based on real-operator network topology and real-world latency values. Our results show that the average end-to-end latency reduces significantly when SFCs are placed at the ME hosts according to their latency and data rate demands. Furthermore, we propose an heuristic algorithm to address the issue of scalability in ILP, that can solve the above association/mapping problem in seconds rather than hours.Finally, we introduce lightMEC - a lightweight MEC platform for deploying mobile edge computing functionalities which allows hosting of low-latency and bandwidth-intensive applications at the network edge. Measurements conducted over a real-life test demonstrated that lightMEC could actually support practical MEC applications without requiring any change to existing mobile network nodes' functionality in the access and core network segments. The significant benefits of adopting the proposed architecture are analyzed based on a proof-of-concept demonstration of the content caching use case. Furthermore, we introduce the AI-driven Kubernetes orchestration prototype that we implemented by leveraging the lightMEC platform and assess the performance of the proposed deep learning models (from stage 1) in an experimental setup. The prototype evaluations confirm the simulation results achieved in stage 1 of the thesis.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24941号 / 情博第852号 / 新制||情||143(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 大木 英司, 教授 原田 博司, 教授 佐藤 高史 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2017-11-24T20:01:50Z No. of bitstreams: 1 Rafael_Anton_Eichelberger_dis.pdf: 5090662 bytes, checksum: 0c27686648c0e4c286c555a921034507 (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-12-04T11:49:36Z (GMT) No. of bitstreams: 1 Rafael_Anton_Eichelberger_dis.pdf: 5090662 bytes, checksum: 0c27686648c0e4c286c555a921034507 (MD5) / Made available in DSpace on 2017-12-04T11:53:53Z (GMT). No. of bitstreams: 1 Rafael_Anton_Eichelberger_dis.pdf: 5090662 bytes, checksum: 0c27686648c0e4c286c555a921034507 (MD5) Previous issue date: 2017-03-15 / Service Function Chaining (SFC) ? um importante campo de pesquisa na ?rea de redes de computadores, com v?rias propostas de diferentes m?todos de encapsulamento e encaminhamento de pacotes. Os m?todos de encaminhamento de pacotes usados para implementar SFC podem inviabilizar o uso de ferramentas tradicionais de depura??o de rede, o que dificulta a detec??o de erros de configura??o ou poss?veis degrada??es de desempenho em ambientes SFC. Este trabalho apresenta o SFC Path Tracer, uma ferramenta para detec??o de problemas no dom?nio SFC em ambientes NFV/SDN. Essa ferramenta permite a identifica??o de problemas no dom?nio SFC, atrav?s da gera??o de trace de pacotes e medi??o de atrasos intra-hop a partir de um SFC Path espec?fico. SFC Path Tracer ? agn?stico em rela??o aos mecanismos de encapsulamento e encaminhamento usados para implementar SFC, sendo eficaz na detec??o de grande parte dos problemas em um ambiente SFC. / Service Function Chaining (SFC) is an important research field in networking area with many encapsulation and forwarding mechanisms being proposed. To implement SFC, non-standard forwarding methods are used which break the mechanism of regular network troubleshooting tools, challenging the detection of SFC misconfiguration or performance degradation. This work presents the SFC Path Tracer, a tool for roubleshooting SFC in NFV/SDN environments. This tool enables the identification of problems in the SFC environment by generating packet trace and computing intra-hop delays from a specific SFC path. SFC Path Tracer is agnostic regarding the SFC encapsulation and forwarding mechanisms being effective to detect most problems in an SFC environment.

During the past decade, growing attention has been given to industrial service offerings in the marketing literature as well as in many manufacturing firms. This phenomenon is often described as a goods-services transition, in which companies increasingly turn to the provision of industrial services in order to achieve competitive advantage, such a closer customer relationships and higher profit margins. Industrial services span a wide range of offerings, from basic after-sales services to process-orientated solutions consisting of both services and capital goods. With industrial service offerings receiving increased attention as their importance is understood, the ability to manage the service business in a manufacturing context becomes ever more vital. The overall purpose of this doctoral thesis is to describe and analyse how capital equipment manufacturing firms strategically manage their industrial service offerings in order to achieve long-term competitive advantage. This includes analysing how to organise the firm for the development and production of service, and, depending on the type of industrial service offering, what the requirements on the service processes are. Furthermore the role of information and communication technologies as enablers for new offerings and processes is analysed. The thesis consists of a compilation of five papers, two case descriptions and an extended summary. The research builds on a multiple case study of the service organisations of market-leading manufacturing firms. The main cases are based on in-depth studies at ITT Water & Wastewater and Toyota Material Handling Group. The results suggest that, as the division between goods and services becomes ever more blurred, there is an increasing need for cooperation between the service and the product organisations. Applying a service logic means that the traditional division between goods sales and after-sales services becomes outdated. Instead, the customer relationship becomes the centre of the offering regardless of its combination of services and goods. Further, the infusion of service in manufacturing firms means that more service processes and interfaces have to be managed simultaneously. Theoretically, this research contributes mainly to the fields of industrial marketing and service as a business logic. One contribution is the proposed typologies for industrial service offerings which make it possible to better understand the dynamics of service processes. Another important contribution of this research is the service function concept. Industrial services must not be equated with the activities of the industrial service organisation only. Although the service organisation most likely is the key entity, it is only one subset of the service function; sales product development, manufacturing, senior management, and other organisational entities, as well as external service providers and customers, are to be seen as part-time service functions that influence the offering. Compared to previously, competitive advantage through industrial service offerings is to a greater extent based on factors outside the service organisation, i.e. in other parts of the service function.

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Fragmentation in healthcare has led to a desire to align and integrate care processes horizontally. The concept of value-based healthcare has been introduced, suggesting a maximized value creation to occur when optimal conditions are created for selected patient segments, integrating all activities that jointly determine the success in meeting a set of patient needs. While targeting specialized segments has been shown to be beneficial, theories of diversification suggests that an increased scope may be an even more efficient approach to improve performance. By sharing resources and capabilities across several specialized units, coordination and knowledge sharing of a hospital’s ancillary services becomes important.   In this study, we examine how an ancillary service function, providing resources and capabilities that are shared across specialized units, can be organized to ensure contribution to the overarching goal of maximizing value for patients. This is done through a qualitative case study of the Karolinska University Laboratory – an ancillary service function of the Karolinska University Hospital. It is concluded that an ancillary service function can, in a diversified context, facilitate and support the value creation around medical conditions by developing a comprehensive structure for knowledge management and sharing, both externally towards medical conditions and internally within the ancillary service function. If structured properly, clear benefits, such as economies of scale, scope and knowledge spillovers, can be achieved by separating sharable resources from the patient flows.

This thesis deals with civil society organizations in the field of cinema in the Czech Republic. Cinematography is part of art and industry, with further influences of technology, culture, social or political situation. As in other areas there creates also civil society in the field of cinematography. The aim of this work is to determine the reasons are civil society organization formed and how they function. Due to the broad approach of the target group the research project work was targeted at those organizations that contribute to the development, support and promotion of Czech cinematography in general, and are the major players with the conceptual and strategic influence to the whole area.