SARS: A novel QoE based service-aware resource scheduling scheme in wireless network

Lin, Xiaoyong; Wu, Wen; Zhu, Yuanyuan; Qiu, Tingting; Mi, Zhengkun

doi:10.1109/icuwb.2016.7790527

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…Specifically, the relationship between benefit and cost is not always proportional, and the related benefits of applications may increase non-proportionally with the increase in the resource cost. Additionally, user experience and satisfaction should also be considered [25]. If an application can provide a good user experience, it will result in greater user loyalty and bring more benefits to the service provider.…”

Section: Resource Allocation For Applicationsmentioning

confidence: 99%

Application-Aware Resource Allocation Based on Benefit–Cost Ratio in Computing Power Network with Heterogeneous Computing Resources

Wang,

Li,

Guo

et al. 2023

Photonics

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The computing power network (CPN) is expected to realize the efficient provisioning of heterogeneous computing power through the collaboration between cloud computing and edge computing. Heterogeneous computing resources consist of CPU, GPU, and other types of computing power. Different types of applications may have diverse requirements for heterogeneous computing resources, such as general applications, CPU-intensive applications, and GPU-intensive applications. Service providers are concerned about how to dynamically provide heterogeneous computing resources for different applications in a cost-effective manner, and how to deploy more applications as much as possible with limited resources. In this paper, the concept of the benefit–cost ratio (BCR) is proposed to quantify the usage efficiency of CPU and GPU in CPNs. An application-aware resource allocation (AARA) algorithm is designed for processing different types of applications. With massive simulations, we compare the performance of the AARA algorithm with a benchmark. In terms of blocking probability, resource utilization, and BCR, AARA achieves better performance than the benchmark. The simulation results indicate that more computing tasks can be accommodated by reducing 3.7% blocking probability through BCR-based resource allocation.

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Section: Resource Allocation For Applicationsmentioning

confidence: 99%

Application-Aware Resource Allocation Based on Benefit–Cost Ratio in Computing Power Network with Heterogeneous Computing Resources

Wang,

Li,

Guo

et al. 2023

Photonics

View full text Add to dashboard Cite

show abstract

“…Some of the challenges include QoE-aware resource discovery and isolation and QoE pricing-based allocation and security [361]. To this end, proper and more efficient QoEaware resource management, QoE-aware scheduling [362] and the whole QoE-based cross-layer software-defined approaches should be designed and implemented.…”

Section: A Qoe Management and Orchestration Challengesmentioning

confidence: 99%

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

Barakabitze

Barman

Ahmad

et al. 2020

IEEE Commun. Surv. Tutorials

168

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The highly demanding Over-The-Top (OTT) multimedia applications pose increased challenges to Internet Service Providers (ISPs) for assuring a reasonable Quality of Experience (QoE) to their customers due to lack of flexibility, agility and scalability in traditional networks. The future networks are shifting towards the cloudification of the network resources via Software Defined Networks (SDN) and Network Function Virtualization (NFV). This will equip ISPs with cutting-edge technologies to provide service customization during service delivery and offer QoE which meets customers' needs via intelligent QoE control and management approaches. Towards this end, we provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a highlevel description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoEoriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

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The effect of QoS and QoE requirements for designing task processing controller based on fuzzy logic on IoT environments

Yang

Zhang²,

Tian³

2022

Cluster Comput

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SARS: A novel QoE based service-aware resource scheduling scheme in wireless network

Cited by 6 publications

References 3 publications

Application-Aware Resource Allocation Based on Benefit–Cost Ratio in Computing Power Network with Heterogeneous Computing Resources

Application-Aware Resource Allocation Based on Benefit–Cost Ratio in Computing Power Network with Heterogeneous Computing Resources

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

The effect of QoS and QoE requirements for designing task processing controller based on fuzzy logic on IoT environments

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