scholarly journals A Flat Mobile Core Network for Evolved Packet Core Based SAE Mobile Networks

2017 ◽  
Vol 05 (05) ◽  
pp. 62-73
Author(s):  
Mohammad Al Shinwan ◽  
Trong-Dinh Huy ◽  
Kim Chul-Soo
Keyword(s):  
Mobile Networks ◽  
Core Network ◽  
Mobile Core Network ◽  
Evolved Packet Core

SDN and NFV in the mobile core: Approaches and challenges

2015 ◽  
Vol 57 (5) ◽  
Author(s):  
Michael Jarschel ◽  
Arsany Basta ◽  
Wolfgang Kellerer ◽  
Marco Hoffmann
Keyword(s):  
Mobile Networks ◽  
Research Question ◽  
Software Defined Networking ◽  
Building Blocks ◽  
Core Network ◽  
Open Research ◽  
New Concepts ◽  
Network Functions ◽  
Development Paths ◽  
Mobile Core Network

AbstractThe introduction of Software Defined Networking (SDN) and Network Functions Virtualization (NFV) has transformed the way networks will be built in the future. This development also applies to mobile networks and their evolution. How the SDN and NFV concepts will be integrated exactly is still an open research question with multiple approaches and techniques in discussion. This article provides an overview of the current discussion points with regard to development paths, building blocks, deployment scenarios, and the opportunities and challenges of the new concepts in the mobile core network context.

scholarly journals An Efficient 5G Data Plan Approach Based on Partially Distributed Mobility Architecture

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 349
Author(s):  
Mohammad Al Shinwan ◽  
Laith Abualigah ◽  
Trong-Dinh Huy ◽  
Ahmed Younes Shdefat ◽  
Maryam Altalhi ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Network Architecture ◽  
Core Network ◽  
Control Plane ◽  
Queuing Delay ◽  
Total Transmission ◽  
Time Simulation ◽  
Control Entity ◽  
The Impact ◽  
Evolved Packet Core

Reaching a flat network is the main target of future evolved packet core for the 5G mobile networks. The current 4th generation core network is centralized architecture, including Serving Gateway and Packet-data-network Gateway; both act as mobility and IP anchors. However, this architecture suffers from non-optimal routing and intolerable latency due to many control messages. To overcome these challenges, we propose a partially distributed architecture for 5th generation networks, such that the control plane and data plane are fully decoupled. The proposed architecture is based on including a node Multi-session Gateway to merge the mobility and IP anchor gateway functionality. This work presented a control entity with the full implementation of the control plane to achieve an optimal flat network architecture. The impact of the proposed evolved packet Core structure in attachment, data delivery, and mobility procedures is validated through simulation. Several experiments were carried out by using NS-3 simulation to validate the results of the proposed architecture. The Numerical analysis is evaluated in terms of total transmission delay, inter and intra handover delay, queuing delay, and total attachment time. Simulation results show that the proposed architecture performance-enhanced end-to-end latency over the legacy architecture.

Optimizing the Traffic of Voice Core Domain in UMTS Network through RNC Re-Homing

2012 ◽  
pp. 227-240
Author(s):  
Ye Ouyang ◽  
Hosein Fallah
Keyword(s):  
Mobile Networks ◽  
Base Station ◽  
Third Generation ◽  
Core Network ◽  
Core Domain ◽  
Network Controller ◽  
Next Generation Mobile Networks ◽  
The Impact ◽  
Umts Networks

The past few years have seen mobile operators transition to next-generation mobile networks, specifically from third-generation networks (3G) to long term evolution (LTE). This paper describes the basic architecture and topology of UMTS R4 core network and introduces two options in network planning, i.e., flat structure or layered structure. This paper introduces the re-homing of radio network controller (RNC) and base station controller (BSC) and studies the impact on the performance of voice core of UMTS networks. The proposed RNC re-homing models are created and analyzed for voice core of UMTS networks. The paper concludes that the appropriate RNC re-homing optimizes the traffic of voice core in UMTS network.

scholarly journals A Survey of Deep Learning for Data Caching in Edge Network

Informatics ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 43 ◽  
Author(s):  
Yantong Wang ◽  
Vasilis Friderikos
Keyword(s):  
Deep Learning ◽  
Mobile Networks ◽  
Traffic Congestion ◽  
Core Network ◽  
Data Caching ◽  
Content Caching ◽  
Model Based ◽  
Edge Network ◽  
Close Proximity ◽  
Edge Caching

The concept of edge caching provision in emerging 5G and beyond mobile networks is a promising method to deal both with the traffic congestion problem in the core network, as well as reducing latency to access popular content. In that respect, end user demand for popular content can be satisfied by proactively caching it at the network edge, i.e., at close proximity to the users. In addition to model-based caching schemes, learning-based edge caching optimizations have recently attracted significant attention, and the aim hereafter is to capture these recent advances for both model-based and data-driven techniques in the area of proactive caching. This paper summarizes the utilization of deep learning for data caching in edge network. We first outline the typical research topics in content caching and formulate a taxonomy based on network hierarchical structure. Then, many key types of deep learning algorithms are presented, ranging from supervised learning to unsupervised learning, as well as reinforcement learning. Furthermore, a comparison of state-of-the-art literature is provided from the aspects of caching topics and deep learning methods. Finally, we discuss research challenges and future directions of applying deep learning for caching.

scholarly journals Towards a Cost Optimal Design for a 5G Mobile Core Network Based on SDN and NFV

2017 ◽  
Vol 14 (4) ◽  
pp. 1061-1075 ◽  
Author(s):  
Arsany Basta ◽  
Andreas Blenk ◽  
Klaus Hoffmann ◽  
Hans Jochen Morper ◽  
Marco Hoffmann ◽  
...  
Keyword(s):  
Optimal Design ◽  
Core Network ◽  
Mobile Core Network
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