Resource Allocation, and Survivability in Network Virtualization Environments

Network virtualization can offer more flexibility and better manageability for the future Internet by allowing multiple heterogeneous virtual networks (VN) to coexist on a shared infrastructure provider (InP) network. A major challenge in this respect is the VN embedding problem that deals with the efficient mapping of virtual resources on InP network resources. Previous research focused on heuristic algorithms for the VN embedding problem assuming that the InP network remains operational at all times. In this thesis, we remove that assumption by formulating the survivable virtual network embedding (SVNE) problem and developing baseline policy heuristics and an efficient hybrid policy heuristic to solve it. The hybrid policy is based on a fast re-routing strategy and utilizes a pre-reserved quota for backup on each physical link. Our evaluation results show that our proposed heuristic for SVNE outperforms baseline heuristics in terms of long term business profit for the InP, acceptance ratio, bandwidth efficiency, and response time

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR

Self-managed resources in network virtualisation environments

Network virtualisation is a promising technique for dealing with the resistance of the Internet to architectural changes, enabling a novel business model in which infrastructure management is decoupled from service provision. It allows infrastructure providers (InPs) who own substrate networks (SNs) to lease chunks of them out to service providers who then create virtual networks (VNs), which can then be re-leased out or used to provide services to end-users. However, the different VNs should be initialised, in which case virtual links and nodes must be mapped to substrate nodes and paths respectively. One of the challenges in the initialisation of VNs is the requirement of an efficient sharing of SN resources. Since the profitability of InPs depends on how many VNs are able to be allocated simultaneously onto the SN, the success of network virtualisation will depend, in part, on how efficiently VNs utilise physical network resources. This thesis contributes to efficient resource sharing in network virtualisation by dividing the problem into three sub-problems: (1) mapping virtual nodes and links to substrate nodes and paths i.e. virtual network embedding (VNE), (2) dynamic managing of the resources allocated to VNs throughout their lifetime (DRA), and (3) provisioning of backup resources to ensure survivability of the VNs. The constrained VNE problem is NP-Hard. As a result, to simplify the solution, many existing approaches propose heuristics that make assumptions (e.g. a SN with infinite resources), some of which would not apply in practical environments. This thesis proposes an improvement in VNE by proposing a one-shot VNE algorithm which is based on column generation (CG). The CG approach starts by solving a restricted version of the problem, and thereafter refines it to obtain a final solution. The objective of a one-shot mapping is to achieve better resource utilisation, while using CG significantly enhances the solution time complexity. In addition current approaches are static in the sense that after the VNE stage, the resources allocated are not altered for the entire lifetime of the VN. The few proposals that do allow for adjustments in original mappings allocate a fixed amount of node and link resources to VNs throughout their life time. Since network load varies with time due to changing user demands, allocating a fixed amount of resources based on peak load could lead to an inefficient utilisation of overall SN resources, whereby, during periods when some virtual nodes and/or links are lightly loaded, SN resources are still reserved for them, while possibly rejecting new VN requests. The second contribution of this thesis are a set of proposals that ensure that SN resources are efficiently utilised, while at the same making sure that the QoS requirements of VNs are met. For this purpose, we propose self-management algorithms in which the SN uses time-difference machine learning techniques to make autonomous decisions with respect to resource allocation. Finally, while some scientific research has already studied multi-domain VNE, the available approaches to survivable VNs have focused on the single InP environment. Since in the more practical situation a network virtualisation environment will involve multiple InPs, and because an extension of network survivability approaches from the single to multi domain environments is not trivial, this thesis proposes a distributed and dynamic approach to survivability in VNs. This is achieved by using a multi-agent-system that uses a multi-attribute negotiation protocol and a dynamic pricing model forming InPs coalitions supporting SNs resource backups. The ultimate objective is to ensure that virtual network operators maximise profitability by minimising penalties resulting from QoS violations.La virtualització de xarxes es una tècnica prometedora per afrontar la resistència d'Internet als canvis arquitectònics, que permet un nou model de negoci en el que la gestió de la infraestructura de xarxa es desacobla de la provisió del servei. Això permet als proveïdors de infraestructura (InPs), propietaris de la xarxa física substrat (SN), llogar segments d'aquesta als proveïdors dels serveis, que crearan xarxes virtuals (VNs) que a l'hora poden re-llogar-se o utilitzar-se per donar servei a usuaris finals. No obstant això, les diferents VNs s'han d'inicialitzar assignant els seus nodes i enllaços als del substrat. Un dels reptes d'aquest procés es el requisit de fer un ús eficient dels recursos de la SN. Donat que el benefici d'un InP depèn del nombre de xarxes virtuals que puguin allotjar-se simultàniament en la SN, l'èxit de la virtualització de xarxes depèn en part de quan eficient es l’ús dels recursos de la xarxa física per part de les VNs. Aquesta Tesi contribueix a la millora de l’eficiència en la compartició de recursos en la virtualització de xarxes dividint el problema en tres sots problemes: (1) assignació de nodes i enllaços virtuals a nodes i enllaços del substrat (VNE), (2) gestió dinàmica dels recursos assignats a les VNs al llarg de la seva vida útil (DRA) i (3) aprovisionament de recursos de backup per assegurar la supervivència de les VNs. La naturalesa del problema VNE el fa “NP-Hard". En conseqüència, per simplificar la solució, moltes de les propostes son heurístiques que es basen en hipòtesis (per exemple, SN amb recursos il•limitats) de difícil compliment en escenaris reals. Aquesta Tesi proposa una millora al problema VNE mitjan_cant un algorisme “one-shot VNE" basat en generació de columnes (CG). La solució CG comena resolent una versió restringida del problema, per tot seguit refinar-la i obtenir la solució final. L'objectiu del “one-shot VNE" es aconseguir millorar l’ús dels recursos, mentre que CG redueix significativament la complexitat temporal del procés. D'altre banda, les solucions actuals son estàtiques, ja que els recursos assignats en la fase VNE no es modifiquen durant tot el temps de vida útil de la VN. Les poques propostes que permeten reajustar l’assignació inicial, es basen en una assignació fixe de recursos a les VNs. No obstant això, degut a que la càrrega de la xarxa varia a conseqüència de la demanda canviant dels usuaris, assignar una quantitat fixe de recursos basada en situacions de càrrega màxima esdevé en ineficiència per infrautilització en períodes de baixa demanda, mentre que en tals períodes de demanda baixa, el tenir recursos reservats, pot originar rebutjos de noves VNs. La segona contribució d'aquesta Tesi es un conjunt de propostes que asseguren l’ús eficient dels recursos de la SN, garantint a la vegada els requeriments de qualitat de servei de totes les VNs. Amb aquesta finalitat es proposen algorismes d’autogestió en els que la SN utilitza tècniques d'aprenentatge de màquines per a materialitzar decisions autònomes en l’assignació dels recursos. Finalment, malgrat que diversos estudis han tractat ja el problema VNE en entorn multi-domini, les propostes actuals de supervivència de xarxes virtuals s'han limitat a contexts d'aprovisionament per part d'un sol InP. En canvi, a la pràctica, la virtualització de xarxes comportarà un entorn d'aprovisionament multi-domini, i com que l’extensió de solucions de supervivència d'un sol domini al multi-domini no es trivial, aquesta Tesi proposa una solució distribuïda i dinàmica per a la supervivència de VNs. Això s'aconsegueix amb un sistema multi-agent que utilitza un protocol de negociació multi-atribut i un model dinàmic de preus per formar coalicions d'InPs que proporcionaran backups als recursos de les SNs. L'objectiu últim es assegurar que els operadors de xarxes virtuals maximitzin beneficis minimitzant les penalitzacions per violació de la QoS.La virtualización de redes es una técnica prometedora para afrontar la resistencia de Internet a cambios arquitectónicos, que permite un nuevo modelo de negocio en el que la gestión de la infraestructura está desacoplada del aprovisionamiento del servicio. Esto permite a los proveedores de infraestructuras (InPs), propietarios de la red física subyacente (SN), alquilar segmentos de la misma a los proveedores de servicio, los cuales crearán redes virtuales (VNs), que a su vez pueden ser realquiladas o usadaspara proveer el servicio a usuarios finales. Sin embargo, las diferentes VNs deben inicializarse, mapeando sus nodos y enlaces en los del substrato. Uno de los retos de este proceso de inicialización es el requisito de hacer un uso eficiente de los recursos de la SN. Dado que el benecio de los InPs depende de cuantas VNs puedan alojarse simultáneamente en la SN, el éxito de la virtualización de redes depende, en parte, de cuan eficiente es el uso de los recursos de red físicos por parte de las VNs. Esta Tesis contribuye a la compartición eficiente de recursos para la virtualización de redes dividiendo el problema en tres sub-problemas: (1) mapeo de nodos y enlaces virtuales sobre nodos y enlaces del substrato (VNE), (2) gestión dinámica de los recursos asignados a las VNs a lo largo de su vida útil (DRA), y (3) aprovisionamiento de recursos de backup para asegurar la supervivencia de las VNs. La naturaleza del problema VNE lo hace “NP-Hard". En consecuencia, para simplificar la solución, muchas de las actuales propuestas son heurísticas que parten de unas suposiciones (por ejemplo, SN con recursos ilimitados) de difícil asumir en la práctica. Esta Tesis propone una mejora al problema VNE mediante un algoritmo “one-shot VNE" basado en generación de columnas (CG). La solución CG comienza resolviendo una versión restringida del problema, para después refinarla y obtener la solución final. El objetivo del “one-shot VNE" es mejorar el uso de los recursos, a la vez que con CG se reduce significativamente la complejidad temporal del proceso. Por otro lado,las propuestas actuales son estáticas, ya que los recursos asignados en la fase VNE no se alteran a lo largo de la vida útil de la VN. Las pocas propuestas que permiten reajustes del mapeado original ubican una cantidad fija de recursos a las VNs. Sin embargo, dado que la carga de red varía con el tiempo, debido a la demanda cambiante de los usuarios, ubicar una cantidad fija de recursos basada en situaciones de pico conduce a un uso ineficiente de los recursos por infrautilización de los mismos en periodos de baja demanda, mientras que en esta situación, al tener los recursos reservados, pueden rechazarse nuevas solicitudes de VNs. La segunda contribución de esta Tesis es un conjunto de propuestas para el uso eficiente de los recursos de la SN, asegurando al mismo tiempo la calidad de servicio de las VNs. Para ello se proponen algoritmos de auto-gestión en los que la SN usa técnicas de aprendizaje de máquinas para materializar decisiones autónomas en la asignación de recursos. Finalmente, aunque determinadas investigaciones ya han estudiado el problema multi-dominio VNE, las propuestas actuales de supervivencia de redes virtuales se han limitado a un entorno de provisión de infraestructura de un solo InP. Sin embargo, en la práctica, la virtualización de redes comportará un entorno de aprovisionamiento con múltiples InPs, y dado a que la extensión de las soluciones de supervivencia de un entorno único a uno multi-dominio no es trivial, esta Tesis propone una solución distribuida y dinámica a la supervivencia de VNs. Esto se consigue mediante un sistema multi-agente que usa un protocolo de negociación multi-atributo y un modelo dinámico de precios para conformar coaliciones de InPs para proporcionar backups a los recursos de las SNs. El objetivo último es asegurar que los operadores de VNs maximicen su beneficio minimizando la penalización por violación de la QoS

Traffic Scheduling in Software-defined Backhaul Network

In the past few years, severe challenges have arisen for network operators, as explosive growth and service differentiation in data demands require an increasing number of network capacity as well as dynamic traffic management. To adapt to the network densification, wireless backhaul solution is attracting more and more attentions due to its flexible deployment. Meanwhile, the software-defined network (SDN) proposes an promising architecture that can achieve dynamic control and management for various functionalities. In this case, by applying the SDN architecture to wireless backhaul networks, the traffic scheduling functionality may satisfy the ever-increasing and differentiated traffic demands. To tackle the traffic demand challenges, traffic scheduling for software-defined backhaul networks (SDBN) is investigated from three aspects in this thesis. In the first aspect, various virtual networks based on service types are embedded to the same wireless backhaul infrastructure. An algorithm, named VNE-SDBN, is proposed to solve the virtual network embedding (VNE) problem to improve the performance of the revenue of infrastructure providers and virtual network request acceptance ratio by exploiting the unique characteristics of SDBNs. In the second aspect, incoming traffic is scheduled online by joint routing and resource allocation approach in backhaul networks operated in low-frequency microwave (LFM) and those operated in millimetre wave (mmW). A digraph-based greedy algorithm (DBGA) is proposed considering the relationship between the degrees of vertices in the constructed interference digraph and system throughput with low complexity. In the third aspect, quality-of-service is provided in terms of delay and throughput with two proposed algorithms for backhaul networks with insufficient spectral resources. At last, as a trial research on E-band, a conceptual adaptive modulation system with channel estimation based on rain rate for E-band SDBN is proposed to exploit the rain attenuation feature of E-band. The results of the research works are mainly achieved through heuristic algorithms. Genetic algorithm, which is a meta-heuristic algorithm, is employed to obtain near-optimal solutions to the proposed NP-hard problems. Low complexity greedy algorithms are developed based on the specific problem analysis. Finally, the evaluation of proposed systems and algorithms are performed through numerical simulations. Simulations for backhaul networks with respect to VNE, routing and resource allocation are developed

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Mobile Ad hoc Networking: Imperatives and Challenges

Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, "ad-hoc" network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-existing communication infrastructure, e.g., disaster recovery environments. Ad hoc networking concept is not a new one, having been around in various forms for over 20 years. Traditionally, tactical networks have been the only communication networking application that followed the ad hoc paradigm. Recently, the introduction of new technologies such as the Bluetooth, IEEE 802.11 and Hyperlan are helping enable eventual commercial MANET deployments outside the military domain. These recent evolutions have been generating a renewed and growing interest in the research and development of MANET. This paper attempts to provide a comprehensive overview of this dynamic field. It first explains the important role that mobile ad hoc networks play in the evolution of future wireless technologies. Then, it reviews the latest research activities in these areas, including a summary of MANET\u27s characteristics, capabilities, applications, and design constraints. The paper concludes by presenting a set of challenges and problems requiring further research in the future

Machine Learning Meets Communication Networks: Current Trends and Future Challenges

The growing network density and unprecedented increase in network traffic, caused by the massively expanding number of connected devices and online services, require intelligent network operations. Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. Important future research challenges are identified and presented to help stir further research in key areas in this direction