A Fuzzy Decision Tree Based Mobility Prediction Mechanism in Mobile Internet

Considering environment factor and user movement randomness, a fuzzy decision tree based mobility prediction mechanism in mobile Internet is proposed. Based on the instance set, an initial fuzzy decision tree is built up with fuzzy attribute and classification entropy. The tree produces fuzzy decision rules for instant mobility predictions and evolves with time. Simulation results have shown that the proposed mechanism is both feasible and effective with relatively high accuracy and low overhead of mobility predictio

Data-Driven Network Management for Next-Generation Wireless Networks

With the commercialization and maturity of the fifth-generation (5G) wireless networks, the next-generation wireless network (NGWN) is envisioned to provide seamless connectivity for mobile user terminals (MUTs) and to support a wide range of new applications with stringent quality of service (QoS) requirements. In the NGWN, the network architecture will be highly heterogeneous due to the integration of terrestrial networks, satellite networks, and aerial networks formed by unmanned aerial vehicles (UAVs), and the network environment becomes highly dynamic because of the mobility of MUTs and the spatiotemporal variation of service demands. In order to provide high-quality services in such dynamic and heterogeneous networks, flexible, fine-grained, and adaptive network management will be essential. Recent advancements in deep learning (DL) and digital twins (DTs) have made it possible to enable data-driven solutions to support network management in the NGWN. DL methods can solve network management problems by leveraging data instead of explicit mathematical models, and DTs can facilitate DL methods by providing extensive data based on the full digital representations created for individual MUTs. Data-driven solutions that integrates DL and DT can address complicated network management problems and explore implicit network characteristics to adapt to dynamic network environments in the NGWN. However, the design of data-driven network management solutions in the NGWN meets several technical challenges: 1) how the NGWN can be configured to support multiple services with different spatiotemporal service demands while simultaneously satisfying their different QoS requirements; 2) how the multi-dimensional network resources are proactively reserved to support MUTs with different mobility patterns in a resource-efficient manner; and 3) how the heterogeneous NGWN components, including base stations (BSs), satellites, and UAVs, jointly coordinate their network resources to support dynamic service demands, etc. In this thesis, we develop efficient data-driven network management strategies in two stages, i.e., long-term network planning and real-time network operation, to address the above challenges in the NGWN. Firstly, we investigate planning-stage network configuration to satisfy different service requirements for communication services. We consider a two-tier network with one macro BS and multiple small BSs, which supports communication services with different spatiotemporal data traffic distributions. The objective is to maximize the energy efficiency of BSs by jointly configuring downlink transmission power and communication coverage for each BS. To achieve this objective, we first design a network planning scheme with flexible binary slice zooming, dual time-scale planning, and grid-based network planning. The scheme allows flexibility to differentiate the communication coverage and downlink transmission power of the same BS for different services while improving the temporal and spatial granularity of network planning. We formulate a combinatorial optimization problem in which communication coverage management and power control are mutually dependent. To solve the problem, we propose a data-driven method with two steps: 1) we propose an unsupervised-learning-assisted approach to determine the communication coverage of BSs; and 2) we derive a closed-form solution for power control. Secondly, we investigate planning-stage resource reservation for a compute-intensive service to support MUTs with different mobility patterns. The MUTs can offload their computing tasks to the computing servers deployed at the core networks, gateways, and BSs. Each computing server requires both computing and storage resources to execute computing tasks. The objective is to optimize long-term resource reservation by jointly minimizing the usage of computing, storage, and communication resources and the cost from re-configuring resource reservation. To this end, we develop a data-driven network planning scheme with two elements, i.e., multi-resource reservation and resource reservation re-configuration. First, DTs are designed for collecting MUT status data, based on which MUTs are grouped according to their mobility patterns. Then, an optimization algorithm is proposed to customize resource reservation for different groups to satisfy their different resource demands. Last, a meta-learning-based approach is proposed to re-configure resource reservation for balancing the network resource usage and the re-configuration cost. Thirdly, we investigate operation-stage computing resource allocation in a space-air-ground integrated network (SAGIN). A UAV is deployed to fly around MUTs and collect their computing tasks, while scheduling the collected computing tasks to be processed at the UAV locally or offloaded to the nearby BSs or the remote satellite. The energy budget of the UAV, intermittent connectivity between the UAV and BSs, and dynamic computing task arrival pose challenges in computing task scheduling. The objective is to design a real-time computing task scheduling policy for minimizing the delay of computing task offloading and processing in the SAGIN. To achieve the objective, we first formulate the on-line computing scheduling in the dynamic network environment as a constrained Markov decision process. Then, we develop a risk-sensitive reinforcement learning approach in which a risk value is used to represent energy consumption that exceeds the budget. By balancing the risk value and the reward from delay minimization, the UAV can explore the task scheduling policy to minimize task offloading and processing delay while satisfying the UAV energy constraint. Extensive simulation have been conducted to demonstrate that the proposed data-driven network management approach for the NGWN can achieve flexible BS configuration for multiple communication services, fine-grained multi-dimensional resource reservation for a compute-intensive service, and adaptive computing resource allocation in the dynamic SAGIN. The schemes developed in the thesis are valuable to the data-driven network planning and operation in the NGWN

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

Flexible cross layer design for improved quality of service in MANETs

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityMobile Ad hoc Networks (MANETs) are becoming increasingly important because of their unique characteristics of connectivity. Several delay sensitive applications are starting to appear in these kinds of networks. Therefore, an issue in concern is to guarantee Quality of Service (QoS) in such constantly changing communication environment. The classical QoS aware solutions that have been used till now in the wired and infrastructure wireless networks are unable to achieve the necessary performance in the MANETs. The specialized protocols designed for multihop ad hoc networks offer basic connectivity with limited delay awareness and the mobility factor in the MANETs makes them even more unsuitable for use. Several protocols and solutions have been emerging in almost every layer in the protocol stack. The majority of the research efforts agree on the fact that in such dynamic environment in order to optimize the performance of the protocols, there is the need for additional information about the status of the network to be available. Hence, many cross layer design approaches appeared in the scene. Cross layer design has major advantages and the necessity to utilize such a design is definite. However, cross layer design conceals risks like architecture instability and design inflexibility. The aggressive use of cross layer design results in excessive increase of the cost of deployment and complicates both maintenance and upgrade of the network. The use of autonomous protocols like bio-inspired mechanisms and algorithms that are resilient on cross layer information unavailability, are able to reduce the dependence on cross layer design. In addition, properties like the prediction of the dynamic conditions and the adaptation to them are quite important characteristics. The design of a routing decision algorithm based on Bayesian Inference for the prediction of the path quality is proposed here. The accurate prediction capabilities and the efficient use of the plethora of cross layer information are presented. Furthermore, an adaptive mechanism based on the Genetic Algorithm (GA) is used to control the flow of the data in the transport layer. The aforementioned flow control mechanism inherits GA’s optimization capabilities without the need of knowing any details about the network conditions, thus, reducing the cross layer information dependence. Finally, is illustrated how Bayesian Inference can be used to suggest configuration parameter values to the other protocols in different layers in order to improve their performance.National Foundation of Scholarships of Greece(I.K.Y.

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Video QoS/QoE over IEEE802.11n/ac: A Contemporary Survey

The demand for video applications over wireless networks has tremendously increased, and IEEE 802.11 standards have provided higher support for video transmission. However, providing Quality of Service (QoS) and Quality of Experience (QoE) for video over WLAN is still a challenge due to the error sensitivity of compressed video and dynamic channels. This thesis presents a contemporary survey study on video QoS/QoE over WLAN issues and solutions. The objective of the study is to provide an overview of the issues by conducting a background study on the video codecs and their features and characteristics, followed by studying QoS and QoE support in IEEE 802.11 standards. Since IEEE 802.11n is the current standard that is mostly deployed worldwide and IEEE 802.11ac is the upcoming standard, this survey study aims to investigate the most recent video QoS/QoE solutions based on these two standards. The solutions are divided into two broad categories, academic solutions, and vendor solutions. Academic solutions are mostly based on three main layers, namely Application, Media Access Control (MAC) and Physical (PHY) which are further divided into two major categories, single-layer solutions, and cross-layer solutions. Single-layer solutions are those which focus on a single layer to enhance the video transmission performance over WLAN. Cross-layer solutions involve two or more layers to provide a single QoS solution for video over WLAN. This thesis has also presented and technically analyzed QoS solutions by three popular vendors. This thesis concludes that single-layer solutions are not directly related to video QoS/QoE, and cross-layer solutions are performing better than single-layer solutions, but they are much more complicated and not easy to be implemented. Most vendors rely on their network infrastructure to provide QoS for multimedia applications. They have their techniques and mechanisms, but the concept of providing QoS/QoE for video is almost the same because they are using the same standards and rely on Wi-Fi Multimedia (WMM) to provide QoS

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Scalable Multiple Description Coding and Distributed Video Streaming over 3G Mobile Networks

In this thesis, a novel Scalable Multiple Description Coding (SMDC) framework is proposed. To address the bandwidth fluctuation, packet loss and heterogeneity problems in the wireless networks and further enhance the error resilience tools in Moving Pictures Experts Group 4 (MPEG-4), the joint design of layered coding (LC) and multiple description coding (MDC) is explored. It leverages a proposed distributed multimedia delivery mobile network (D-MDMN) to provide path diversity to combat streaming video outage due to handoff in Universal Mobile Telecommunications System (UMTS). The corresponding intra-RAN (Radio Access Network) handoff and inter-RAN handoff procedures in D-MDMN are studied in details, which employ the principle of video stream re-establishing to replace the principle of data forwarding in UMTS. Furthermore, a new IP (Internet Protocol) Differentiated Services (DiffServ) video marking algorithm is proposed to support the unequal error protection (UEP) of LC components of SMDC. Performance evaluation is carried through simulation using OPNET Modeler 9. 0. Simulation results show that the proposed handoff procedures in D-MDMN have better performance in terms of handoff latency, end-to-end delay and handoff scalability than that in UMTS. Performance evaluation of our proposed IP DiffServ video marking algorithm is also undertaken, which shows that it is more suitable for video streaming in IP mobile networks compared with the previously proposed DiffServ video marking algorithm (DVMA)