Hierarchical Resource Allocation in Multi-Service Wireless Networks With Wireless Network Virtualization

Han, Yan; Tao, Xiaofeng; Zhang, Xuefei; Jia, Sijia

doi:10.1109/tvt.2020.3019217

Cited by 23 publications

(7 citation statements)

References 41 publications

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“…Virtualization technology provides a new opportunity to improve resource utilization by creating virtual (rather than real) versions of corresponding resources (such as network infrastructure servers) to utilize key resources [5]. In partic-ular, the concept of network virtualization, which allows the establishment of customized virtual networks (VNS) on shared physical infrastructure, is considered one of the key technologies for the development of the future Internet, aimed at solving the obstacles of the current transformation of the Internet architecture [6,7].…”

Section: Introductionmentioning

confidence: 99%

Wireless Network Virtualization Resource Sharing Based on Dynamic Resource Allocation Algorithm

Ren

2022

Wireless Communications and Mobile Computing

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In recent years, with the continuous development of IT industry, network virtualization technology has gradually developed into a hotspot of research and application in the field of communication because IT allows the construction of customized virtual network (VN) on shared physical infrastructure. In particular, the proposal of wireless network virtualization for the development of the enhanced Internet. Because these technologies require effective algorithms named virtual network mapping (VNE) to instantiate virtual networks on the SN, on the basis of satisfying the isolation between wireless network slices, a resource allocation mechanism based on bilateral auction is proposed. At present, many researchers have proposed that network virtualization technology is a feasible way to solve the rigid Internet architecture. In the field of existing research focuses on the cable network virtualization, mainly related to the data center network and backbone, then, the side of the wireless access network virtualization the key technology research is still in its infancy, in order to accelerate the process of wireless skill for innovation and meet the demand of the difference of the emerging business, wireless network virtualization becomes the research hotspot and focus of academia and industry. However, no one has applied the dynamic resource allocation algorithm to wireless network virtualization resource sharing field. Here, this paper analyzes and summarizes the existing virtual network resource allocation schemes at home and abroad. The wireless virtual network resource allocation model and cross-domain virtual network resource allocation model are established, and the network centrality theory in social network and complex network is introduced to analyze the topology properties of virtual network and physical network, and two efficient virtual network resource allocation methods are proposed.

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Section: Introductionmentioning

confidence: 99%

Wireless Network Virtualization Resource Sharing Based on Dynamic Resource Allocation Algorithm

Ren

2022

Wireless Communications and Mobile Computing

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“…It enables multiple independent logical networks (i.e., slices) to run on a common physical network infrastructure [5], [9]. However, as V2X applications advance, the predefined slice for ultrareliable low-latency communications (URLLC) can hardly meet more and more stringent and heterogeneous service characteristics by one-shot resource allocation [6], [7], [8]. However, as V2X applications advance, the predefined slice for ultra-reliable low-latency communications (URLLC) can hardly meet more and more stringent and heterogeneous service characteristics by one-shot resource allocation [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

Zhuang

et al. 2024

IEEE Trans. on Mobile Comput.

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With the advancement of intelligent transportation systems, a series of diversified V2X applications come into being, which have different key performance indicators (KPIs) and transmission features. Moreover, multi-tier computing as a new system-level architecture distributes computing and communication capabilities anywhere between the cloud and the end-user. Unfortunately, the existing network paradigm for V2X services adopts a one-shot allocation of resources ignoring the inherent differences of V2X service. To cope with these problems, three types of refined network slices for V2X services are first proposed to simultaneously support heterogeneous service characteristics without excessively splitting resources. Considering the spatiotemporal correlation between service traffic and physical resources, a jagged slicing in multi-tier dynamic resources, which forms a "slice sandwich" brightly, is realized by a dual timescale intelligent resource management scheme. The inter-slice resource configuration is based on neural bandits with upper confidence bounds at each large-time period, while the exclusive resources are managed elastically by deep Q-learning in terms of the real-time changing network state in the small slot. We developed a simulation environment by Simulation of Urban Mobility (SUMO) including real-world road conditions and traffic models. The experiment results demonstrate that the proposed scheme can effectively guarantee KPIs of V2X services and improve the system revenue compared with benchmark algorithms.

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“…UE clustering has been applied in several studies. In [ 12 ] the resource allocation scheme contains the allocation of a resource block (RB) on a time-frequency scale to a cluster of massive machine-type communications (mMTC) UEs in a MIoT slice; however, there are no details about how the UEs are clustered. As for the scheduler, one RB may be sufficient; however, one RB is too small for a subslice as a logical network on physical layer of 5G-NR.…”

Section: Introductionmentioning

confidence: 99%

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

Kulmar

Müürsepp

Alam

2023

Sensors

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In 5G and beyond, the network slicing is a crucial feature that ensures the fulfillment of service requirements. Nevertheless, the impact of the number of slices and slice size on the radio access network (RAN) slice performance has not yet been studied. This research is needed to understand the effects of creating subslices on slice resources to serve slice users and how the performance of RAN slices is affected by the number and size of these subslices. A slice is divided into numbers of subslices of different sizes, and the slice performance is evaluated based on the slice bandwidth utilization and slice goodput. A proposed subslicing algorithm is compared with k-means UE clustering and equal UE grouping. The MATLAB simulation results show that subslicing can improve slice performance. If the slice contains all UEs with a good block error ratio (BLER), then a slice performance improvement of up to 37% can be achieved, and it comes more from the decrease in bandwidth utilization than the increase in goodput. If a slice contains UEs with a poor BLER, then the slice performance can be improved by up to 84%, and it comes only from the goodput increase. The most important criterion in subslicing is the minimum subslice size in terms of resource blocks (RB), which is 73 for a slice that contains all good-BLER UEs. If a slice contains UEs with poor BLER, then the subslice can be smaller.

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Hierarchical Resource Allocation in Multi-Service Wireless Networks With Wireless Network Virtualization

Cited by 23 publications

References 41 publications

Wireless Network Virtualization Resource Sharing Based on Dynamic Resource Allocation Algorithm

Wireless Network Virtualization Resource Sharing Based on Dynamic Resource Allocation Algorithm

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

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