scholarly journals Towards a software-based mobility management for 5G: An experimental approach for flattened network architectures

2020 ◽  
Vol 17 (1) ◽  
pp. 51-70
Author(s):  
Jesús Calle-Cancho ◽  
José-Manuel Mendoza-Rubio ◽  
José-Luis González-Sánchez ◽  
David Cortés-Polo ◽  
Javier Carmona-Murillo
Keyword(s):  
Mobile Networks ◽  
Mobility Management ◽  
Network Performance ◽  
Mobile Network ◽  
Network Control ◽  
Network Services ◽  
Smart Devices ◽  
Network Architectures ◽  
Data Traffic ◽  
Management Capability

The number of mobile subscribers, as well as the data traffic generated by them, is increasing exponentially with the growth of wireless smart devices and the number of network services that they can support. This significant growth is pushing mobile network operators towards new solutions to improve their network performance and efficiency. Thus, the appearance of Software Defined Networking (SDN) can overcome the limitations of current deployments through decoupling the network control plane from the data plane, allowing higher flexibility and programmability to the network. In this context, the process of handling user mobility becomes an essential part of future mobile networks. Taking advantage of the benefits that SDN brings, in this article we present a novel mobility management solution. This proposal avoids the use of IP-IP tunnels and it adds the dynamic flow management capability provided by SDN. In order to analyse performance, an analytical model is developed to compare it with NB-DMM (Network-based DMM), one of the main DMM (Distributed Mobility Management) solutions. Additionally, performance is also evaluated with an experimental testbed. The results allow handover latency in real scenarios and numerical investigations to be measured, and also show that SR-DMM achieves better efficiency in terms of signaling and routing cost than NB-DMM solution.

scholarly journals Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks

2018 ◽  
Vol 6 (1) ◽  
pp. 26-40
Author(s):  
Battulga Davaasambuu
Keyword(s):  
Mobile Networks ◽  
Mobility Management ◽  
Single Point ◽  
Mobile Network ◽  
Base Stations ◽  
Data Traffic ◽  
Distributed Mobility Management ◽  
Mobile Cellular ◽  
Network Technologies

The rapidly-growing number of mobile subscribers has led to the creation of a large number of signalling messages. This makes it difficult to efficiently handle the mobility of subscribers in mobile cellular networks. The long-term evolution (LTE) architecture provides software-defined networking (SDN) to meet the requirements of 5G networks and to forward massive mobile data traffic. The SDN solution proposes separation of the control and data planes of a network. Centralized mobility management (CMM) is widely used in current mobile network technologies, such as 4G networks. One of the problems related to CMM is a single point of failure. To solve the problems of CMM and in order to provide for efficient mobility management, IETF has developed a solution called distributed mobility management (DMM), in which mobility is handled via the nearest mobility anchor. In this paper, we propose a DMM solution with handover operations for SDN-enabled mobile networks. The advantage of the proposed solution is that intra and inter handover procedures are defined with the data buffering and forwarding processes between base stations and mobility anchors. We adopt a simulation model to evaluate and compare the proposed solution with the existing solution in terms of handover latency, packet loss and handover failures.

scholarly journals Data Traffic Based on Slicing in a 5G Smart Uplink System

Telecom IT ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 44-54
Author(s):  
A. Grebenshchikova ◽  
Elagin V.
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Relay Node ◽  
Mobile Network ◽  
Video Stream ◽  
Base Station ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Fifth Generation

The paper considers the data traffic based on slicing in a 5g mobile network uplink system. Slicing is a promising technology for the fifth generation of networks that provides optimal quality of QOS services for each specific user or group of users. Data traffic that is processed by cellular networks increases every year. Therefore, we should consider all set of traffic from VoIP to M2M devices. For example, smart devices in the healthcare system transmit big data that is sensitive to latency, but also a video stream that requires minimal latency in certain cases. The paper focuses on the successful processing of traffic through a relay node, donor microstates, and a base station. All traffic is divided into three levels of QoS segmentation: sensitive, less sensitive, and low-sensitivity, using the AnyLogic simulation program. For fifth-generation 5G networks, achieving minimum latency and maximum data transfer speed within QoS is an important implementation condition. Therefore, in this paper, using simulation modeling, the main and possible results of each segment in the new generation of mobile networks are obtained. The use of a relay node in conjunction with micro-stations can ensure optimal station load and successful data processing. Also, the solutions outlined in this paper will allow you to identify a number of areas for future research to assess possible ways to design new mobile networks, or improve existing ones.

scholarly journals Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks

2018 ◽  
Vol 6 (1) ◽  
pp. 26-40
Author(s):  
Battulga Davaasambuu
Keyword(s):  
Mobile Networks ◽  
Mobility Management ◽  
Single Point ◽  
Mobile Network ◽  
Base Stations ◽  
Data Traffic ◽  
Distributed Mobility Management ◽  
Mobile Cellular ◽  
Network Technologies

The rapidly-growing number of mobile subscribers has led to the creation of a large number of signalling messages. This makes it difficult to efficiently handle the mobility of subscribers in mobile cellular networks. The long-term evolution (LTE) architecture provides software-defined networking (SDN) to meet the requirements of 5G networks and to forward massive mobile data traffic. The SDN solution proposes separation of the control and data planes of a network. Centralized mobility management (CMM) is widely used in current mobile network technologies, such as 4G networks. One of the problems related to CMM is a single point of failure. To solve the problems of CMM and in order to provide for efficient mobility management, IETF has developed a solution called distributed mobility management (DMM), in which mobility is handled via the nearest mobility anchor. In this paper, we propose a DMM solution with handover operations for SDN-enabled mobile networks. The advantage of the proposed solution is that intra and inter handover procedures are defined with the data buffering and forwarding processes between base stations and mobility anchors. We adopt a simulation model to evaluate and compare the proposed solution with the existing solution in terms of handover latency, packet loss and handover failures.

scholarly journals Mobile Network Architectures and Context-Aware Network Control Technology in the IoT Era

2018 ◽  
Vol E101.B (10) ◽  
pp. 2083-2093 ◽  
Author(s):  
Takanori IWAI ◽  
Daichi KOMINAMI ◽  
Masayuki MURATA ◽  
Ryogo KUBO ◽  
Kozo SATODA
Keyword(s):  
Mobile Network ◽  
Network Control ◽  
Network Architectures ◽  
Control Technology ◽  
Context Aware

scholarly journals Improving the network traffic classification using the Packet Vision approach

2020 ◽  
Author(s):  
Rodrigo Moreira ◽  
Larissa Rodrigues ◽  
Pedro Rosa ◽  
Flávio Silva
Keyword(s):  
Mobile Networks ◽  
Network Traffic ◽  
State Of The Art ◽  
Security And Privacy ◽  
Network Services ◽  
Network Architectures ◽  
Traffic Classification ◽  
Raw Data ◽  
Network Traffic Classification ◽  
Application Aware

The network traffic classification allows improving the management, and the network services offer taking into account the kind of application. The future network architectures, mainly mobile networks, foresee intelligent mechanisms in their architectural frameworks to deliver application-aware network requirements. The potential of convolutional neural networks capabilities, widely exploited in several contexts, can be used in network traffic classification. Thus, it is necessary to develop methods based on the content of packets transforming it into a suitable input for CNN technologies. Hence, we implemented and evaluated the Packet Vision, a method capable of building images from packets raw-data, considering both header and payload. Our approach excels those found in state-of-the-art by delivering security and privacy by transforming the raw-data packet into images. Therefore, we built a dataset with four traffic classes evaluating the performance of three CNNs architectures: AlexNet, ResNet-18, and SqueezeNet. Experiments showcase the Packet Vision combined with CNNs applicability and suitability as a promising approach to deliver outstanding performance in classifying network traffic.

scholarly journals Base Station Energy Efficiency Improvement for Next Generation Mobile Networks

2017 ◽  
Vol 63 (2) ◽  
pp. 187-194 ◽  
Author(s):  
Weston Mwashita ◽  
Marcel Ohanga Odhiambo
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Carbon Dioxide Emissions ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Data Traffic ◽  
Energy Efficiency Improvement ◽  
Next Generation Mobile Networks ◽  
Operational Expenditure

Abstract As more and more Base Stations (BSs) are being deployed by mobile operators to meet the ever increasing data traffic, solutions have to be found to try and reduce BS energy consumption to make the BSs more energy efficient and to reduce the mobile networks’ operational expenditure (OPEX) and carbon dioxide emissions. In this paper, a BS sleeping technology deployable in heterogeneous networks (HetNets) is proposed. The proposed scheme is validated by using extensive OMNeT++/SimuLTE simulations. From the simulations, it is shown that some lightly loaded micro BSs can be put to sleep in a HetNet when the network traffic is very low without compromising the QoS of the mobile network.

scholarly journals A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization

2021 ◽  
Vol 11 (16) ◽  
pp. 7686
Author(s):  
Adriano Lopes ◽  
João Oliveira ◽  
Pedro Sebastião ◽  
Marco Sousa ◽  
Pedro Vieira
Keyword(s):  
Mobile Networks ◽  
Network Performance ◽  
Mobile Network ◽  
Life Cycle Management ◽  
Functional Requirements ◽  
Modular Architecture ◽  
Web Based ◽  
Multiple Data ◽  
Network Simulations ◽  
User Friendly

Mobile networks management is increasingly critical due to heavy communications usage by customers and complex due to the multiple technologies and systems deployed. Thus, mno are constantly looking for better software solutions and tools to help them increase network performance and manage their networks more efficiently. In this paper, we present a modular web-based software solution to tackle problems related to mobile network planning, operation and optimization. The solution is focused on a set of functional requirements carefully chosen to support the network life cycle management, from planning to oam and optimisation stages. Based on a 3-tier modular architecture and implemented using only open-source software, the solution handles multiple data sources (e.g., dt and pm) and multiple ran technologies. mno can explore all available data through a flexible and user-friendly web interface, that also includes map-based visualization of the network. Moreover, the solution incorporates a set of recently developed and validated ran algorithms, supporting tasks of network diagnosis, optimization, and planning. Also, with the purpose of optimizing the network, mno can investigate network simulations, using the ran algorithms, of how the network will behave under certain conditions, and visualize the outcome of those simulations.

scholarly journals Method of intelligent content management in mobile networks

2020 ◽  
Vol 68 (3) ◽  
Author(s):  
T. A. Maksymyuk ◽  
◽  
B. P. Shubyn ◽  
V. S. Andrushchak ◽  
S. S. Dumych ◽  
...  
Keyword(s):  
User Experience ◽  
Mobile Networks ◽  
Network Performance ◽  
Mobile Network ◽  
Content Management ◽  
Dark Side ◽  
Multimedia Content ◽  
Physical Constraints ◽  
Content Caching ◽  
Content Popularity

With the advent of 5G, the market has been expecting the immersive user experience with rich multimedia content. Meeting such requirements within the physical constraints of limited spectrum and infrastructure availability is a challenging task, which prevents operators to scale their services properly. Currently, mobile operators are forced to invest large amount of money in their infrastructure, in order to maximize the capacity by network densification and higher frequency reuse factors. The dark side of such trend is that infrastructure becomes more expensive, spectrum price is getting higher and total cost of ownership for operator increases drastically. Nowadays, with the rise of artificial intelligence, cloud and edge computing the network becomes more flexible that opens many opportunities to enhance the performance and user experience. In this paper, we propose a new approach for content management in mobile network by using predictive caching of rich multimedia content in edge servers. Proposed approach is based on the content popularity prediction by using recurrent neural networks, that allows to deliver corresponding content in the close proximity to the target end users by the time it will be needed. Simulation results show that the proposed model is more than 90% accurate for both daily and weekly timeframes. Furthermore, we develop a method of personalized content caching in user devices based on their subscriptions and preferences, to make sure that user will have the best experience. Proposed approach for content management allows to improve the overall network performance by proactive content caching during the time of low network load. Moreover, the proactive caching allows to download the content in the best quality, regardless of the network congestions and bottlenecks.

Big Data in Telecommunications

2015 ◽  
pp. 67-81
Author(s):  
Yen Pei Tay ◽  
Vasaki Ponnusamy ◽  
Lam Hong Lee
Keyword(s):  
Big Data ◽  
Mobile Networks ◽  
Traffic Congestion ◽  
Big Data Analytics ◽  
Mobile Network ◽  
Consumer Electronics ◽  
Data Traffic ◽  
Network Discovery ◽  
Crowd Intelligence ◽  
4G Lte

The meteoric rise of smart devices in dominating worldwide consumer electronics market complemented with data-hungry mobile applications and widely accessible heterogeneous networks e.g. 3G, 4G LTE and Wi-Fi, have elevated Mobile Internet from a ‘nice-to-have' to a mandatory feature on every mobile computing device. This has spurred serious data traffic congestion on mobile networks as a consequence. The nature of mobile network traffic today is more like little Data Tsunami, unpredictable in terms of time and location while pounding the access networks with waves of data streams. This chapter explains how Big Data analytics can be applied to understand the Device-Network-Application (DNA) dimensions in annotating mobile connectivity routine and how Simplify, a seamless network discovery solution developed at Nextwave Technology, can be extended to leverage crowd intelligence in predicting and collaboratively shaping mobile data traffic towards achieving real-time network congestion control. The chapter also presents the Big Data architecture hosted on Google Cloud Platform powering the backbone behind Simplify in realizing its intelligent traffic steering solution.

scholarly journals Game-Theoretic Solutions for Data Offloading in Next Generation Networks

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 299 ◽  
Author(s):  
Muhammad Asif ◽  
Shafi Khan ◽  
Rashid Ahmad ◽  
Dhananjay Singh
Keyword(s):  
Stackelberg Game ◽  
Mobile Network ◽  
Economic Incentive ◽  
Base Station ◽  
Smart Devices ◽  
Theoretic Approach ◽  
Data Traffic ◽  
Game Theoretic ◽  
Frame Work ◽  
Internet Connections

In recent years, global mobile data traffic has seen an unprecedented increase. This is due to worldwide usage of smart devices, availability of fast internet connections, and the popularity of social media. The Mobile Network Operators (MNOs) are, therefore, facing problems in handling this huge traffic flow. Each type of traffic, including real-time video, audio, and text has its own Quality of Services (QoS) requirements which, if not met, may cause a sufficient loss of profit. Offloading of these traffics can be made more efficient so that values of QoS parameters are enhanced. In this work, we propose an incentive-based game-theoretic frame work for downloading data. The download of each type of data will get an incentive determined by the two-stage Stackelberg game. We model the communication among single Mobile Base Station (MBS) and multiple Access Points (APs) in a crowded metropolitan environment. The leader offers an economic incentive based on the traffic type and followers respond to the incentive and offload traffic accordingly. The model optimizes strategies of both the MBS and APs in order to make the best use of their utilities. For the analysis, we have used a combination of analytical and experimental methods. The numerical outcome characterized a direct process of the best possible offloading ratio and legalized the efficiency of the proposed game. Optimal incentives and optimal offloading was the achievement of our proposed game-theoretic approach. We have implemented the model in MATLAB, and the experimental results show a maximum payoff was achieved and the proposed scheme achieved Nash Equilibria.

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