Joint multi-objective MEH selection and traffic path computation in 5G-MEC systems

Multi-access Edge Computing (MEC) is an emerging technology that allows to reduce the service latency and traffic congestion and to enable cloud offloading and context awareness. MEC consists in deploying computing devices, called MEC Hosts (MEHs), close to the user. Given the mobility of the user, several problems rise. The first problem is to select a MEH to run the service requested by the user. Another problem is to select the path to steer the traffic from the user to the selected MEH. The paper jointly addresses these two problems. First, the paper proposes a procedure to create a graph that is able to capture both network-layer and application-layer performance. Then, the proposed graph is used to apply the Multi-objective Dijkstra Algorithm (MDA), a technique used for multi-objective optimization problems, in order to find solutions to the addressed problems by simultaneously considering different performance metrics and constraints. To evaluate the performance of MDA, the paper implements a testbed based on AdvantEDGE and Kubernetes to migrate a VideoLAN application between two MEHs. A controller has been realized to integrate MDA with the 5G-MEC system in the testbed. The results show that MDA is able to perform the migration with a limited impact on the network performance and user experience. The lack of migration would instead lead to a severe reduction of the user experience.publishedVersio

Efficient Spectrum Management as an Enabler Towards 5G Cellular Systems

Advanced spectrum sharing and resource management techniques are needed in future wireless cellular networks to ensure high data rates to the end users. New system architec- tures will be required, taking into account aspects such as like spectrum resources availabil- ity, deployment and operational costs, as well as power consumption. Thus, it becomes key for the development of the fifth generation of cellular networks (5G) to pursue an efficient exploitation of the wireless medium, in the sense of both using advanced physical (PHY) layer techniques, and also seeking coordination among operators. In this thesis, we analyze the problem of spectrum management within the next generation of cellular networks and we propose new algorithms for spectrum sharing and for interference coordination. In the first part of the thesis, we focus on the spectrum sharing between operators. Firstly, we develop a Long Term Evolution (LTE) standard compliant simulation environ- ment extending the open-source network simulator ns3 to support multi-input multi-output (MIMO) systems and advanced beamforming systems. Then, we present a mathematical analysis for the network performance of non-orthogonal spectrum sharing, connecting it directly with the statistics of the radio channel and we develop some spectrum sharing al- gorithms considering different aspects of the operators coexistence. The analysis is further extended to the performance evaluation of more complex digital beamforming techniques developed in a multi-input-single-output (MISO) system allowing to reach a Pareto equi- librium between the operators. Finally, we consider also an orthogonal spectrum sharing scenario investigating the impact of asymmetries and dynamics of the user demands on the implementation of spectrum sharing techniques. In the second part of the thesis, we extend the concept of spectrum management to two different scenarios. In the first scenario, we consider coordination between multiple cells, e.g. coordinated multipoint (CoMP). In particular, thanks to the exploitation of digital beamforming techniques, we present a novel distributed clustering algorithm that adapts the cluster configuration according to the users distribution and the average cluster size. In the second scenario, we extend the concept of spectrum sharing to the coexistence between different communications system in order to study the feasibility of the deployment of the cellular systems within the mmWave spectrum. In particular, we analyze the impact of the novel cellular networks on the fixed satellite system (FSS). In the last part of the thesis, we focus on the mobility management of the users in a het- erogeneous network. Firstly, we focus on the average performance experienced by a mobile user while crossing a pico/femtocell, as a function of the handover parameters to provide an approximate expression of the average Shannon capacity experienced by a mobile user when crossing the femtocell. Then, we propose a Markov-based framework to model the user state during the handover process and, based on such a model, we derive an optimal context-dependent handover criterion

Heterogeneous Networking for Beyond 3G system in a High-Speed Train Environment. Investigation of handover procedures in a high-speed train environment and adoption of a pattern classification neural-networks approach for handover management

Based on the targets outlined by the EU Horizon 2020 (H2020) framework, it is expected that heterogeneous networking will play a crucial role in delivering seamless end-to-end ubiquitous Internet access for users. In due course, the current GSM-Railway (GSM-R) will be deemed unsustainable, as the demand for packet-oriented services continues to increase. Therefore, the opportunity to identify a plausible replacement system conducted in this research study is timely and appropriate. In this research study, a hybrid satellite and terrestrial network for enabling ubiquitous Internet access in a high-speed train environment is investigated. The study focuses on the mobility management aspect of the system, primarily related to the handover management. A proposed handover strategy, employing the RACE II MONET and ITU-T Q.65 design methodology, will be addressed. This includes identifying the functional model (FM) which is then mapped to the functional architecture (FUA), based on the Q.1711 IMT-2000 FM. In addition, the signalling protocols, information flows and message format based on the adopted design methodology will also be specified. The approach is then simulated in OPNET and the findings are then presented and discussed. The opportunity of exploring the prospect of employing neural networks (NN) for handover is also undertaken. This study focuses specifically on the use of pattern classification neural networks to aid in the handover process, which is then simulated in MATLAB. The simulation outcomes demonstrated the effectiveness and appropriateness of the NN algorithm and the competence of the algorithm in facilitating the handover process

IMPLEMENTATION AND OPTIMIZATION OF RWP MOBILITY MODEL IN WSNS UNDER TOSSIM SIMULATOR

Mobility has always represented a complicated phenomenon in the network routing process. This complexity is mainly facilitated in the way that ensures reliable connections for efficient orientation of data. Many years ago, different studies were initiated basing on routing protocols dedicated to static environments in order to adapt them to the mobile environment. In the present work, we have a different vision of mobility that has many advantages due to its 'mobile' principle. Indeed, instead of searching to prevent mobility and testing for example to immobilize momentarily a mobile environment to provide routing task, we will exploit this mobility to improve routing. Based on that, we carried out a set of works to achieve this objective. For our first contribution, we found that the best way to make use of this mobility is to follow a mobility model. Many models have been proposed in the literature and employed as a data source in most studies. After a careful study, we focused on the Random Waypoint mobility model (RWP) in order to ensure routing in wireless networks. Our contribution involves a Random Waypoint model (in its basic version) that was achieved on the TOSSIM simulator, and it was considered as a platform for our second (and main) contribution, in which we suggested an approach based RWP where network nodes can collaborate and work together basing on our recommended algorithm. Such an approach offers many advantages to ensure routing in a dynamic environment. Finally, our contributions comprise innovative ideas for suggesting other solutions that will improve them

Middleware-Controlled Resource consumption for Location Traffic in Cellular Networks

Location is valuable information for services implemented in wireless networks. Location systems often use the infrastructure of cellular networks that have already been deployed. Accordingly, location systems spend resources of the network they use. This paper proposes a middleware to reduce the consumption of network resources and optimize the location traffic that is being carried. This middleware, called MILCO (Middleware for Location Cost Optimization), selects the optimum location technique depending on the request, i.e. the location technique that satisfies the quality of service (QoS) required and minimizes the resource operating expense. In addition, MILCO takes advantage of ongoing and carried location processes to reduce the overall expenditure of resources. Our results show that MILCO can reduce location-process failures and improve latency figures for location provisioning and resource use in cellular networks such as UMTS

IP Mobility Support in Multi-hop Vehicular Communications Networks

The combination of infrastructure-to-vehicle and vehicle-to-vehicle communications, namely the multi-hop Vehicular Communications Network (VCN) , appears as a promising solution for the ubiquitous access to IP services in vehicular environments. In this thesis, we address the challenges of multi-hop VCN, and investigate the seamless provision of IP services over such network. Three different schemes are proposed and analyzed. First, we study the limitations of current standards for the provision of IP services, such as 802.11p/WAVE, and propose a framework that enables multi-hop communications and a robust IP mobility mechanism over WAVE. An accurate analytical model is developed to evaluate the throughput performance, and to determine the feasibility of the deployment of IP-based services in 802.11p/WAVE networks. Next, the IP mobility support is extended to asymmetric multi-hop VCN. The proposed IP mobility and routing mechanisms react to the asymmetric links, and also employ geographic location and road traffic information to enable predictive handovers. Moreover, since multi-hop communications suffer from security threats, it ensures that all mobility signalling is authenticated among the participant vehicles. Last, we extend our study to a heterogeneous multi-hop VCN, and propose a hybrid scheme that allows for the on-going IP sessions to be transferred along the heterogeneous communications system. The proposed global IP mobility scheme focuses on urban vehicular scenarios, and enables seamless communications for in-vehicle networks, commuters, and pedestrians. The overall performance of IP applications over multi-hop VCN are improved substantially by the proposed schemes. This is demonstrated by means of analytical evaluations, as well as extensive simulations that are carried out in realistic highway and urban vehicular scenarios. More importantly, we believe that our dissertation provides useful analytical tools, for evaluating the throughput and delay performance of IP applications in multi-hop vehicular environments. In addition, we provide a set of practical and efficient solutions for the seamless support of IP tra c along the heterogeneous and multi-hop vehicular network, which will help on achieving ubiquitous drive-thru Internet, and infotainment traffic access in both urban and highway scenarios

Quality-aware Tasking in Mobile Opportunistic Networks - Distributed Information Retrieval and Processing utilizing Opportunistic Heterogeneous Resources.

Advances in wireless technology have facilitated direct communication among mobile devices in recent years, enabling opportunistic networks. Opportunistic networking among mobile devices is often utilized to offload and save cellular network traffic and to maintain communication in case of impaired communication infrastructure, such as in emergency situations. With a plethora of built-in capabilities, such as built-in sensors and the ability to perform even intensive operations, mobile devices in such networks can be used to provide distributed applications for other devices upon opportunistic contact. However, ensuring quality requirements for such type of distributed applications is still challenging due to uncontrolled mobility and resource constraints of devices. Addressing this problem, in this thesis, we propose a tasking methodology, which allows for assigning tasks to capable mobile devices, considering quality requirements. To this end, we tackle two fundamental types of tasks required in a distributed application, i.e., information retrieval and distributed processing. Our first contribution is a decentralized tasking concept to obtain crowd collected data through built-in sensors of participating mobile devices. Based on the Named Data Networking paradigm, we propose a naming scheme to specify the quality requirements for crowd sensing tasks. With the proposed naming scheme, we design an adaptive self-organizing approach, in which the sensing tasks will be forwarded to the right devices, satisfying specified quality requirements for requested information. In our second contribution, we develop a tasking model for distributed processing in opportunistic networks. We design a task-oriented message template, which enhances the definition of a complex processing task, which requires multiple processing stages to accomplish a predefined goal. Our tasking concept enables distributed coordination and an autonomous decision of participating device to counter uncertainty caused by the mobility of devices in the network. Based on this proposed model, we develop computation handover strategies among mobile devices for achieving quality requirements of the distributed processing. Finally, as the third contribution and to enhance information retrieval, we integrate our proposed tasking concept for distributed processing into information retrieval. Thereby, the crowd-collected data can be processed by the devices during the forwarding process in the network. As a result, relevant information can be extracted from the crowd-collected data directly within the network without being offloaded to any remote computation entity. We show that the obtained information can be disseminated to the right information consumers, without over-utilizing the resource of participating devices in the network. Overall, we demonstrate that our contributions comprise a tasking methodology for leveraging resources of participating devices to ensure quality requirement of applications built upon an opportunistic network

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms