Limiting Properties of Overloaded Multiuser Wireless Systems With Throughput-Optimal Scheduling

Wang, Xuan; Cai, Lin

doi:10.1109/tcomm.2014.2359875

Cited by 5 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…-Existence of dedicated bandwidth UEs -Demonstrate the benefits to maximize a given objective (throughput, latency, fairness, energy, etc.) [22], [23], [24] -Needs new specialized hardware to support the system -Buffer size issues.…”

Section: Scheduler Supportmentioning

confidence: 99%

“…Different from the traditional UEs that access the network, our study provides a hint of the QoS deployment strategy for MNOs and how the management of UEs with differentiated QoS services can be accomplished for next generation mobile services with core network configuration assistance for different user types. Scheduler Design: The problem of QoS support using various scheduling algorithms has been proposed for cellular networks with different objectives, such as throughput, latency, fairness, energy, etc in [22], [23], [24]. A throughput maximizing method using max-weight based scheduling algorithm is proposed in [23].…”

Section: Experimental Trialsmentioning

confidence: 99%

“…Scheduler Design: The problem of QoS support using various scheduling algorithms has been proposed for cellular networks with different objectives, such as throughput, latency, fairness, energy, etc in [22], [23], [24]. A throughput maximizing method using max-weight based scheduling algorithm is proposed in [23]. Out of different studied scheduling algorithms, Proportional Fair (PF) scheduling algorithm has attracted higher interest among the academic as well as industrial community and is widely adopted.…”

Section: Experimental Trialsmentioning

confidence: 99%

See 2 more Smart Citations

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

Zeydan¹,

Mangues‐Bafalluy²,

Dedeoglu³

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Differentiated quality-of-Service (QoS) techniques are widely used to distinguish between different service classes and prioritize service needs in mobile networks. Mobile Network Operators (MNOs) utilize QoS techniques to develop strategies that are supported by the mobile network infrastructure. However, QoS deployment strategy can ensure that the radio resources provided by the base station are easily consumed if it is not used correctly or when different techniques are used all together. In this paper, we propose a scheduling algorithm and compare two different QoS deployment strategies for prioritized User Equipment (UEs) (with higher scheduling rates and dedicated bandwidth) that MNOs can use in the current infrastructure, using a commercial real-time Long Term Evolution (LTE) network in different test scenarios. Moreover, we expose the real-time user experience in terms of uplink throughput and analyze results of the UE's real-time key performance indicators (KPIs) in detail. Experiment results are evaluated considering the implications of different QoS support types on network coverage and capacity planning optimizations. Our results demonstrate that even though preconfigured resource allocations can be given to prioritize UEs, the experience of all the UEs can be affected unexpectedly in the presence of many UEs who have received different QoS deployment support. Our experimental observations have revealed that location of the UEs with respect to Base Station (BS) and the availability of dedicated bandwidth UEs inside cell may have implications on the apriori defined resource allocation strategies of the other UEs. INDEX TERMS QoS, differentiated services, mobile networks, experiments.

show abstract

Section: Scheduler Supportmentioning

confidence: 99%

Section: Experimental Trialsmentioning

confidence: 99%

Section: Experimental Trialsmentioning

confidence: 99%

See 1 more Smart Citation

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

Zeydan¹,

Mangues‐Bafalluy²,

Dedeoglu³

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Thus, it is not practical to employ FLS scheme at future ultra‐dense networks. Nguyen and Rao, Chen, and Wang and Cai developed optimal solutions for wireless multiuser scheduling problem. The solutions are based on linear programming and machine learning tools.…”

Section: Related Workmentioning

confidence: 99%

Throughput enhanced scheduling (TES) scheme for ultra‐dense networks

Hacı

Abdelbari

2019

Int J Communication

View full text Add to dashboard Cite

This paper proposes two novel packet scheduling schemes, called as throughput enhanced scheduling (TES) and TES plus (TES+), for future ultra-dense networks. These schemes introduce two novel parameters to the scheduling decision making and reformulate the parameters used by the state-of-the-art schemes. The aim is to have a more balanced weight distribution between delay and throughput-related parameters at scheduling decisions. Also include a new telecommunications related parameter into scheduling decision making that has not been studied by popular schedulers. The performance of novel schemes is compared with well-known schemes-proportional fairness (PF), exponential/proportional fairness (EXP/PF), and M-LWDF. For performance evaluation, five performance metrics-average spectral efficiency and delay, quality of service (QoS) violation ratio, jitter, and Jain's fairness index-are investigated. The simulation results show that proposed schemes can outperform all the compared scheduling schemes. KEYWORDS5G networks, EXP/PF, M-LWDF, packet scheduling, real-time traffic, ultra-dense networks Int J Commun Syst. 2020;33:e4229.wileyonlinelibrary.com/journal/dac

show abstract

“…Many scheduling algorithms have been proposed for single-radio single-channel (SR-SC) networks. A max-weight-based scheduling algorithm was proposed in [14], where the stability of the queue length was transformed into a convex optimization problem with the objective being to maximize the average throughput. The epidemic theory and truthful mechanism were adopted in scheduling algorithms to satisfy the delay constraint in [15,16], respectively.…”

Section: Introductionmentioning

confidence: 99%

Distributed Rate-Control and Delay-Guaranteed Scheduling in MR-MC Wireless Mesh Networks

Zhao

Geng

2019

Sensors

View full text Add to dashboard Cite

Wireless mesh networks (WMNs) can provide flexible wireless connections in smart city, Internet of Things (IoT), and device-to-device (D2D) communications. The performance of WMNs can be greatly enhanced by adopting the multi-radio multi-channel (MR-MC) technique, which enables a node to communicate with more nodes simultaneously. However, increasing the number of data flows will result in network congestion and longer end-to-end delays. In this paper, a distributed rate-control and delay-aware (DRDA) scheduling algorithm is proposed based on a multidimensional conflict graph. To satisfy the arrival rate and delay constraints of a flow, two virtual queues are constructed. All the actual and virtual queues are stabilized by the Lyapunov drift optimization method. The scheduling policy of each flow is optimized only based on the local information. The simulation results show that our proposed algorithm can maintain the stability of all the queues and strictly satisfy the arrival rate and delay constraint of each flow in the network as well.

show abstract

Limiting Properties of Overloaded Multiuser Wireless Systems With Throughput-Optimal Scheduling

Cited by 5 publications

References 37 publications

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

Throughput enhanced scheduling (TES) scheme for ultra‐dense networks

Distributed Rate-Control and Delay-Guaranteed Scheduling in MR-MC Wireless Mesh Networks

Contact Info

Product

Resources

About