Energy Efficiency and Quality of Services in Virtualized Cloud Radio Access Network

Cloud Radio Access Network (C-RAN) is being widely studied for soft and green fifth generation of Long Term Evolution - Advanced (LTE-A). The recent technology advancement in network virtualization function (NFV) and software defined radio (SDR) has enabled virtualization of Baseband Units (BBU) and sharing of underlying general purpose processing (GPP) infrastructure. Also, new innovations in optical transport network (OTN) such as Dark Fiber provides low latency and high bandwidth channels that can support C-RAN for more than forty-kilometer radius. All these advancements make C-RAN feasible and practical. Several virtualization strategies and architectures are proposed for C-RAN and it has been established that C-RAN offers higher energy efficiency and better resource utilization than the current decentralized radio access network (D-RAN). This project studies proposed resource utilization strategy and device a method to calculate power utilization. Then proposes and analyzes a new resource management and virtual BBU placement strategy for C-RAN based on demand prediction and inter-BBU communication load. The new approach is compared with existing state of art strategies with same input scenarios and load. The trade-offs between energy efficiency and quality of services is discussed. The project concludes with comparison between different strategies based on complexity of the system, performance in terms of service availability and optimization efficiency in different scenarios

Wetlands Classification: A Tool for Protection or Abandonment?

The notion of the networked society is more than ever true nowadays. The Internet has a big impact on our daily lives. Network operators provide the underlying infrastructure and continuously deploy services in order to meet customer demands. The amount of data transported through operator networks is also increasing with the introduction of new high band width services and over the network content. That being said, operators, most often deploy or operate networks to meet these demands without any regard to energy-efficiency. As the price of electricity continues to grow,  tends to become a problem with serious implications. To solve this problem a trend towards more energy efficient networks has emerged. In this thesis, we investigate a way to facilitate the introduction of new energy efficiency paradigms for fixed networks. Towards this end, we investigate the energy efficiency schemes proposed up to now and select one that we believe is more realistic to deploy. Furthermore, we specify the inputs required for the selected “green” routing approach. Moreover, we study existing and new protocols that can provide basic network monitoring functionality that enables the acquirement of these inputs. In the end, a Software Defined Networking (SDN) approach is proposed to facilitate the development of energy-efficient aware networks. The details of a basic SDN monitoring application are presented from an abstract architectural point of view and three designs stemming from this basic architecture are discussed. The three designs are namely All_Flow, First_Switch and Port_FlowRemoved. The first two were implemented as steps towards understanding the full capabilities of performing monitoring in SDN enabled networks and provided useful input towards realizing the third one as a proof of concept. Their usage and faults are discussed as they can provide useful insight for possible future implementations. The Port_FlowRemoved is the design and implementation that is suggested as providing the most fitting results for the monitoring purpose at hand. This purpose is to retrieve the identified inputs for the selected “green” networking approach. The differentiation factor among the three designs is how they collect the required inputs from the network. A fast-prototype is created as a proof of concept in order to validate the proposed architecture and thus empower the validity of the idea.

Security of Software-defined Wireless Sensor Networks

Wireless Sensor Network (WSN) using Software Defined Networking (SDN) can achieve several advantages such as flexible and centralized network management and efficient routing. This is because SDN is a logically centralized architecture that separates the control plane from the data plane. SDN can provide security solutions, such as routing isolation, while handling the heterogeneity, scalability, and the limited resources of WSNs. However, such centralized architecture brings new challenges due to the single attack point and having non-dedicated channels for the control plane in WSNs. In this thesis, we investigate and propose security solutions for software-defined WSNs considering energy-efficiency and resource-preservation. The details are as follows. First, the functionality of software-defined WSNs can be affected by malicious sensor nodes that perform arbitrary actions such as message dropping or flooding. The malicious nodes can degrade the availability of the network due to in-band communications and the inherent lack of secure channels in software-defined WSNs. Therefore, we design a hierarchical trust management scheme for software-defined WSNs (namely TSW) to detect potential threats inside software-defined WSNs while promoting node cooperation and supporting decision-making in the forwarding process. The TSW scheme evaluates the trustworthiness of involved nodes and enables the detection of malicious behavior at various levels of the software-defined WSN architecture. We develop sensitive trust computational models to detect several malicious attacks. Furthermore, we propose separate trust scores and parameters for control and data traffic, respectively, to enhance the detection performance against attacks directed at the crucial traffic of the control plane. Additionally, we develop an acknowledgment-based trust recording mechanism by exploiting some built-in SDN control messages. To ensure the resilience and honesty of the trust scores, a weighted averaging approach is adopted, and a reliability trust metric is also defined. Through extensive analyses and numerical simulations, we demonstrate that TSW is efficient in detecting malicious nodes that launch several communication and trust management threats such as black-hole, selective forwarding, denial of service, bad and good mouthing, and ON-OFF attacks. Second, network topology obfuscation is generally considered a proactive mechanism for mitigating traffic analysis attacks. The main challenge is to strike a balance among energy consumption, reliable routing, and security levels due to resource constraints in sensor nodes. Furthermore, software-defined WSNs are more vulnerable to traffic analysis attacks due to the uncovered pattern of control traffic between the controller and the nodes. As a result, we propose a new energy-aware network topology obfuscation mechanism, which maximizes the attack costs and is efficient and practical to be deployed. Specifically, first, a route obfuscation method is proposed by utilizing ranking-based route mutation, based on four different critical criteria: route overlapping, energy consumption, link costs, and node reliability. Then, a sink node obfuscation method is introduced by selecting several fake sink nodes that are indistinguishable from actual sink nodes, according to the k-anonymity model. As a result, the most suitable routes and sink nodes can be selected, and a highest obfuscation level can be reached without sacrificing energy efficiency. Finally, extensive simulation results demonstrate that the proposed methods strongly mitigate traffic analysis attacks and achieve effective network topology obfuscation for software-defined WSNs. In addition, the proposed methods reduce the success rate of the attacks while achieving lower energy consumption and longer network lifetime. Last, security networking functions, such as trust management and Intrusion Detection System (IDS), are deployed in WSNs to protect the network from multiple attacks. However, there are many resource and security challenges in deploying these functions. First, they consume tremendous nodes’ energy and computational resources, which are limited in WSNs. Another challenge is preserving the security at a sufficient level in terms of reliability and coverage. Watchdog nodes, as one of the main components in trust management, overhear and monitor other nodes in the network. Accordingly, a secure and energy-aware watchdog placement optimization solution is studied for software-defined WSNs. The solution balances the required energy consumption, computational resource, and security in terms of the honesty of the watchdog nodes. To this end, a multi-population genetic algorithm is proposed for the optimal placement of the watchdog function in the network given the comprehensive aspects of resources and security. Finally, simulation results demonstrate that the proposed solution robustly preserves security levels and achieves energy-efficient deployment. In summary, reactive and proactive security solutions are investigated, designed, and evaluated for software-defined WSNs. The novelty of these proposed solutions is not only efficient and robust security but also their energy awareness, which allows them to be practical on resource-constrained networks. Thus, this thesis is considered a significant advancement toward more trustworthy and dependable software-defined WSNs

Theory of Algorithm Suitability on Managing Radio Resources in Next Generation Mobile Networks

Beyond 2020, wireless networking model will be radically changed and oriented to business-driven concept as foreseen by the next generation mobile network (NGMN) alliance. As the available spectrum granted to a given operator is physically limited, new radio resource management techniques are required to ensure massive connectivity for wireless devices. Given this situation, we investigate in this paper how the key network functionalities as self-optimizing network (SON) must be thought to meet NGMN requirements. We propose therefore, algorithm suitability theory (AST) combined to the notion of network operator infrastructure convergence. The approach is based on software-defined networking (SDN) principle that allows an adaptability of the load balance algorithm to the dynamic network status. Besides, we use the concept of network function virtualization (NFV) that alleviates the constraint of confining the wireless devices to their home network operator only. Relying on these two technologies, we build AST through a lexicographic optimality criterion based on SPC (Status, Performance, and Complexity) order. Numerical results demonstrate a better network coverage verified by the improvement of metrics such as call blocking rate, spectrum efficiency, energy efficiency and load balance index

Theory of Algorithm Suitability on Managing Radio Resources in Next Generation Mobile Networks

Beyond 2020, wireless networking model will be radically changed and oriented to business-driven concept as foreseen by the next generation mobile network (NGMN) alliance. As the available spectrum granted to a given operator is physically limited, new radio resource management techniques are required to ensure massive connectivity for wireless devices. Given this situation, we investigate in this paper how the key network functionalities as self-optimizing network (SON) must be thought to meet NGMN requirements. We propose therefore, algorithm suitability theory (AST) combined to the notion of network operator infrastructure convergence. The approach is based on software-defined networking (SDN) principle that allows an adaptability of the load balance algorithm to the dynamic network status. Besides, we use the concept of network function virtualization (NFV) that alleviates the constraint of confining the wireless devices to their home network operator only. Relying on these two technologies, we build AST through a lexicographic optimality criterion based on SPC (Status, Performance, and Complexity) order. Numerical results demonstrate a better network coverage verified by the improvement of metrics such as call blocking rate, spectrum efficiency, energy efficiency and load balance index

Infrastructure sharing of 5G mobile core networks on an SDN/NFV platform

When looking towards the deployment of 5G network architectures, mobile network operators will continue to face many challenges. The number of customers is approaching maximum market penetration, the number of devices per customer is increasing, and the number of non-human operated devices estimated to approach towards the tens of billions, network operators have a formidable task ahead of them. The proliferation of cloud computing techniques has created a multitude of applications for network services deployments, and at the forefront is the adoption of Software-Defined Networking (SDN) and Network Functions Virtualisation (NFV). Mobile network operators (MNO) have the opportunity to leverage these technologies so that they can enable the delivery of traditional networking functionality in cloud environments. The benefit of this is reductions seen in the capital and operational expenditures of network infrastructure. When going for NFV, how a Virtualised Network Function (VNF) is designed, implemented, and placed over physical infrastructure can play a vital role on the performance metrics achieved by the network function. Not paying careful attention to this aspect could lead to the drastically reduced performance of network functions thus defeating the purpose of going for virtualisation solutions. The success of mobile network operators in the 5G arena will depend heavily on their ability to shift from their old operational models and embrace new technologies, design principles and innovation in both the business and technical aspects of the environment. The primary goal of this thesis is to design, implement and evaluate the viability of data centre and cloud network infrastructure sharing use case. More specifically, the core question addressed by this thesis is how virtualisation of network functions in a shared infrastructure environment can be achieved without adverse performance degradation. 5G should be operational with high penetration beyond the year 2020 with data traffic rates increasing exponentially and the number of connected devices expected to surpass tens of billions. Requirements for 5G mobile networks include higher flexibility, scalability, cost effectiveness and energy efficiency. Towards these goals, Software Defined Networking (SDN) and Network Functions Virtualisation have been adopted in recent proposals for future mobile networks architectures because they are considered critical technologies for 5G. A Shared Infrastructure Management Framework was designed and implemented for this purpose. This framework was further enhanced for performance optimisation of network functions and underlying physical infrastructure. The objective achieved was the identification of requirements for the design and development of an experimental testbed for future 5G mobile networks. This testbed deploys high performance virtualised network functions (VNFs) while catering for the infrastructure sharing use case of multiple network operators. The management and orchestration of the VNFs allow for automation, scalability, fault recovery, and security to be evaluated. The testbed developed is readily re-creatable and based on open-source software

Analysis, characterization and optimization of the energy efficiency on softwarized mobile platforms

Mención Internacional en el título de doctorLa inminente 5ª generación de sistemas móviles (5G) está a punto de revolucionar la industria, trayendo una nueva arquitectura orientada a los nuevos mercados verticales y servicios. Debido a esto, el 5G Infrastructure Public Private Partnership (5G-PPP) ha especificado una lista de Indicadores de Rendimiento Clave (KPI) que todo sistema 5G tiene que soportar, por ejemplo incrementar por 1000 el volumen de datos, de 10 a 100 veces m´as dispositivos conectados o consumos energéticos 10 veces inferiores. Con el fin de conseguir estos requisitos, se espera expandir los despligues actuales usando mas Puntos de Acceso (PoA) incrementando así su densidad con múltiples tecnologías inalámbricas. Esta estrategia de despliegue masivo tiene una contrapartida en la eficiencia energética, generando un conflicto con el KPI de reducir por 10 el consumo energético. En este contexto, la comunidad investigadora ha propuesto nuevos paradigmas para alcanzar los requisitos impuestos para los sistemas 5G, siendo materializados en tecnologías como Redes Definidas por Software (SDN) y Virtualización de Funciones de Red (NFV). Estos nuevos paradigmas son el primer paso hacia la softwarización de los despliegues móviles, incorporando nuevos grados de flexibilidad y reconfigurabilidad de la Red de Acceso Radio (RAN). En esta tesis, presentamos primero un análisis detallado y caracterización de las redes móviles softwarizadas. Consideramos el software como la base de la nueva generación de redes celulares y, por lo tanto, analizaremos y caracterizaremos el impacto en la eficiencia energética de estos sistemas. La primera meta de este trabajo es caracterizar las plataformas software disponibles para Radios Definidas por Software (SDR), centrándonos en las dos soluciones principales de código abierto: OpenAirInterface (OAI) y srsLTE. Como resultado, proveemos una metodología para analizar y caracterizar el rendimiento de estas soluciones en función del uso de la CPU, rendimiento de red, compatibilidad y extensibilidad de dicho software. Una vez hemos entendido qué rendimiento podemos esperar de este tipo de soluciones, estudiamos un prototipo SDR construido con aceleración hardware, que emplea una plataformas basada en FPGA. Este prototipo está diseñado para incluir capacidad de ser consciente de la energía, permiento al sistema ser reconfigurado para minimizar la huella energética cuando sea posible. Con el fin de validar el diseño de nuestro sistema, más tarde presentamos una plataforma para caracterizar la energía que será empleada para medir experimentalmente el consumo energético de dispositivos reales. En nuestro enfoque, realizamos dos tipos de análisis: a pequeña escala de tiempo y a gran escala de tiempo. Por lo tanto, para validar nuestro entorno de medidas, caracterizamos a través de análisis numérico los algoritmos para la Adaptación de la Tasa (RA) en IEEE 802.11, para entonces comparar nuestros resultados teóricos con los experimentales. A continuación extendemos nuestro análisis a la plataforma SDR acelerada por hardware previamente mencionada. Nuestros resultados experimentales muestran que nuestra sistema puede en efecto reducir la huella energética reconfigurando el despligue del sistema. Entonces, la escala de tiempos es elevada y presentamos los esquemas para Recursos bajo Demanda (RoD) en despliegues de red ultra-densos. Esta estrategia está basada en apagar/encender dinámicamente los elementos que forman la red con el fin de reducir el total del consumo energético. Por lo tanto, presentamos un modelo analítico en dos sabores, un modelo exacto que predice el comportamiento del sistema con precisión pero con un alto coste computacional y uno simplificado que es más ligero en complejidad mientras que mantiene la precisión. Nuestros resultados muestran que estos esquemas pueden efectivamente mejorar la eficiencia energética de los despliegues y mantener la Calidad de Servicio (QoS). Con el fin de probar la plausibilidad de los esquemas RoD, presentamos un plataforma softwarizada que sigue el paradigma SDN, OFTEN (OpenFlow framework for Traffic Engineering in mobile Network with energy awareness). Nuestro diseño está basado en OpenFlow con funcionalidades para hacerlo consciente de la energía. Finalmente, un prototipo real con esta plataforma es presentando, probando así la plausibilidad de los RoD en despligues reales.The upcoming 5th Generation of mobile systems (5G) is about to revolutionize the industry, bringing a new architecture oriented to new vertical markets and services. Due to this, the 5G-PPP has specified a list of Key Performance Indicator (KPI) that 5G systems need to support e.g. increasing the 1000 times higher data volume, 10 to 100 times more connected devices or 10 times lower power consumption. In order to achieve these requirements, it is expected to expand the current deployments using more Points of Attachment (PoA) by increasing their density and by using multiple wireless technologies. This massive deployment strategy triggers a side effect in the energy efficiency though, generating a conflict with the “10 times lower power consumption” KPI. In this context, the research community has proposed novel paradigms to achieve the imposed requirements for 5G systems, being materialized in technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). These new paradigms are the first step to softwarize the mobile network deployments, enabling new degrees of flexibility and reconfigurability of the Radio Access Network (RAN). In this thesis, we first present a detailed analysis and characterization of softwarized mobile networking. We consider software as a basis for the next generation of cellular networks and hence, we analyze and characterize the impact on the energy efficiency of these systems. The first goal of this work is to characterize the available software platforms for Software Defined Radio (SDR), focusing on the two main open source solutions: OAI and srsLTE. As result, we provide a methodology to analyze and characterize the performance of these solutions in terms of CPU usage, network performance, compatibility and extensibility of the software. Once we have understood the expected performance for such platformsc, we study an SDR prototype built with hardware acceleration, that employs a FPGA based platform. This prototype is designed to include energy-awareness capabilites, allowing the system to be reconfigured to minimize the energy footprint when possible. In order to validate our system design, we later present an energy characterization platform that we will employ to experimentally measure the energy consumption of real devices. In our approach, we perform two kind of analysis: at short time scale and large time scale. Thus, to validate our approach in short time scale and the energy framework, we have characterized though numerical analysis the Rate Adaptation (RA) algorithms in IEEE 802.11, and then compare our theoretical results to the obtained ones through experimentation. Next we extend our analysis to the hardware accelerated SDR prototype previously mentioned. Our experimental results show that our system can indeed reduce the energy footprint reconfiguring the system deployment. Then, the time scale of our analysis is elevated and we present Resource-on-Demand (RoD) schemes for ultradense network deployments. This strategy is based on dynamically switch on/off the elements that form the network to reduce the overall energy consumption. Hence, we present a analytic model in two flavors, an exact model that accurately predicts the system behaviour but high computational cost and a simplified one that is lighter in complexity while keeping the accuracy. Our results show that these schemes can effectively enhance the energy efficiency of the deployments and mantaining the Quality of Service (QoS). In order to prove the feasibility of RoD, we present a softwarized platform that follows the SDN paradigm, the OFTEN (Open Flow framework for Traffic Engineering in mobile Networks with energy awareness) framework. Our design is based on OpenFlow with energy-awareness functionalities. Finally, a real prototype of this framework is presented, proving the feasibility of the RoD in real deployments.FP7-CROWD (2013-2015) CROWD (Connectivity management for eneRgy Optimised Wireless Dense networks).-- H2020-Flex5GWare (2015-2017) Flex5GWare (Flexible and efficient hardware/software platforms for 5G network elements and devices).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Gramaglia , Marco.- Secretario: José Nuñez.- Vocal: Fabrizio Giulian

A secure and energy-aware approach for cognitive radio communications

The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radiospectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using sucha technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcityproblem and maximize spectrum efficiency. However, two major impediments have been limiting thewidespread adoption of cognitive radio technology. The software-defined radio technology, which is theenabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature ofthe CR can lead to major security concerns about the data being sent and how safe it is. In this paper,we introduce an energy-and-security-aware CR-based communication approach that alleviates the powerconsumption of the CR technique and enhances its security measures according to the confidentialitylevel of the data being sent. Furthermore, the proposed approach takes into account user-related factors,such as the user’s battery level and user’s data type, and network-related factors, such as the number ofunutilized bands and vulnerability level and then models the research question as a constrained optimizationproblem. Considering the time complexity of the optimum solution, we also propose a heuristic solution.We examine the proposed solution against existing solutions, and our obtained results show that theproposed approach can save energy consumption up to 18%, increase user throughput up to 20%, andachieve better spectrum utilization, up to 98%. Our proposed admission approach has the potential toopen a new research direction towards safer and greener cognitive radio techniques