IoT Traffic Management and Integration in the QoS Supported Network

This paper proposes: (i) a traffic flow management policy, which allocates and organises Machine Type Communication (MTC) traffic flows network resources sharing within Evolved Packet System (EPS), (ii) an access element as a Wireless Sensor Network (WSN) gateway for providing an overlaying access channel between the Machine Type Devices (MTDs) and EPS and (iii) it addresses the effect and interaction in the heterogeneity of applications, services and terminal devices and the related Quality of Service (QoS) issues among them. This work overcomes the problems of network resource starvation by preventing deterioration of network performance. The scheme is validated through simulation, which indicates the proposed traffic flow management policy outperforms the current traffic management policy. Specifically, simulation results show that the proposed model achieves an enhancement in QoS performance for the MTC traffic flows, including a decrease of 99.45% in Packet Loss Ratio (PLR), a decrease of 99.89% in packet End To End (E2E) delay, a decrease of 99.21% in Packet Delay Variation (PDV). Furthermore, it retains the perceived Quality of Experience (QoE) of the real time application users within high satisfaction levels, such as the VoLTE service possessing a Mean Opinion Score (MOS) of 4.349 and enhancing the QoS of a video conference service within the standardised values of a 3GPP body, with a decrease of 85.28% in PLR, a decrease of 85% in packet E2E delay and a decrease of 88.5% in PDV

SMART TRANSPORTATION SYSTEMS: IOT-CONNECTED WIRELESS SENSOR NETWORKS FOR TRAFFIC CONGESTION MANAGEMENT

Smart Transportation Systems (STS) are crucial to alleviating urban traffic congestion. This paper examines how gridlock managers might use IoT-related remote sensor networks to improve transportation productivity and flexibility. The study's initial inquiry examines traffic congestion's negative consequences on cities, including increased travel time, fuel consumption, and pollution. It emphasizes the need for creative solutions to reduce traffic and improve urban life. The solution's IoT-enabled wireless sensor networks simplify real-time data collection and analysis. A dense sensor network at important traffic sites can collect significant data on traffic flow, vehicle density, and road conditions. This data enables smart traffic management methods and better transportation systems. Sensor hubs, information transmission standards, and information analysis methodologies are examined in the exploratory article. It discusses network-sending challenges such as power productivity, flexibility, and information security and proposes solutions. The essay also considers synergies with autonomous cars, smart traffic signal systems, and IoT-connected wireless sensor networks in transportation infrastructure. These pairings boost gridlock executives' viability and STS's future. An IoT-associated remote sensor network was dispatched to a metropolitan region in the exploration piece to test the proposed configuration. The research examines the data, how traffic management tactics were applied, and how traffic flow, trip time, and environmental sustainability improved. This research shows that IoT-connected wireless sensor networks may transform smart transportation system traffic congestion management. Advanced analytics and real-time data may help cities reduce congestion, increase mobility, and develop sustainable cities

New cross-domain QoE guarantee method based on isomorphism flow

This paper investigates the issue of Quality of Experience(QoE)for multimedia services over heterogeneous networks. Anew concept of “Isomor-phism Flow”(iFlow) was introduced for analyzing multimedia traffics, which is inspired by the abstract algebrabased on experimental research. By using iF-low, the multimedia traffics with similar QoErequirements for differentusersare aggregated. AQoE evaluation method was also proposed for the aggregated traffics. Then a new cross-domain QoE guarantee method based on the iFlow QoEis proposed in this paper to adjust the network resource fromthe perspec-tive of user perception.The proposed scheme is validated through simulations. Simulationresults show that the proposed scheme achieves an enhancement in QoE performanceandoutperforms the existing schemes

Análisis de Tráfico de Red de dispositivos IoT

[ES] En la actualidad multitud de dispositivos se conectan entre sí para intercambiar información. La importancia de dicha interconexión y la gran variedad de servicios ofrecidos a través de la red de redes (Internet) ha alcanzado lo más profundo de los hogares de las personas. Hoy en día es común encontrar televisores con acceso a Internet o termostatos que se pueden controlar desde miles de kilómetros de distancia. A este fenómeno de conectar a Internet dispositivos de uso cotidiano que antes no disponían de dicho acceso a la red, se le conoce como Internet de las cosas. Al margen de este fenómeno y todas las ventajas que trae consigo, este tipo de dispositivos pueden presentar problemas de seguridad que los hace objetivo de ataques. Además, y dada la diversidad de fabricantes, la homogeneidad en cuanto a los métodos de conexión utilizados es inexistente. Este trabajo utiliza el tráfico generado por el comportamiento de estos dispositivos en las redes domésticas de los usuarios capturado mediante un entorno de pruebas desarrollado, y aplica diferentes técnicas de análisis como la inspección profunda de paquetes o el análisis basado en flujos con el fin de estudiar y profundizar en el uso de dichas técnicas, así como explorar formas avanzadas de enriquecimiento y visualización de los datos

Assurance, Provision, Management and Enhancement of QoS in 5G Communication Networks

Enhancement of QoS in PS network as 5G communication network is non trivial endeavour which faces a host of new challenges beyond 3G and 4G communication networks. The number of nodes, the homogeneity of the access technologies, the conflicting network management objectives, resource usage minimization, and the division between limited physical resources and elastic virtual resources is driving a complete change in the vision and methodologies for efficient management of the available network resources. QoS is the measure of the reliability and performance of the networks’ nodes and links, particularly as perceivedbytheendusersoftheservicesandapplicationthataretransportedviaPSnetwork. Furthermore, QoS is a composite metric as it based on a number of multiple factors, which indicate the E2E characteristics and performance of the network condition, applications and services. Hence, reductions or improvements in the QoS level can brought about through a number of combined factors. This thesis tries to introduce a vision of Quality of Service (QoS) enhancement and management based on the 5th generation network requirements and solutions by: Firstly: Proposing a traffic flow management policy, which allocates and organises Machine Type Communication (MTC) traffic flow’s network resources sharing within Evolved Packet System (EPS), with an access element as a Wireless Sensor Network (WSN) gateway for providing an overlaying access channel between the Machine Type Devices (MTDs) and EPS. This proposal addresses the effect and interaction in the heterogeneity of applications, services and terminal devices and the related QoS issues among them. The introduced work inthisproposalovercomestheproblemsofnetworkresourcestarvationbypreventingdeterioration of network performance. The scheme is validated through simulation, which indicates the proposed traffic flow management policy outperforms the current traffic management policy. Specifically, simulation results show that the proposed model achieves an enhancement in QoS performance for the MTC traffic flows, including a decrease of 99.45% in Packet Loss Rate (PLR), a decrease of 99.89% in packet End to End (E2E) delay, a decrease of 99.21% in Packet Delay Variation (PDV). Furthermore, it retains the perceived Quality of Experience (QoE) of the real time application users within high satisfaction levels, such as the Voice over Long Term Evolution (VoLTE) service possessing a Mean Opinion Score (MOS)of4.349andenhancingtheQoSofavideoconferenceservicewithinthestandardised values of a 3GPP body, with a decrease of 85.28% in PLR, a decrease of 85% in packet E2E delay and a decrease of 88.5% in PDV. Secondly: Proposing an approach for allocating existing 4G installed network radio access nodes to multiple Base Band Unit (BBU) pools, which is proposed to deploy 5G Cloud-Radio Access Network (C-RAN) and improve the offered Network QoS (NQoS). The proposed approach involves performing radio access nodes clustering based on the Particle Swarm Optimization (PSO) algorithm, model selection Bayesian Information Criterion (BIC), Measure of spread technique and Voronoi tessellation. The proposed scheme is used to consider a Dynamic C-RAN (DC-RAN) operation, that adaptively adjusts the main Radio Remote Head (RRH) coverage range according to the traffic load requirement as well as considering energy saving. The numerical results of the approach show that the optimized partition of the proposed network model is 41 BBU pools, with an average density of RRHs per pool area, which matches the primary average density of the radio access nodes per network area. Thirdly: Developing mathematical framework that investigates the Power Consumption (PC) profile for the interaction of Internet of Thing (IoT) Application QoS (AQoS) with NQoS in wireless Software Defined Network (SDN) as SDN for WIreless SEnsor network (SDN-WISE). This profile model offers flexibility for managing the structure of the Machine to Machine (M2M) system in IoT. It enables controlling the provided NQoS, precisely the achieved PHY layer transmission link throughput, combined with the AQoS, represented by IoT data stream payload size. The investigation is composed of two essential SDN traffic parts, they are control plane signalling and data plane traffic PCs and their relevance with QoS. The results show that 98% PC in data plane companion with a control plane PC of 2% in overall of the proposed system power, these figures were achieved with control plane signalling Transmission Time Interval (TTI) of 5 sec and a maximum data plane payload size of 92 Bytes as a worst case scenario.Ministry of Higher Education and Scientific Research (MOHESR), Cultural Attache and University of Wasit in Ira

Development of a Random Time-Frequency Access Protocol for M2M Communication

This thesis focuses on the design and development of the random time-frequency access protocol in Machine-to-Machine (M2M) communication systems and covers different aspects of the data collision problem in these systems. The randomisation algorithm, used to access channels in the frequency domain, represents the key factor that affects data collisions. This thesis presents a new randomisation algorithm for the channel selection process for M2M technologies. The new algorithm is based on a uniform randomisation distribution and is called the Uniform Randomisation Channel Selection Technique (URCST). This new channel selection algorithm improves system performance and provides a low probability of collision with minimum complexity, power consumption, and hardware resources. Also, URCST is a general randomisation technique which can be utilised by different M2M technologies. The analysis presented in this research confirms that using URCST improves system performance for different M2M technologies, such as Weightless-N and Sigfox, with a massive number of devices. The thesis also provides a rigorous and flexible mathematical model for the random time-frequency access protocol which can precisely describe the performance of different M2M technologies. This model covers various scenarios with multiple groups of devices that employ different transmission characteristics like the number of connected devices, the number of message copies, the number of channels, the payload size, and transmission time. In addition, new and robust simulation testbeds have been built and developed in this research to evaluate the performance of different M2M technologies that utilise the random time-frequency access protocol. These testbeds cover the channel histogram, the probability of collisions, and the mathematical model. The testbeds were designed to support the multiple message copies approach with various groups of devices that are connected to the same base station and employ different transmission characteristics. Utilising the newly developed channel selection algorithm, mathematical model, and testbeds, the research offers a detailed and thorough analysis of the performance of Weightless-N and Sigfox in terms of the message lost ratio (MLR) and power consumption. The analysis shows some useful insights into the performance of M2M systems. For instance, while using multiple message copies improves the system performance, it might degrade the reliability of the system as the number of devices increases beyond a specific limit. Therefore, increasing the number of message copies can be disadvantageous to M2M communication performance