Construction Of Flexible Networks Research Articles

Study on Drone Handover Methods Suitable for Multipath Interference Due to Obstacles

Networks constructed in the sky are known as non-terrestrial networks (NTNs). As an example of an NTN, relay transmission using drones as radio stations enables flexible network construction in the air by performing handovers with ground stations. However, the presence of structures or obstacles in the flight path causes multipath interference; consequently, the propagation environment fluctuates significantly based on the flight. In such a communication environment, it is difficult for a drone to select an optimal ground station for a handover. Moreover, unlike a terrestrial network, the propagation environment of a flying drone is affected by structures and other factors that cause multipaths based on the flight speed and altitude, making the conditions of the propagation environment even more complex. To solve these problems, we propose handover schemes between drones and the ground that consider the multipath interference caused by obstacles. The proposed methods are used to perform handovers based on an optimal threshold of received power considering interference and avoid unnecessary handovers based on the moving speed, which makes the handover seamless. Finally, we develop a simulator that evaluates the cross layer from propagation to upper network protocols in a virtual space, including buildings, evaluate the communication quality of a drone flying in a three-dimensional space, and confirm the effectiveness of the proposed methods as well as the evaluation of the real environment.

N3-CPL: Neuroplasticity-based neuromorphic network cell proliferation learning

In general, Spiking Neural Networks (SNNs) have a network structure with special methods applied to neuron models and information transmission to mimic humans biologically. However, the existing SNN structures have two problems, such as fixed existing Artificial Neural Network structures and difficulty in learning due to lack of spike information during information transfer. Recently, many approaches of learning SNNs have been proposed in order to alleviate those two drawbacks. However, it is very difficult to overcome the drawbacks only by the learning method without the fundamental solution for the structure. In order to solve the problem of structure and learning method, we propose a novel flexible network construction method using neurogenesis-based cell proliferation concept and Triple Simultaneous- Spike Timing Dependent Plasticity (TS-STDP) which is improved learning method through neuroplasticity-based spike timing. We build the network flexibly and automatically by employing the concept that not only one neuron exists in the neural network, but also that various cells proliferate and transform from stem cells to function. In addition, TS-STDP is designed by considering the correlation of signal response among several neurons to solve the lack of information due to spike sparsity, which is a disadvantage of STDP. In the experimental section, we demonstrate and analyze our method using Mixed National Institute of Standards and Technology image data. Our method is 2.7× better in memory efficiency and 1.7× better in computational efficiency than the existing method. In particular, the research that automatically constructs the network structure is the first to my knowledge.

Self‐Organized Cell Outage Detection Architecture and Approach for 5G H‐CRAN

An attractive architecture called heterogeneous cloud radio access networks (H‐CRAN) becomes one of the important components of 5G networks, which can provide ubiquitous high‐bandwidth services with flexible network construction. However, massive access nodes increase the risk of cell outages, leading to negative impact on user‐perceived QoS (Quality of Service) and QoE (Quality of Experience). Thus, cell outage management (COM) became a key function proposed in SON (Self‐Organized Networks) use cases. Based on COM, cell outage detection (COD) will be resolved before cell outage compensation (COC). Currently few studies concentrate on COD for 5G H‐CRAN, and we propose self‐organized COD architecture and approach for it. We firstly summarize current COD solutions for LTE/LTE‐A HetNets and then introduce self‐organized architecture and approach suitable for H‐CRAN, which includes COD architecture and procedures, and corresponding key technologies for it. Based on the architecture, we take a use case with handover data analysis using modified LOF (Local Outlier Factor) detection approach to detect outage for different kinds of cells in H‐CRAN. Results show that the proposed approach can identify the outage cell effectively.

Length Shuffle: Achieving high performance and flexibility for data center networks design

Scale-out data center requires the underlying network to provide high performance and design flexibility on commodity switches. Current rigid architectures can provide high performance, but they hardly support network design flexibility. Flexible proposals address the issue of elasticity in the rigid networks. However, the introduction of random connection cannot provide guaranteed network performance. In this paper, we proposed Length Shuffle connection to address the performance issue in flexible data center networks. The proposed approach follows a greedy principle that gradually connects the furthest two switches with their available ports. Length Shuffle connection can reduce the number of long paths significantly, which results in a small average length of routing path. The proposed connection can work with random connection and regular connection in flexible network construction, and does not interfere the original routing protocols. Numerical analysis shows the nice properties of Length Shuffle connection in various dimensions. The extensive experimental results demonstrate the advantages of Length Shuffle connection in data transmission delay and aggregate throughput under different traffic patterns.

Topology Management and Route Establishment Method for Base Station Networks Using Cognitive Radio

Cognitive radio, which utilizes the radio frequency spectrum efficiently by recognizing radio resource availability, is an attractive technology for overcoming the shortage of radio frequency. From the perspective of networking, cognitive radio technologies are also useful since they allow flexible network construction. This paper proposes base station networks using cognitive radio technologies. In order to achieve efficient utilization of the radio frequency spectrum and flexible network construction, we also propose a topology management and route control method for our proposed base station network. Our method shares the status of the wireless links along with topology information and establishes routes by using this information. Through simulation, we evaluate that our method significantly improves the throughput by efficient utilization of the radio frequency spectrum. Moreover, we demonstrate that our method works well when the size of the network gets larger.