Scheduling For 5G Cellular Networks With Priority And Deadline Constraints

Hadar, Ido; Raviv, Li-on; Leshem, Amir

doi:10.1109/icsee.2018.8646225

Cited by 12 publications

(5 citation statements)

References 16 publications

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“…Considering RT solutions, works like [19], [32], [33] use schedulers based on EDF to assign priorities to packets based on their deadlines. EDF ensures the packets with the earliest deadline are transmitted first.…”

Section: Related Workmentioning

confidence: 99%

A Stochastic Network Calculus (SNC)-Based Model for Planning B5G uRLLC RAN Slices

Adamuz-Hinojosa

Sciancalepore²,

Ameigeiras

et al. 2023

IEEE Trans. Wireless Commun.

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Radio Access Network (RAN) slicing involves several challenges. In particular, the Mobile Network Operator (MNO) must ensure -before deploying each slice-that corresponding requirements can be met throughout its lifetime. For ultra-Reliable Low Latency Communication (uRLLC) slices, the MNO must guarantee the packet transmission delay within a delay budget with a certain probability. Most existing solutions focus on allocating dynamically radio resources to maximize the number of packets, whose transmission delay is within the delay budget. However, these solutions do not ensure the violation probability is below a target value in the long term. In this paper, we focus on slicing from a planning perspective. Specifically, we propose a Stochastic Network Calculus (SNC)-based model, which given the amount of radio resources allocated for a uRLLC slice, the target violation probability and the traffic demand distribution, provides the delay bound for such conditions. Additionally, we propose heuristics for planning uRLLC slices. Interestingly, such heuristics benefit from the proposed SNC-based model to compute the amount of radio resources to be assigned to each slice while its delay bound, given a target

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Section: Related Workmentioning

confidence: 99%

A Stochastic Network Calculus (SNC)-Based Model for Planning B5G uRLLC RAN Slices

Adamuz-Hinojosa

Sciancalepore²,

Ameigeiras

et al. 2023

IEEE Trans. Wireless Commun.

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“…We then relax the problem into a linear program by allowing Time Division Multiplexing (TDM) at the sub-frame level. This work performs a parallel packet assignment differently than sequential greedy policies that the authors presented in [6], [11], and [12]. We use the following notation: boldface capital letters denote matrices, boldface lowercase letters denote vectors, and standard lowercase letters denote scalars.…”

Section: B Contributionmentioning

confidence: 99%

Joint Scheduling and Resource Allocation for Packets With Deadlines and Priorities

Raviv

Leshem

2023

IEEE Commun. Lett.

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Cellular networks provide communication for different applications. Some applications have strict and very short latency requirements, while others require high bandwidth with varying priorities. The challenge of satisfying the requirements grows in congested traffic where some packets might miss their deadlines. Unfortunately, we prove that the problem is NP-Hard. To overcome this, we propose a new scheduling policy for packets with multiple priorities, latency requirements, and strict deadlines. To alleviate the complexity, our solution incorporates a novel time domain relaxation solved by linear programming. Simulation results show that this method outperforms existing scheduling strategies.

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“…However, 3GPP specifications have not outlined any programming policies to support period of time or non‐real‐time application services, however leaves its style and implementation to the vendors. Hadar et al state 1 priorities and deadlines are taken into account for allocating resource blocks (RBs) and spatial beams to users by means of a simple scheduling algorithm. The overall system performance depends on the scheduling; it is stated by Kwan et al 2 Mennerich et al, 3 and Lien et al 4 Simply representing the scheduling problem as to allocate the scheduling block (SB) to a subset of user equipment (UE) (3GPP term for mobile terminal) in order to achieve some objective function.…”

Section: Literature Surveymentioning

confidence: 99%

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

Pradeep¹,

Lakshminarasimman

2022

Int J Communication

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Summary The increase in mobile communication has been caused the network traffic problem. For that, phantom cell is used for further spectrum efficiency enhancements. In this paper, improved cat swarm optimization clustering (ICSOC)‐based energy aware load balancing is made for both macro cell and small cell to improve the broadband network efficiency using 5G and beyond wireless networks. Then, Multilevel Feedback Queue with Round Robin (MFQ‐RR) scheduling is used to provide superior channel quality and well improved resource sharing for mobile phones. In this wireless network, the phantom cells provided a feasible and cost‐effective way of refining the network coverage and capacity for both local and wide area networks because of their low cost and easy deployment. This system has highly efficient, cost effective, and flexible that will fulfill the end user expectations, and it enhances the capacity and flexible multi‐RAT access to support the diverse applications. This system performance is evaluated using MATLAB 12 software. From experimental results, it is observed that the throughput and spectral efficiency are increased by 20% and 35%, respectively. As well as the packet delay is reduced to 12% and packet loss ratio is 33% decreased when compared with the existing techniques.

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Scheduling For 5G Cellular Networks With Priority And Deadline Constraints

Cited by 12 publications

References 16 publications

A Stochastic Network Calculus (SNC)-Based Model for Planning B5G uRLLC RAN Slices

A Stochastic Network Calculus (SNC)-Based Model for Planning B5G uRLLC RAN Slices

Joint Scheduling and Resource Allocation for Packets With Deadlines and Priorities

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

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