Slicing Scheduling for Supporting Critical Traffic in Beyond 5G

Esmaeily, Ali; Kralevska, Katina; Mahmoodi, Toktam

doi:10.1109/ccnc49033.2022.9700671

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Compared to the works presented above, in our previous work [36], we maximize the data rate for each of the eMBB users while guaranteeing a minimum acceptable data rate requirement per eMBB user. We develop the resource allocation problem by formulating a loss function for each eMBB user that experiences an adverse impact on its data rate due to the puncturing by the incoming URLLC traffic.…”

Section: A Related Workmentioning

confidence: 99%

Beyond 5G Resource Slicing With Mixed-Numerologies for Mission Critical URLLC and eMBB Coexistence

Esmaeily

Mendis

Mahmoodi

et al. 2023

IEEE Open J. Commun. Soc.

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Network slicing has been a significant technological advance in the 5G mobile network allowing delivery of diverse and demanding requirements. The slicing grants the ability to create customized virtual networks from the underlying physical network, while each virtual network can serve a different purpose. One of the main challenges yet is the allocation of resources to different slices, both to best serve different services and to use the resources in the most optimal way. In this paper, we study the radio resource slicing problem for Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile Broadband (eMBB) as two prominent use cases. The URLLC and eMBB traffic is multiplexed over multiple numerologies in 5G New Radio, depending on their distinct service requirements. Therein, we present our optimization algorithm, Mixed-numerology Mini-slot based Resource Allocation (MiMRA), to minimize the impact on eMBB data rate due to puncturing by different URLLC traffic classes. Our strategy controls such impact by introducing a puncturing rate threshold. Further, we propose a scheduling mechanism that maximizes the sum rate of all eMBB users while maintaining the minimum data rate requirement of each eMBB user. The results obtained by simulation confirm the applicability of our proposed resource allocation algorithm.

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Section: A Related Workmentioning

confidence: 99%

Beyond 5G Resource Slicing With Mixed-Numerologies for Mission Critical URLLC and eMBB Coexistence

Esmaeily

Mendis

Mahmoodi

et al. 2023

IEEE Open J. Commun. Soc.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In related works, the authors of [9] focused on the design of a fronthaul network based on the IEEE 802.1CM standard assuming a single low-latency profile of fronthaul traffic. In [10], optimal allocation of radio resources for eMBB and URLLC slices was studied, however, without considering the xHaul transport domain. In [11], a slice-aware optimization of the placement of DU and CU processing resources was In [12], the eMBB traffic was handled as the best-effort traffic without latency guarantees.…”

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confidence: 99%

Analysis of Latency-Aware Network Slicing in 5G Packet xHaul Networks

Klinkowski

2022

International Journal of Electronics and Telecommunications

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Packet-switched xHaul networks are a scalable solution enabling convergent transport of diverse types of radio data flows, such as fronthaul / midhaul / backhaul (FH / MH / BH) flows, between remote sites and a central site (hub) in 5G radio access networks (RANs). Such networks can be realized using the cost-efficient Ethernet technology, which enhanced with time-sensitive networking (TSN) features allows for prioritized transmission of latency-sensitive fronthaul flows. Provisioning of multiple types of 5G services of different service requirements in a shared network, commonly referred to as network slicing, requires adequate handling of transported data flows in order to satisfy particular service / slice requirements. In this work, we investigate two traffic prioritization policies, namely, flowaware (FA) and latency-aware (LA), in a packet-switched xHaul network supporting slices of different latency requirements. We evaluate the effectiveness of the policies in a networkplanning case study, where virtualized radio processing resources allocated at the processing pool (PP) facilities, for two slices related to enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC) services, are subject to optimization. Using numerical experiments, we analyze PP cost savings from applying the LA policy (vs. FA) in various network scenarios. The savings in active PPs reach up to 40% − 60% in ring scenarios and 30% in a mesh network, whereas the gains in overall PP cost are up to 20% for the cost values assumed in the analysis.

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A Price-and-Branch Algorithm for Network Slice Optimization in Packet-Switched Xhaul Access Networks

Klinkowski

2024

Applied Sciences

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Network slicing is a concept introduced in 5G networks that supports the provisioning of multiple types of mobile services with diversified quality of service (QoS) requirements in a shared network. Network slicing concerns the placement/allocation of radio processing resources and traffic flow transport over the Xhaul transport network—connecting the 5G radio access network (RAN) elements—for multiple services while ensuring the slices’ isolation and fulfilling specific service requirements. This work focuses on modeling and optimizing network slicing in packet-switched Xhaul networks, a cost-effective, flexible, and scalable transport solution in 5G RANs. The considered network scenario assumes two types of network slices related to enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services. We formulate a network slicing planning optimization problem and model it as a mixed-integer linear programming (MILP) problem. Moreover, we develop an efficient price-and-branch algorithm (PBA) based on column generation (CG). This advanced optimization technique allows for overcoming the MILP model’s poor performance when solving larger network problem instances. Using extensive numerical experiments, we show the advantages of the PBA regarding the quality of the solutions obtained and the computation times, and analyze the packet-switched Xhaul network’s performance in various network slicing scenarios.

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Slicing Scheduling for Supporting Critical Traffic in Beyond 5G

Cited by 3 publications

References 12 publications

Beyond 5G Resource Slicing With Mixed-Numerologies for Mission Critical URLLC and eMBB Coexistence

Beyond 5G Resource Slicing With Mixed-Numerologies for Mission Critical URLLC and eMBB Coexistence

Analysis of Latency-Aware Network Slicing in 5G Packet xHaul Networks

A Price-and-Branch Algorithm for Network Slice Optimization in Packet-Switched Xhaul Access Networks

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