Review on Construction Procedures of Driving Cycles

The goal of this paper is to give an overview of the literature of construction techniques of driving cycles. Our motivation for the overview is the future goal of constructing our own driving cycles for various types of vehicles and routes. This activity is part of a larger project focusing on determination of fuel and energy consumption by dynamic simulation of vehicles. Accordingly, the papers dealing with sample route determination, data collection and processing, driving cycle construction procedures, statistical evaluation of data are in our focus

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Comparison of vertical handover decision-based techniques in heterogeneous networks

Industry leaders are currently setting out standards for 5G Networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature because no single network type is capable of optimally meeting all the rapid changes in customer demands. Heterogeneous networks are typically characterized by some network architecture, base stations of varying transmission power, transmission solutions and the deployment of a mix of technologies (multiple radio access technologies). In heterogeneous networks, the processes involved when a mobile node successfully switches from one radio access technology to the other for the purpose of quality of service continuity is termed vertical handover or vertical handoff. Active calls that get dropped, or cases where there is discontinuity of service experienced by mobile users can be attributed to the phenomenon of delayed handover or an outright case of an unsuccessful handover procedure. This dissertation analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using the OMNeT++ discrete event simulator. The loose coupling type network architecture is adopted and results of the simulation are analysed and compared for the two major categories of handover basis; multiple and single criteria based handover methods. The key performance indices from the simulations showed better overall throughput, better call dropped rate and shorter handover time duration for the multiple criteria based decision method compared to the single criteria based technique. This work also touches on current trends, challenges in area of seamless handover and initiatives for future Networks (Next Generation Heterogeneous Networks)

SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS

A finales de los años noventa, y al comienzo del nuevo milenio, las redes inalámbricas han evolucionado bastante, pasando de ser sólo una tecnología prometedora para convertirse en un requisito para las actividades cotidianas en las sociedades desarrolladas. La infraestructura de transporte también ha evolucionado, ofreciendo comunicación a bordo para mejorar la seguridad vial y el acceso a contenidos de información y entretenimiento. Los requisitos de los usuarios finales se han hecho dependientes de la tecnología, lo que significa que sus necesidades de conectividad han aumentado debido a los diversos requisitos de las aplicaciones que se ejecutan en sus dispositivos móviles, tales como tabletas, teléfonos inteligentes, ordenadores portátiles o incluso ordenadores de abordo (On-Board Units (OBUs)) dentro de los vehículos. Para cumplir con dichos requisitos de conectividad, y teniendo en cuenta las diferentes redes inalámbricas disponibles, es necesario adoptar técnicas de Vertical Handover (VHO) para cambiar de red de forma transparente y sin necesidad de intervención del usuario. El objetivo de esta tesis es desarrollar algoritmos de decisión (Vertical Handover Decision Algorithms (VHDAs)) eficientes y escalables, optimizados para el contexto de las redes vehiculares. En ese sentido se ha propuesto, desarrollado y probado diferentes algoritmos de decisión basados en la infraestructura disponible en las actuales, y probablemente en las futuras, redes inalámbricas y redes vehiculares. Para ello se han combinado diferentes técnicas, métodos computacionales y modelos matemáticos, con el fin de garantizar una conectividad apropiada, y realizando el handover hacia las redes más adecuadas de manera a cumplir tanto con los requisitos de los usuarios como los requisitos de las aplicaciones. Con el fin de evaluar el contexto, se han utilizado diferentes herramientas para obtener información variada, como la disponibilidad de la red, el estado de la red, la geolocalizaciónMárquez Barja, JM. (2012). SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17869Palanci

Intelligent based Packet Scheduling Scheme using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Technology for 5G. Design and Investigation of Bandwidth Management Technique for Service-Aware Traffic Engineering using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) for 5G

Multi-Protocol Label Switching (MPLS) makes use of traffic engineering (TE) techniques and a variety of protocols to establish pre-determined highly efficient routes in Wide Area Network (WAN). Unlike IP networks in which routing decision has to be made through header analysis on a hop-by-hop basis, MPLS makes use of a short bit sequence that indicates the forwarding equivalence class (FEC) of a packet and utilises a predefined routing table to handle packets of a specific FEC type. Thus header analysis of packets is not required, resulting in lower latency. In addition, packets of similar characteristics can be routed in a consistent manner. For example, packets carrying real-time information can be routed to low latency paths across the networks. Thus the key success to MPLS is to efficiently control and distribute the bandwidth available between applications across the networks. A lot of research effort on bandwidth management in MPLS networks has already been devoted in the past. However, with the imminent roll out of 5G, MPLS is seen as a key technology for mobile backhaul. To cope with the 5G demands of rich, context aware and multimedia-based user applications, more efficient bandwidth management solutions need to be derived. This thesis focuses on the design of bandwidth management algorithms, more specifically QoS scheduling, in MPLS network for 5G mobile backhaul. The aim is to ensure the reliability and the speed of packet transfer across the network. As 5G is expected to greatly improve the user experience with innovative and high quality services, users’ perceived quality of service (QoS) needs to be taken into account when deriving such bandwidth management solutions. QoS expectation from users are often subjective and vague. Thus this thesis proposes the use of fuzzy logic based solution to provide service aware and user-centric bandwidth management in order to satisfy requirements imposed by the network and users. Unfortunately, the disadvantage of fuzzy logic is scalability since dependable fuzzy rules and membership functions increase when the complexity of being modelled increases. To resolve this issue, this thesis proposes the use of neuro-fuzzy to solicit interpretable IF-THEN rules.The algorithms are implemented and tested through NS2 and Matlab simulations. The performance of the algorithms are evaluated and compared with other conventional algorithms in terms of average throughput, delay, reliability, cost, packet loss ratio, and utilization rate. Simulation results show that the neuro-fuzzy based algorithm perform better than fuzzy and other conventional packet scheduling algorithms using IP and IP over MPLS technologies.Tertiary Education Trust Fund (TETFUND

Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al

An intelligent vertical handoff decision algorithm in next generation wireless networks

Philosophiae Doctor - PhDSeamless mobility is the missing ingredient needed to address the inefficient communication problems faced by the field workforces of service companies that are using field workforce automation solutions to streamline and optimise the operations of their field workforces in an increasingly competitive market place. The key enabling function for achieving seamless mobility and seamless service continuity is seamless handoffs across heterogeneous wireless access networks. A challenging issue in the multi-service next generation wireless network (NGWN) is to design intelligent and optimal vertical handoff decision algorithms, beyond traditional ones that are based on only signal strength, to determine when to perform a handoff and to provide optimal choice of access network technology among all available access networks for users equipped with multimode mobile terminals. The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria); used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model; used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff; and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to user

Adaptive intelligent traffic control systems for improving traffic quality and congestion in smart cities

A systematic review was undertaken to examine the solutions available for traffic congestion and associated problems in smart cities. Google Scholar and Google were used as search engines, leading to the final selection of 35 eligible papers for inclusion in this review, after a serious of screening based on definite criteria. Intelligent transport systems were found to be the most suitable solution to traffic congestion and associated problems in smart cities. Certain models and frameworks of smart cities include smart mobility and transport management systems. These can be approximated to intelligent transport systems. True intelligent transport systems are infrastructure-based or intelligent vehicle based or more preferably, a combination of both. The Internet of Things and cloud computing should be built into the system as they enable the operation of smart transport networks. Some methods of designing traffic control systems combining both Eulerian and Lagrangian approaches have been discussed for the possibility of using any of them to design a new automatic traffic monitoring and control system for smart cities. The practical implication of this research is that it can improve quality of life of people by minimizing traffic congestion. Limitations of this paper include this being a systematic review, availability of very few papers and not considering adaptive intelligent traffic control systems. Explanations for these limitations have been provide