Machine learning requirements for energy-efficient virtual network embedding

Network virtualization is a technology proven to be a key enabling a family of strategies in different targets, such as energy efficiency, economic revenue, network usage, adaptability or failure protection. Network virtualization allows us to adapt the needs of a network to new circumstances, resulting in greater flexibility. The allocation decisions of the demands onto the physical network resources impact the costs and the benefits. Therefore it is one of the major current problems, called virtual network embedding (VNE). Many algorithms have been proposed recently in the literature to solve the VNE problem for different targets. Due to the current successful rise of artificial intelligence, it has been widely used recently to solve technological problems. In this context, this paper investigates the requirements and analyses the use of the Q-learning algorithm for energy-efficient VNE. The results achieved validate the strategy and show clear improvements in terms of cost/revenue and energy savings, compared to traditional algorithms.This work has been supported by the Agencia Estatal de Investigación of Ministerio de Ciencia e Innovación of Spain under project PID2019-108713RB-C51 MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

Modelling and Design of Resilient Networks under Challenges

Communication networks, in particular the Internet, face a variety of challenges that can disrupt our daily lives resulting in the loss of human lives and significant financial costs in the worst cases. We define challenges as external events that trigger faults that eventually result in service failures. Understanding these challenges accordingly is essential for improvement of the current networks and for designing Future Internet architectures. This dissertation presents a taxonomy of challenges that can help evaluate design choices for the current and Future Internet. Graph models to analyse critical infrastructures are examined and a multilevel graph model is developed to study interdependencies between different networks. Furthermore, graph-theoretic heuristic optimisation algorithms are developed. These heuristic algorithms add links to increase the resilience of networks in the least costly manner and they are computationally less expensive than an exhaustive search algorithm. The performance of networks under random failures, targeted attacks, and correlated area-based challenges are evaluated by the challenge simulation module that we developed. The GpENI Future Internet testbed is used to conduct experiments to evaluate the performance of the heuristic algorithms developed

Network access selection in heterogeneous wireless networks

In heterogeneous wireless networks (HWNs), both single-homed and multi-homed terminals are supported to provide connectivity to users. A multiservice single-homed multi-mode terminal can support multiple types of services, such as voice call, file download and video streaming simultaneously on any one of the available radio access technologies (RATs) such as Wireless Local Area Network (WLAN), and Long Term Evolution (LTE). Consequently, a single-homed multi-mode terminal having multiple on-going calls may need to perform a vertical handover from one RAT to another. One of the major issues in HWNs is how to select the most suitable RAT for multiple handoff calls, and the selection of a suitable RAT for multiple-calls from a single-homed multi-mode terminal in HWNs is a group decision problem. This is because a single-homed multi-mode terminal can connect to only one RAT at a time, and therefore multiple handoff calls from the terminal have to be handed over to the same RAT. In making group decision for multiple-calls, the quality of service (QoS) requirements for individual calls needs to be considered. Thus, the RAT that most satisfies the QoS requirements of individual calls is selected as the most suitable RAT for the multiple-calls. Whereas most research efforts in HWNs have concentrated on developing vertical handoff decision schemes for a single call from a multi-mode terminal, not much has been reported in the literature on RAT-selection for multiple-calls from a single-homed multi-mode terminal in next generation wireless networks (NGWNs). In addition, not much has been done to investigate the sensitivity of RAT-selection criteria for multiple-calls in NGWNs. Therefore, this dissertation addresses these issues by focusing on following two main aspects: (1) comparative analysis of four candidate multi-criteria group decision-making (MCGDM) schemes that could be adapted for making RAT-selection decisions for multiple-calls, and (2) development of a new RAT-selection scheme named the consensus RAT-selection model. In comparative analysis of the candidate RAT-selection schemes, four MCGDM schemes namely: distance to the ideal alternative-group decision making (DIA-GDM), multiplicative exponent weighting-group decision making (MEW-GDM), simply additive weighting-group decision making (SAW-GDM), technique for order preference by similarity to Ideal solution-group decision making (TOPSIS-GDM) are considered. The performance of the multiple-calls RAT-selection schemes is evaluated using the MATLAB simulation tool. The results show that DIA-GDM and TOPSIS-GDM schemes are more suitable for multiple handoff calls than SAW-GDM and MEW-GDM schemes. This is because they are consistent and less-sensitive in making RAT-selection decision than the other two schemes, with regards to RAT-selection criteria (service price, data rate, security, battery power consumption and network delay) in HWNs. In addition, the newly developed RAT-selection scheme incorporates RAT-consensus level for improving RAT-selection decisions for multiple-calls. Numerical results conducted in MATLAB validate the effectiveness and performance of the newly proposed RAT-selection scheme for multiple-calls in HWNs

車両・無人航空機を活用した災害時情報共有のためのDTNプロトコル

電気通信大学202

An investigation of decision support knowledge production, transfer and adoption for it outsourcing

Information Technology Outsourcing (ITO) is a widely-adopted strategy for IT governance. ITO decisions are very complicated and challenging for many organisations. During the past three decades of ITO research, numerous decision support artefacts (e.g. frameworks, models, tools) to support organisational ITO decisions have been described in academic publications. However, the scope, rigour, relevance and adoption of this research by industry practitioners had not been assessed. This study investigates the production, transfer and adoption of academic research-generated knowledge for ITO decision support through multiple perspectives of ITO researchers and practitioners (e.g. IT managers, IT consultants) to provide insights into the research problem. A mixed-methods research approach underpinned by the critical realism paradigm is employed in this study. The study comprised three phases. In Phase A, the scope of extant research for supporting ITO decisions is identified through a systematic literature review and critical assessment of the rigour and relevance of this body of research is conducted using a highly regarded research framework. One hundred and thirty three articles on IT outsourcing (including cloud sourcing) were identified as ITO decision support academic literature. These articles suggested a range of Multiple Criteria Decision Making (MCDM), optimisation and simulation methods to support different IT outsourcing decisions. The assessment of these articles raised concerns about the limited use of reference design theories, validation and naturalistic evaluation in ITO decision support academic literature. Recommendations to enhance the rigour and relevance of ITO decision support research are made in this thesis. Phase B involved interviewing and surveying academic researchers who published academic literature on ITO decision support artefacts. This phase reports researchers’ reflections on their ITO research experience and knowledge transfer activities undertaken by them. The findings indicate researchers’ motivations, knowledge transfer mechanisms, and communication/ interaction channels with industry may explain effective knowledge transfer. Impact-minded researchers were significantly more effective than publication-minded researchers in knowledge transfer. In Phase C, interviews and a survey of practitioners engaged in IT outsourcing shed light on use of academic-generated knowledge. Academic research was the least used source of decision-making knowledge among ITO practitioners. Practitioners preferred to seek advice from their peers, IT vendors and consultants to inform their ITO decision making. Two communities of users and non-users of academic research were identified in our sample of ITO practitioners, with non-users forming the majority. Six factors that may influence the use of academic research by practitioners were identified. Non-users of academic research held perceptions that academic research was not timely, required too much time to read, was far from the real world and that it was not a commonly-used knowledge source for practitioners. Also, non-users of academic research read academic research less frequently and did not perceive themselves as an audience for academic research. This study engaged two fields of research: ITO decision support and academic knowledge transfer/utilisation (including research-practice gap). ITO decision support research provide the specific context for a critical assessment of academic knowledge production, transfer and adoption. For ITO DSS, this study identified the scope, rigour and relevance of the field, and improvement opportunities. This study confirms that a research-practice gap exists in the ITO decision support field as previously suggested by some scholars. Also, this study made a significant contribution to the highly complex and contested field of research utilisation and the research-practice gap. The relationship between research and practice in terms of knowledge production, transfer and utilisation is modelled using social system theory. Multiple theories are applied through a retroductive (abductive) analysis to shed light on the root causes of the research-practice gap. This study suggests that the lack of adequate appreciation of research relevance in academic reward schemes and the academic publishing structure are the main root causes of the research-practice gap in the knowledge production side. Moreover, various institutional mechanisms exist in knowledge transfer and adoption domains that influence the knowledge adoption channels of practitioners. As a result, academic research does not become a priority source of ITO decision support knowledge for practitioners. This study suggests that to overcome the barriers to academic research adoption by practitioners, the effective structural coupling mechanism between the system of science (knowledge production domain) and organisation systems (knowledge consumption domain) needs to be identified and activated

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

Algorithmen zum effizienten Deployment virtueller Netzwerkservices

Die Virtualisierung von Netzfunktionen (NFV, Network Function Virtualization) ist ein zentrales Konzept zukünftiger Mobilfunknetze: Statt wie in klassischen Netzen rein auf Hardwarekomponenten zu setzen, deren Logik untrennbar mit der eigentlichen Hardware verwoben ist, wird die Funktionalität in NFV-Netzen innerhalb virtueller Netzwerkfunktionen gekapselt und von der eigentlichen physischen Hardware separiert. Hochspezialisierte Hardwareboxen werden durch viel flexiblere Standardhardware ersetzt, auf der nun unterschiedliche Netzwerkfunktionen installiert werden können. Ein Kernkonzept dabei ist die Integration von Cloud Computing-Technologien innerhalb der Mobilfunk-Kerninfrastruktur: Dies ermöglicht es dem Mobilfunkprovider, die Konfiguration des Netzes viel dynamischer an die sich ständig verändernden Anforderungen des Marktes anzupassen. Sollen neue Netzwerkservices installiert werden, kann dazu ein Großteil der bereits vorhandenen physischen Infrastruktur wiederverwendet werden; die vorhandene Hardware muss nicht komplett ausgetauscht werden. Die Integration neuer Services erfolgt stattdessen durch den wesentlich kosteneffizienteren Austausch von (virtuellen) Netzwerkfunktionen -- und nicht durch Austausch von Hardware. Mobilfunkprovider werden in Zukunft in der Lage sein, viel einfacher und effizienter zusätzliche Netzfunktionen dort zuzuschalten, wo sie gebraucht werden, ohne dass jedes Mal Änderungen an der eigentlichen Hardware-Konfiguration erforderlich werden. Darüber hinaus können Netzfunktionen flexibel auf andere Komponenten migriert werden, wenn Hardwarekomponenten aus wartungstechnischen Gründen temporär oder dauerhaft außer Betrieb genommen werden. Die vorliegende Arbeit befasst sich mit der Thematik, wie sich derartige virtuelle Netzwerkservices innerhalb des physischen Netzwerks der Provider einbetten lassen. Im Mittelpunkt steht die Frage, auf welchen Hardwarekomponenten die verschiedenen (virtuellen) Netzwerkfunktionen installiert werden sollen. Aus theoretischer Sicht ist die optimale Berechnung eines solchen Deployments ein NP-hartes Optimierungsproblem. Optimale Algorithmen zur Lösung dieses Problems sind daher nur in sehr kleinen Szenarien anwendbar. Für die effiziente Lösung im Zusammenhang mit Szenarien realer Größenordnung kommen aus diesem Grund nur heuristische Ansätze in Betracht, die für die Bestimmung eines guten, aber nicht zwingenderweise optimalen Deployments entworfen werden. Die vorliegende Arbeit befasst sich mit der effizienten, heuristischen Lösung dieses NP-harten Deployment-Problems. Es wird zunächst eine Simulationsumgebung beschrieben, die die umfassende Evaluation von Deploymentalgorithmen ermöglicht. Anders als bisherige Simulationstools lässt sich die hier beschriebene Umgebung sehr einfach um neue Funktionen erweitern. Daran anschließend wird ein verteilter Deployment-Algorithmus vorgestellt, der virtuelle Netze innerhalb von Cloud-Infrastrukturen effizient einbetten kann (DPVNE, Distributed and Parallel Virtual Network Embedding). Kernidee hinter diesem Ansatz ist die Aufteilung der physischen Cloud-Infrastruktur in hierarchisch organisierte Netzwerkpartitionen. Dies ermöglicht die parallele Einbettung virtueller Netze. Durch die Verteilung des Berechnungsaufwands auf mehrere Knoten lässt sich das Deployment-Problem auch in Szenarien mit sehr großen Netzwerkinfrastrukturen lösen. Darüber hinaus wird ein Backtracking-basierter Algorithmus vorgestellt, mit dem das Deployment virtueller Netzwerkservices in NFV-Szenarien durchgeführt werden kann (CoordVNF, Coordinated deployment of Virtual Network Functions). In NFV-Szenarien liegt der Fokus auf der Betrachtung der Netzwerkservices, die zur Verarbeitung von Datenströmen innerhalb der Infrastruktur des Mobilfunkproviders installiert werden. Jeder Netzwerkservice besteht dabei aus mehreren (virtuellen) Netzwerkfunktionen, die verschiedene Operationen auf empfangene Daten anwenden und diese dann zur Weiterverarbeitung an andere Netzwerkfunktionen weitergeben. Die genaue Reihenfolge, in der die Datenströme durch die einzelnen Netzwerkfunktionen geroutet werden, ist dabei nicht eindeutig vorgegeben. Anders als in Cloud-Szenarien ist die Struktur der einzubettenden virtuellen Netze also in Teilen flexibel, was zu interessanten neuen, theoretischen Aspekten bzgl. des Deployment-Problems führt. Der CoordVNF-Algorithmus ist als einer der ersten Ansätze in der Lage, solche flexiblen NFV-Netzwerkservices effizient innerhalb der Infrastruktur des Mobilfunkproviders zu platzieren. Im Gegensatz zu bisherigen Verfahren kann CoordVNF auch im Zusammenhang mit größeren Infrastrukturen verwendet werden. Abschließend wird das Deployment ausfallsicherer Netzwerkservices diskutiert. In diesem Kontext wird beschrieben, wie sich die Robustheit eingebetteter NFV-Services durch Reservierung zusätzlicher Backup-Ressourcen erhöhen lässt. Aufbauend auf CoordVNF wird dann ein Deploymentalgorithmus vorgestellt, der in der Lage ist, Einbettungen gegenüber Ausfällen abzusichern (SVNF, Survivable deployment of Virtual Network Functions).Network Function Virtualization (NFV) is being considered as an emerging key technology for future mobile network infrastructures. In classical networks, network functions are tightly bound to specific hardware boxes. In contrast, in NFV networks, (software) functionality is separated from hardware components. Highly specific hardware boxes are being replaced by commodity computing, networking, and storage equipment, offering resources for hosting and running more than just one specific type of network function. One of the key concepts of NFV is the integration of cloud computing technology into the network core: This enables virtual network functions to be installed and deployed where they are needed; additional resources can be dynamically provided in times of high demand, whereas virtual functions can also be consolidated on a smaller hardware setting if demand decreases. NFV enables operators to manage network functions in a much more flexible way, without having the need of instructing technicians to manually reconfigure hardware equipment on-site -- instead, network functions can be deployed and managed remotely. Additionally, for reliability reasons, virtual network functions can be easily migrated to backup resources in case of hardware or software failures. This thesis discusses the question on how those virtual network functions can be efficiently deployed within the physical network infrastructure. From a theoretical perspective, finding the optimal deployment of virtual network services (e.g., in terms of embedding cost) is known as a NP-hard optimization problem. In this context, the thesis introduces heuristic approaches for solving the deployment problem. To this end, first, an extensible simulation framework is discussed which enables researchers to thoroughly evaluate both existing and novel deployment algorithms. Second, a distributed algorithm (DPVNE) is presented for embedding virtual networks into a shared physical cloud infrastructure. Here, the main idea is to partition the physical network into several smaller, non-overlapping network regions. Embeddings in those network partitions can then be performed in parallel: Computational efforts can be spread to multiple distributed nodes. This way, solving this NP-hard optimization problem becomes feasible even in large-scale network scenarios where virtual network deployment requests arrive continuously. Third, a backtracking-based algorithm (CoordVNF) is presented in this thesis for the deployment of virtual network functions in NFV scenarios. In contrast to cloud scenarios, in NFV scenarios, the exact chaining of network functions is not always predefined: In fact, the same network service can be provided by several chainings of network functions. The first embedding algorithm presented here aims to deploy those flexible virtual network services in a cost- and time-efficient way, even in large-scale scenarios. Finally, the thesis discusses the deployment of resilient NFV services; in this context, an extension of the CoordVNF algorithm is presented that allocates additional backup resources for protecting network services from failures