Design and development of handover simulator model in 5G cellular network

In the modern era of technology, the high speed internet is the most important part of human life. The current available network is reckoned to be slow in speed and not be up to snuff for data transmission regarding business applications. The objective of handover mechanism is to reassign the current session handle by internet gadget. The globe needs the next generation high mobility and throughput performance based internet model. This research paper explains the proposed method of design and development for handover based 5G cellular network. In comparison to the traditional method, we propose to control the handovers between base-stations using a concentric method. The channel simulator is applied over the range of the frequencies from 500 MHz to 150 GHz and radio frequency for the 700 MHz bandwidth. The performance of the simulation system is calculated on the basis of handover preparation and completion time regarding base station as well as number of users. From this experiment we achieve the 7.08 ms handover preparation time and 9.98 ms handover completion time. The author recommended the minimum handover completion time, perform the high speed for 5G cellular networks

A Highly Scalable IoT Architecture through Network Function Virtualization

As the number of devices for Internet of Things (IoT) is rapidly growing, existing communication infrastructures are forced to continually evolve. The next generation network infrastructure is expected to be virtualized and able to integrate different kinds of information technology resources. Network Functions Virtualization (NFV) is one of the leading concepts facilitating the operation of network services in a scalable manner. In this paper, we present an architecture involving NFV to meet the requirements of highly scalable IoT scenarios. We highlight the benefits and challenges of our approach for IoT stakeholders. Finally, the paper illustrates our vision of how the proposed architecture can be applied in the context of a state-of-the-art high-tech operating room, which we are going to realize in future work

New concepts for traffic, resource and mobility management in software-defined mobile networks

The evolution of mobile telecommunication networks is accompanied by new demands for the performance, portability, elasticity, and energy efficiency of network functions. Network Function Virtualization (NFV), Software Defined Networking (SDN), and cloud service technologies are claimed to be able to provide most of the capabilities. However, great leap forward will only be achieved if resource, traffic, and mobility management methods of mobile network services can efficiently utilize these technologies. This paper conceptualizes the future requirements of mobile networks and proposes new concepts and solutions in the form of Software-Defined Mobile Networks (SDMN) leveraging SDN, NFV and cloud technologies. We evaluate the proposed solutions through testbed implementations and simulations. The results reveal that our proposed SDMN enhancements supports heterogeneity in wireless networks with performance improvements through programmable interfaces and centralized control

Issues and Challenges Facing Low Latency in Tactile Internet

Tactile Internet is considered as the next step towards a revolutionary impact on the society, this is due to the introduction of different types of applications mainly the haptic ones that require strict Quality of Service guarantee especially in terms of latency. This would be a major challenge towards the design of new communication technologies and protocols in order to provide ultra-low latency. This article discusses the diverse technologies, communication protocols, and the necessary infrastructure to provide low latency based principally on the fifth generation (5G) of mobile network that is considered as the key enablers of the Tactile Internet. Furthermore, current research direction along with future challenges and open issues are discussed extensively

Evaluation of machine learning techniques for intrusion detection in software defined networking

Abstract. The widespread growth of the Internet paved the way for the need of a new network architecture which was filled by Software Defined Networking (SDN). SDN separated the control and data planes to overcome the challenges that came along with the rapid growth and complexity of the network architecture. However, centralizing the new architecture also introduced new security challenges and created the demand for stronger security measures. The focus is on the Intrusion Detection System (IDS) for a Distributed Denial of Service (DDoS) attack which is a serious threat to the network system. There are several ways of detecting an attack and with the rapid growth of machine learning (ML) and artificial intelligence, the study evaluates several ML algorithms for detecting DDoS attacks on the system. Several factors have an effect on the performance of ML based IDS in SDN. Feature selection, training dataset, and implementation of the classifying models are some of the important factors. The balance between usage of resources and the performance of the implemented model is important. The model implemented in the thesis uses a dataset created from the traffic flow within the system and models being used are Support Vector Machine (SVM), Naive-Bayes, Decision Tree and Logistic Regression. The accuracy of the models has been over 95% apart from Logistic Regression which has 90% accuracy. The ML based algorithm has been more accurate than the non-ML based algorithm. It learns from different features of the traffic flow to differentiate between normal traffic and attack traffic. Most of the previously implemented ML based IDS are based on public datasets. Using a dataset created from the flow of the experimental environment allows training of the model from a real-time dataset. However, the experiment only detects the traffic and does not take any action. However, these promising results can be used for further development of the model

Quality of Experience monitoring and management strategies for future smart networks

One of the major driving forces of the service and network's provider market is the user's perceived service quality and expectations, which are referred to as user's Quality of Experience (QoE). It is evident that QoE is particularly critical for network providers, who are challenged with the multimedia engineering problems (e.g. processing, compression) typical of traditional networks. They need to have the right QoE monitoring and management mechanisms to have a significant impact on their budget (e.g. by reducing the users‘ churn). Moreover, due to the rapid growth of mobile networks and multimedia services, it is crucial for Internet Service Providers (ISPs) to accurately monitor and manage the QoE for the delivered services and at the same time keep the computational resources and the power consumption at low levels. The objective of this thesis is to investigate the issue of QoE monitoring and management for future networks. This research, developed during the PhD programme, aims to describe the State-of-the-Art and the concept of Virtual Probes (vProbes). Then, I proposed a QoE monitoring and management solution, two Agent-based solutions for QoE monitoring in LTE-Advanced networks, a QoE monitoring solution for multimedia services in 5G networks and an SDN-based approach for QoE management of multimedia services

OpenEPC Integration within 5GTN as an NFV proof of concept

Abstract. Gone are the days, when a hardware is changed on every malfunctioning and the whole operation either stays down or load on the replacing hardware becomes too much which ultimately compromises the QoS. The IT industry is mature enough to tackle problems regarding scalability, space utilization, energy consumption, cost, agility and low availability. The expected throughput and network latency with 5G in the cellular Telecommunication Networks seems to be unachievable with the existing architecture and resources. Network Function Virtualization promises to merge IT and Telecommunications in such an efficient way that the expected results could be achieved no longer but sooner. The thesis work examines the compatibility and flexibility of a 3GPP virtual core network in a virtualization platform. The testbed is established on an LTE (Long Term Evolution) based network being already deployed and OpenEPC is added as virtual core network on it. The integration of OpenEPC in 5GTN (5TH Generation Test Network) is discussed in details in the thesis which will give an account of the possibility of implementing such a simulated vEPC (Virtual Evolved Packet Core) in a real network platform. The deployed setup is tested to check its feasibility and flexibility for a platform which could be used for NFV deployment in future. The monitoring of OpenEPC’s individual components while utilizing the major resources within them, forms the primary performance test. The CPU Load and Memory Utilization is tested on different CPU stress levels having a constant data traffic from actual UEs. At the completion of the thesis work, a consensus is built up based on the test results that the test setup can hold number of subscribers to a certain amount without any performance degradation. Moreover, the virtual core network throughput and network latency is also compared to the commercial LTE networks and theoretical maximum values on similar resources to check performance consistency OpenEPC must offer