Academic literature on the topic 'Service Function Chains'

New services and ever increasing traffic volumes require the next generation of mobile networks, e.g. 5G, to be much more flexible and scalable. The primary enabler for its flexibility is transforming network functions from proprietary hardware to software using modern virtualization technologies, paving the way of virtual network functions (VNF). Such VNFs can then be flexibly deployed on cloud data centers while traffic is routed along a chain of VNFs through software-defined networks. However, such flexibility comes with a new challenge of allocating efficient computational resources to each VNF and optimally placing them on a cluster. In this thesis, we argue that, to achieve an autonomous and efficient performance optimization method, a solid understanding of the underlying system, service chains, and upcoming traffic is required. We, therefore, conducted a series of focused studies to address the scalability and performance issues in three stages. We first introduce an automated profiling and benchmarking framework, named NFV-Inspector to measure and collect system KPIs as well as extract various insights from the system. Then, we propose systematic methods and algorithms for performance modelling and resource recommendation of cloud native network functions and evaluate them on a real 5G testbed. Finally, we design and implement a bottom-up performance simulator named PerfSim to approximate the performance of service chains based on the nodes’ performance models and user-defined scenarios.

Recent advancements in mobile communication technology have led to the fifth generation of mobile cellular networks (5G), driven by the proliferation in data traffic demand, stringent latency requirements, and the desire for a fully connected world. This transformation calls for novel technology solutions such as Multi-access Edge Computing (MEC) and Network Function Virtualization (NFV) to satisfy service requirements while providing dynamic and instant service deployment. MEC and NFV are two principal and complementary enablers for 5G networks whose co-existence can lead to numerous benefits. Despite the numerous advantages MEC offers, physical resources at the edge are extremely scarce and require efficient utilization. In this doctoral dissertation, we first attempt to optimize resource utilization at the network edge for the scenario of live video streaming. We specifically utilize the real-time Radio Access Network (RAN) information available at the MEC servers to develop a machine learning-based prediction solution and anticipate user requests. Consequently, Integer Linear Programming (ILP) models are used to prefetch/cache video contents from a centralized video server. Regarding the advantages of NFV technology for the deployment of NFs, the second problem that this dissertation address is the proper association of the users to the gNBs along with efficient placement of SFCs on the substrate network. Our primary purpose is to find a proper embedding of the SFC in a hierarchical 5G network. The problem is formulated as a Mixed Integer Linear Programming (MILP) model, having the objective to minimize service provisioning cost, link utilization, and the effect of VNF migration on users' perceived quality of experience. After rigorously analyzing the proposed SFC placement and considering mobile networks' dynamicity, our next goal is to develop an ILP-based model that minimizes the resource provisioning cost by dynamically embed and scale SFCs so that provisioning cost is minimized while user requirements are met.

By virtue of the recent technological developments in cloud computing, more applications are deployed in a cloud. Among these modern cloud-based applications, some require bounded and predictable low-latency responses. However, the current cloud infrastructure is unsuitable as it cannot satisfy these requirements, due to many limitations in both hardware and software. This licentiate thesis describes attempts to reduce the latency of Internet services by carefully studying the currently available infrastructure, optimizing it, and improving its performance. The focus is to optimize the performance of network functions deployed on commodity hardware, known as network function virtualization (NFV). The performance of NFV is one of the major sources of latency for Internet services. The first contribution is related to optimizing the software. This project began by investigating the possibility of superoptimizing virtualized network functions(VNFs). This began with a literature review of available superoptimization techniques, then one of the state-of-the-art superoptimization tools was selected to analyze the crucial metrics affecting application performance. The result of our analysis demonstrated that having better cache metrics could potentially improve the performance of all applications. The second contribution of this thesis employs the results of the first part by taking a step toward optimizing cache performance of time-critical NFV service chains. By doing so, we reduced the tail latencies of such systems running at 100Gbps. This is an important achievement as it increases the probability of realizing bounded and predictable latency for Internet services.<br>Tack vare den senaste tekniska utvecklingen inom beräkningar i molnet(“cloud computing”) används allt fler tillämpningar i molnlösningar. Flera avdessa moderna molnbaserade tillämpningar kräver korta svarstider är låga ochatt dessa ska vara förutsägbara och ligga inom givna gränser. Den nuvarandemolninfrastrukturen är dock otillräcklig eftersom den inte kan uppfylla dessa krav,på grund av olika typer av begränsningar i både hårdvara och mjukvara. I denna licentiatavhandling beskrivs försök att minska fördröjningen iinternettjänster genom att noggrant studera den nuvarande tillgängligainfrastrukturen, optimera den och förbättra dess prestanda. Fokus ligger påatt optimera prestanda för nätverksfunktioner som realiseras med hjälp avstandardhårdvara, känt som nätverksfunktionsvirtualisering (NFV). Prestanda hosNFV är en av de viktigaste källorna till fördröjning i internettjänster. Det första bidraget är relaterat till att optimera mjukvaran. Detta projektbörjade med att undersöka möjligheten att “superoptimera” virtualiseradenätverksfunktioner (VNF). Detta inleddes med en litteraturöversikt av tillgängligasuperoptimeringstekniker, och sedan valdes ett av de toppmodernasuperoptimeringsverktygen för att analysera de viktiga mätvärden som påverkartillämpningssprestanda. Resultatet av vår analys visade att bättre cache-mätningar potentiellt skulle kunna förbättra prestanda för alla tillämpningar. Det andra bidraget i denna avhandling utnyttjar resultaten från den förstadelen genom att ta ett steg mot att optimera cache-prestanda för tidskritiskakedjor av NFV-tjänster. Genom att göra så reducerade vi de långa fördröjningarnahos sådana system som kördes vid 100 Gbps. Detta är en viktig bedrift eftersomdetta ökar sannolikheten för att uppnå en begränsad och förutsägbar fördrörninghos internettjänster.<br><p>QC 20190415</p><br>Time-Critical Clouds<br>ULTRA

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.

Orientador: Franco Giuseppe Dedini<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica<br>Made available in DSpace on 2018-08-17T05:45:09Z (GMT). No. of bitstreams: 1 Abreu_PollyannaSilva_M.pdf: 3581814 bytes, checksum: e1e25ece993ce9c23f6bbc11ec80b9f8 (MD5) Previous issue date: 2010<br>Resumo: Neste trabalho buscou-se a utilização de instrumentos, técnicas e procedimentos da Psicologia, para auxiliar a tradução das necessidades básicas de clientes em uma forma estruturada, para o levantamento da Voz do Cliente, a fim de auxiliar na aplicação do método Desdobramento da Função Qualidade (QFD). A pesquisa foi realizada com usuários de cadeira de rodas e, por meio de questionários abertos e fechados, e análises qualitativas e quantitativas dos dados obtidos, foram levantadas as principais necessidades dos cadeirantes em relação à cadeira de rodas. As necessidades levantadas foram divididas em parâmetros, traduzidas em requisitos de engenharia e inseridas na Matriz I (Casa da Qualidade) do QFD. Os processos adotados são sugeridos para equipes com profissionais de diversas áreas, como metodologia válida, para levantamento da Voz do Cliente. A Matriz construída possibilitará estabelecer alguns requisitos para soluções possíveis de projeto de cadeira de rodas<br>Abstract: This work aimed to utilize instruments, techniques and procedures of the psychology science to help in the translation the basic necessities of the clients in a well arranged form, known as client voice, in order to aid in the application of the Quality Function Deployment(QFD). The research was carried out with Wheel chair users and utilizing both open and closed questionnaires and both qualitative and quantitative analysis of the obtained data, the main client necessities was raised in regard to the Wheel chairs. The necessities raised was divided in parameters which were translated in requisites of engineering and then inserted in the Matrix (House of the Quality) of the QFD. The processes taken as basis are suggested to teams with Professionals from several areas, as a valid methodology to survey the client voice. The generated Matrix will enable to establish some requisite to possible solutions of wheel chairs projects<br>Mestrado<br>Mecanica dos Sólidos e Projeto Mecanico<br>Mestre em Engenharia Mecânica

Thesis (MBA (Business Management))--Stellenbosch University, 2009.<br>ENGLISH ABSTRACT: A typical medium-sized service company in South Africa faces definite challenges and misses opportunities in optimising and managing its operational expenses in its sourcing and supply chain. Medium-sized companies generally do not have the benefit of sophisticated in-house procurement divisions and extensive buying power but they still have to optimise their expenses in order to ensure maximum profitability and business longevity. The study addresses these challenges and opportunities by developing and proposing a framework for a typical medium-sized service company that does not have a central procurement function related to the cost optimisation and management of the identified sourcing and supply-chain elements. The research process entails the development of a conceptual framework developed from literature analysis and a representational practical environment as well as the testing, reviewing and validating of the test implementation of the framework. The results flowing from the testing and implementation of the framework are excluded from the research project. The results are displayed in the form of a summary of specific relevant information around each framework element as well as a conceptual framework. Recommendations are made in relation to the implementation and practical adaptation of the framework. It is concluded that a medium-sized service company can successfully optimise and manage its costs in the sourcing and supply-chain elements in the absence of a central procurement function. This requires the effective implementation of the developed framework, which was adapted from sophisticated larger companies. Implementation and the measurement process need to be driven or, preferably, conducted by the medium-sized company owner or management. Buy-in of the framework and the processes around it needs to be obtained from employees, suppliers and other stakeholders.<br>AFRIKAANSE OPSOMMING: ’n Tipiese mediumgrootte diensverskaffingsonderneming in Suid-Afrika staar spesifieke uitdagings in die gesig en ontbeer geleenthede met betrekking tot die optimalisering en bestuur van die bedryfsuitgawes in sy aankoop- en verskaffingsketting. Mediumgrootte ondernemings beskik in die algemeen nie oor die voordeel van ’n gesofistikeerde interne aankoopafdeling en groot aankoopkrag nie, maar hierdie ondernemings moet nog steeds hulle koste-uitgawes optimaliseer in die nastreef van maksimale wins en besigheidsukses. Die navorsingstudie neem hierdie uitdagings en geleenthede onder die loep deur die ontwikkeling en aanbeveling van ’n raamwerk vir ’n tipiese mediumgrootte diensverskaffingsonderneming wat nie oor ’n sentrale interne aankoopafdeling beskik nie. Die raamwerk is gebaseer op koste-optimalisering en -bestuur van die geïdentifiseerde aankoop- en verskaffingskettingelemente. Die navorsingsproses behels die ontwikkeling van ’n konseptuele raamwerk deur literatuuranalise en ’n verteenwoordigende praktiese omgewing, sowel as die toetsing, hersiening en geldigverklaring van die raamwerk tydens die toets-implementering daarvan in die praktiese omgewing. Die resultate van die toets en implementering van die raamwerk vorm nie deel van hierdie studie nie. Die navorsingsresultate word ten toon gestel in die vorm van ’n opsomming van die relevante raamwerkelemente sowel as ’n ontwikkelde raamwerk. Aanbevelings ten opsigte van die implementering en praktiese aanpassing van die raamwerk word dan gemaak. Die gevolgtrekking word gemaak dat ’n mediumgrootte diensverskaffingsonderneming wel in die afwesigheid van ’n sentrale interne aankoopafdeling sy kostes in die aankoop- en verskaffingsketting suksesvol kan optimaliseer en bestuur. Dit kan gedoen word deur die doeltreffende implementering en aanwending van die ontwikkelde raamwerk wat vanaf groter ondernemings aangepas is. Die raamwerk se implementering- en metingsproses moet deur die eienaar of bestuur van die mediumgrootte onderneming gelei, of verkieslik uitgevoer, word. Die werknemers, verskaffers en ander belanghebbendes se ondersteuning vir die raamwerk en gepaardgaande prosesse is baie belangrik vir die implementering en sukses van die raamwerk.

Supply Chain Event Management (SCEM) bezeichnet eine Teildisziplin des Supply Chain Management und ist für Unternehmen ein Ansatzpunkt, durch frühzeitige Reaktion auf kritische Ausnahmeereignisse in der Wertschöpfungskette Logistikleistung und -kosten zu optimieren. Durch Rahmenbedingungen wie bspw. globale Logistikstrukturen, eine hohe Artikelvielfalt und volatile Geschäftsbeziehungen zählt die Modeindustrie zu den Branchen, die für kritische Störereignisse besonders anfällig ist. In diesem Sinne untersucht die vorliegende Dissertation nach einer Beleuchtung der wesentlichen Grundlagen zunächst, inwiefern es in der Modeindustrie tatsächlich einen Bedarf an SCEM-Systemen gibt. Anknüpfend daran zeigt sie nach einer Darstellung bisheriger SCEM-Architekturkonzepte Gestaltungsmöglichkeiten für eine Systemarchitektur auf, die auf den Designprinzipien der Serviceorientierung beruht. In diesem Rahmen erfolgt u. a. auch die Identifikation SCEM-relevanter Business Services. Die Vorzüge einer serviceorientierten Gestaltung werden detailliert anhand der EPCIS (EPC Information Services)-Spezifikation illustriert. Abgerundet wird die Arbeit durch eine Betrachtung der Nutzenpotenziale von SCEM-Systemen. Nach einer Darstellung von Ansätzen, welche zur Nutzenbestimmung infrage kommen, wird der Nutzen anhand eines Praxisbeispiels aufgezeigt und fließt zusammen mit den Ergebnissen einer Literaturrecherche in eine Konsolidierung von SCEM-Nutzeffekten. Hierbei wird auch beleuchtet, welche zusätzlichen Vorteile sich für Unternehmen durch eine serviceorientierte Architekturgestaltung bieten. In der Schlussbetrachtung werden die wesentlichen Erkenntnisse der Arbeit zusammengefasst und in einem Ausblick sowohl beleuchtet, welche Relevanz die Ergebnisse der Arbeit für die Bewältigung künftiger Herausforderungen innehaben als auch welche Anknüpfungspunkte sich für anschließende Forschungsarbeiten ergeben.