Efficient Resource Allocation and Spectrum Trading for Virtualized Multi-tenant 5G Networks

The huge increase of mobile devices and user data demand has initiated efforts for more efficient mobile network solutions. To this direction, virtualization has attracted much attention as a promising solution for higher resource utilization and improved system performance. Therefore, basic on-demand wireless resource allocation approaches among multiple tenants are investigated. Taking also into consideration two contrasting terms, the spectrum scarcity and the spectrum underutilization, this work proposes spectrum trading among frequency owners and tenants, enabling dynamic spectrum access and optimal management

Seamless LTE-WiFi Architecture for Offloading the Overloaded LTE with Efficient UE Authentication

Nowadays a cellular network suffers from a data traffic load in a metropolitan area due to the enormous number of mobile devices connectivity. Therefore, the users experience many issues because of a congestion and overload at an access network such as low throughput, long latencies and network outages. Current network operator’s solutions, such as capping data usage and throttling a connection speed, have a negative effect on the user satisfaction. Therefore, alternative solutions are needed such as Access Point (AP)-based complementary network. In this paper, we use WiFi as a complementary network to Long-Term Evolution (LTE). We propose a seamless network architecture between LTE and WiFi networks, by utilizing the packet gateway (P-GW) as an IP flow anchor between LTE and WiFi to maintain a seamless connectivity. The proposed architecture has two new components, Access Network Query Protocol-Data Server (ANQP-DS) and Access Zone Control (AZC), to WiFi core network for managing UE authentication and balancing the load of UEs between APs. Finally, we demonstrate and validate the effectiveness of our proposed idea over other prior approaches based on comparison with a current handover and Extensible Authentication Protocol-Authentication and Key Agreement (EAP-AKA) mechanisms in the literature through simulations

Traffic Management in LTE-WiFi Slicing Networks

Proliferation of the number of smart devices and user applications has generated a tremendous volume of data traffic from/to a cellular network. With a traditional cellular network, a user may experience many drawbacks such as low throughput, large latencies and network outages due to overload of data traffic. The software defined networking (SDN) and network function virtualization (NFV) rise as a promising solution to overcome such issues of traditional network architecture. In this paper, we introduce a new network architecture for LTE and WiFi slicing networks taking into account the advantage of SDN and NFV concepts. We propose an IP-Flow management controller in a slicing network to offload and balance the data traffic flow. By utilizing the P-GW and Wireless Access Gateway, we can handle the IP-Flow between LTE and WiFi networks. The P-GW works as an IP-Flow anchor to maintain the flow seamlessly during the offloading and balancing IP-Flow. Within WiFi networks, we leverage the Light Virtual Access Point (LVAP) approach to abstract the WiFi protocol stack for a programming capability of centralized control of WiFi network through the WiFi controller. By creating a client virtual port and assigning a specific Service Set Identifier (SSID), we give a capability to slice an operator’s network to control over his clients within a WiFi coverage area network

Matching theory as enabler of efficient spectrum management in 5G networks

This is the peer reviewed version of the following article: Tsirakis, C, Lopez‐Aguilera, E, Agapiou, G, Varoutas, D. Matching theory as enabler of efficient spectrum management in 5G networks. Trans Emerging Tel Tech. 2020; 31:e3769., which has been published in final form at https://doi.org/10.1002/ett.3769. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.This paper analyzes the spectrum trading problem in virtualized fifth generation (5G) networks in order to enhance the network performance with respect to the spectrum utilization. The problem is modeled as a Many-to-Many Matching (M2MM) game with utility-based preferences and determines the matching between mobile network operators and mobile virtual network operators. The two proposed versions of utility functions for each set aim at maximizing the satisfaction of both sets with conflicting interests and improving the overall spectrum efficiency. In the simulation evaluation, the proposed scheme is compared with three different schemes in terms of the system utility, individual and pair matching satisfaction. We also investigate the scalability aspects, the strategy plan impact on the matching performance of our proposed scheme, and, at the same time, we attempt to make appropriate assumptions closer to reality. Our proposed scheme shows much better performance than the other schemes achieving a quite high level of satisfaction for the matching result on both sets.Postprint (author's final draft

User Oriented Resource Management with Virtualization: A Hierarchical Game Approach

The explosive advancements in mobile Internet and Internet of Things challenge the network capacity and architecture. The ossification of wireless networks hinders the further evolution towards the fifth generation of mobile communication systems. Ultra-dense small cell networks are considered as a feasible way to meet high-capacity demands. Meanwhile, ultradense small cell network virtualization also exploits an insightful perspective for the evolution because of

MODELING AND RESOURCE ALLOCATION IN MOBILE WIRELESS NETWORKS

We envision that in the near future, just as Infrastructure-as-a-Service (IaaS), radios and radio resources in a wireless network can also be provisioned as a service to Mobile Virtual Network Operators (MVNOs), which we refer to as Radio-as-a-Service (RaaS). In this thesis, we present a novel auction-based model to enable fair pricing and fair resource allocation according to real-time needs of MVNOs for RaaS. Based on the proposed model, we study the auction mechanism design with the objective of maximizing social welfare. We present an Integer Linear Programming (ILP) and Vickrey-Clarke-Groves (VCG) based auction mechanism for obtaining optimal social welfare. To reduce time complexity, we present a polynomial-time greedy mechanism for the RaaS auction. Both methods have been formally shown to be truthful and individually rational. Meanwhile, wireless networks have become more and more advanced and complicated, which are generating a large amount of runtime system statistics. In this thesis, we also propose to leverage the emerging deep learning techniques for spatiotemporal modeling and prediction in cellular networks, based on big system data. We present a hybrid deep learning model for spatiotemporal prediction, which includes a novel autoencoder-based deep model for spatial modeling and Long Short-Term Memory units (LSTMs) for temporal modeling. The autoencoder-based model consists of a Global Stacked AutoEncoder (GSAE) and multiple Local SAEs (LSAEs), which can offer good representations for input data, reduced model size, and support for parallel and application-aware training. Mobile wireless networks have become an essential part in wireless networking with the prevalence of mobile device usage. Most mobile devices have powerful sensing capabilities. We consider a general-purpose Mobile CrowdSensing(MCS) system, which is a multi-application multi-task system that supports a large variety of sensing applications. In this thesis, we also study the quality of the recruited crowd for MCS, i.e., quality of services/data each individual mobile user and the whole crowd are potentially capable of providing. Moreover, to improve flexibility and effectiveness, we consider fine-grained MCS, in which each sensing task is divided into multiple subtasks and a mobile user may make contributions to multiple subtasks. More specifically, we first introduce mathematical models for characterizing the quality of a recruited crowd for different sensing applications. Based on these models, we present a novel auction formulation for quality-aware and fine- grained MCS, which minimizes the expected expenditure subject to the quality requirement of each subtask. Then we discuss how to achieve the optimal expected expenditure, and present a practical incentive mechanism to solve the auction problem, which is shown to have the desirable properties of truthfulness, individual rationality and computational efficiency. In a MCS system, a sensing task is dispatched to many smartphones for data collections; in the meanwhile, a smartphone undertakes many different sensing tasks that demand data from various sensors. In this thesis, we also consider the problem of scheduling different sensing tasks assigned to a smartphone with the objective of minimizing sensing energy consumption while ensuring Quality of SenSing (QoSS). First, we consider a simple case in which each sensing task only requests data from a single sensor. We formally define the corresponding problem as the Minimum Energy Single-sensor task Scheduling (MESS) problem and present a polynomial-time optimal algorithm to solve it. Furthermore, we address a more general case in which some sensing tasks request multiple sensors to re- port their measurements simultaneously. We present an Integer Linear Programming (ILP) formulation as well as two effective polynomial-time heuristic algorithms, for the corresponding Minimum Energy Multi-sensor task Scheduling (MEMS) problem. Numerical results are presented to confirm the theoretical analysis of our schemes, and to show strong performances of our solutions, compared to several baseline methods

Taxonomías de soluciones de Internet de las cosas orientadas a personas con discapacidades

El Internet de las Cosas (IoT - Internet of Things) ha revolucionado los sistemas y la conectividad a nivel mundial. Éste permite que cientos de dispositivos puedan recopilar información, enviar y recibir datos a través de Internet. El IoT ha sido aplicado en diversos campos, no siendo la excepción el ámbito médico; entre sus aplicaciones se encuentra el apoyo al personal sanitario, durante el tratamiento de personas con discapacidades, el uso de estos dispositivos interconectados ha permitido que estas personas desarrollen actividades de manera autónoma, ayudando en la mejora de su calidad de vida. En el contexto de la expansión de IoT a nivel mundial, se ve la necesidad de concentrar los estudios y las soluciones en un trabajo que articule, clasifique y evidencie las soluciones abordadas por diferentes grupos de investigación a nivel mundial. Para cubrir esta necesidad, hacen falta estudios secundarios que reúnan la evidencia técnica y científica de manera apropiada y que permitan encontrar brechas de investigación útiles para el avance científico y la no duplicidad de soluciones existentes. En este proyecto se desarrollará una revisión científica, repetible y replicable de la literatura para obtener una base sólida de soluciones IoT que solventen problemas para personas con discapacidad, se empleará la metodología de Kitchenham, se iniciará con una selección exhaustiva de investigaciones primarias relevantes para este proyecto, a continuación, se evaluará la calidad de los estudios seleccionados según una lista de comprobación que defina los factores a ser revisados, finalmente se extraerá y sintetizará los datos relevantes encontrados, los mismos que facilitarán el planteamiento de taxonomías que aporten a los profesionales de la salud en la toma de decisiones para diagnósticos, pronósticos y tratamientos para personas con discapacidades.The Internet of Things (IoT - Internet of Things) has revolutionized systems and connectivity worldwide. It allows hundreds of devices to collect information, send and receive data over the Internet. The IoT has been applied in various fields, the medical field not being the exception; Among its applications is the support to health personnel, during the treatment of people with disabilities, the use of these interconnected devices, has allowed these people to develop activities independently, helping to improve their quality of life. In the context of the expansion of IoT worldwide, there is a need to concentrate studies and solutions in a work that articulates, classifies and evidences the solutions addressed by different research groups worldwide. To cover this need, secondary studies are needed that gather the technical and scientific evidence in an appropriate way and that allow finding useful research gaps for scientific advancement and the non-duplication of existing solutions. In this project, a scientific, repeatable and replicable review of the literature will be developed to obtain a solid base of IoT solutions that solve problems for people with disabilities, the Kitchenham methodology will be used, it will begin with an exhaustive selection of primary research relevant to this project, then the quality of the selected studies will be evaluated according to a checklist that defines the factors to be reviewed, finally the relevant data found will be extracted and synthesized, the same that will facilitate the approach of taxonomies that contribute to the professionals of health in decision-making for diagnoses, prognoses and treatments for people with disabilities.Magíster en Gestión Estratégica de Tecnologías de la InformaciónCuenc

SLICING-BASED RESOURCE ALLOCATION AND MOBILITY MANAGEMENT FOR EMERGING WIRELESS NETWORKS

The proliferation of smart mobile devices and user applications has continued to contribute to the tremendous volume of data traffic in cellular networks. Moreover, with the feature of heterogeneous connectivity interfaces of these smart devices, it becomes more complex for managing the traffic volume in the context of mobility. To surmount this challenge, service and resource providers are looking for alternative mechanisms that can successfully facilitate managing network resources and mobility in a more dynamic, predictive and distributed manner. New concepts of network architectures such as Software-Defined Network (SDN) and Network Function Virtualization (NFV) have paved the way to move from static to flexible networks. They make networks more flexible (i.e., network providers capable of on-demand provisioning), easily customizable and cost effective. In this regard, network slicing is emerging as a new technology built on the concepts of SDN and NFV. It splits a network infrastructure into isolated virtual networks and allows them to manage network resources based on their requirements and characteristics. Most of the existing solutions for network slicing are facing challenges in terms of resource and mobility management. Regarding resource management, it creates challenges in terms of provisioning network throughput, end-to-end delay, and fairness resources allocation for each slice, whereas, in the case of mobility management, due to the rapid change of user mobility the network slice operator would like to hold the mobility controlling over its clients across different access networks, rather than the network operator, to ensure better services and user experience. In this thesis, we propose two novel architectural solutions to solve the challenges identified above. The first proposed solution introduces a Network Slicing Resource Management (NSRM) mechanism that assigns the required resources for each slice, taking into consideration resource isolation between different slices. The second proposed v solution provides a Mobility Management architecture-based Network Slicing (MMNS) where each slice manages its users across heterogeneous radio access technologies such as WiFi, LTE and 5G networks. In MMNS architecture, each slice has different mobility demands (e.g,. latency, speed and interference) and these demands are governed by a network slice configuration and service characteristics. In addition, NSRM ensures isolating, customizing and fair sharing of distributed bandwidths between various network slices and users belonging to the same slice depending on different requirements of each one. Whereas, MMNS is a logical platform that unifies different Radio Access Technologies (RATs) and allows all slices to share them in order to satisfy different slice mobility demands. We considered two software simulations, namely OPNET Modeler and OMNET++, to validate the performance evaluation of the thesis contributions. The simulation results for both proposed architectures show that, in case of NSRM, the resource blocking is approximately 35% less compared to the legacy LTE network, which it allows to accommodate more users. The NSRM also successfully maintains the isolation for both the inter and intra network slices. Moreover, the results show that the NSRM is able to run different scheduling mechanisms where each network slice guarantee perform its own scheduling mechanism and simultaneously with other slices. Regarding the MMNS, the results show the advantages of the proposed architecture that are the reduction of the tunnelling overhead and the minimization of the handover latency. The MMNS results show the packets delivery cost is optimal by reducing the number of hops that the packets transit between a source node and destination. Additionally, seamless session continues of a user IP-flow between different access networks interfaces has been successfully achieved