A survey on QoE-oriented wireless resources scheduling

Sousa, Ivo; Queluz, Maria Paula; Rodrigues, António

doi:10.1016/j.jnca.2020.102594

Cited by 24 publications

(26 citation statements)

References 159 publications

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“…Wang et al [19] 2016 Architecture for personalized QoE management Yes No No Peng et al [35] 2017 QoE-oriented mobile edge service management Yes MEC only No Sousa et al [26] 2017 QoE-based scheduling strategies No No No Skorin-Kapov et al [25], Petrangeli et al [31] 2018…”

Section: No Nomentioning

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

160

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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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Section: No Nomentioning

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

160

View full text Add to dashboard Cite

show abstract

“…According to Sousa et al, 9 the estimation of QoE is influenced by several factors related to a system, service, application, the user's preferences, or context whose actual state or setting may have an influence on the QoE for the user. These factors can be categorized as a human, system, and contents based.…”

Section: The Proposed Framework For Computing Qoementioning

confidence: 99%

“…These can be the temporal aspects, like the day of the weak or time of the day, duration of the content and its popularity, and service type. 9 However, QoE can depend on the multiple factors mentioned above, and therefore, it may be measured by various qualitative and quantitative metrics. An application dependent QoE is quantified by a mean opinion score (MOS) value, which is calculated using the degree of subjective satisfaction for the end-users of a particular application.…”

Section: The Proposed Framework For Computing Qoementioning

confidence: 99%

“…Therefore, QoE is more appropriate for characterizing the quality of the communication service provided by the operators. 9 QoE-based techniques are unsuitable for resource-constrained devices though they are better alternatives to QoSbased ones for estimating the quality of applications or services. By downgrading the parameters of QoE computational metrics, it is possible to use these techniques for devices with limited capabilities.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing quality of experience using peer‐to‐peer overlay on device‐to‐device communications

Tetarave

Tripathy

Ghosh

2020

Int J Communication

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Summary With the recent development of LTE‐A/5G technologies, data sharing among mobile devices offer an attractive opportunity to reduce Internet access. However, it requires smart strategies to share the data with low trade‐offs in time, cost, and energy. Several existing schemes offer a super‐peer‐based two‐tier model using a distributed hash table (DHT) organization for smart devices having device‐to‐device (D2D)/Bluetooth/WiFi capabilities. The primary focus of these schemes has been to reduce Internet usage by increased D2D content sharing. However, the real challenge is not in creating a two‐tier model, but evolving an efficient overlay that offers enhanced opportunities for D2D content sharing over the existing model. In this paper, we formulated a P‐median‐based selection of tier‐1 devices in a distribution network and solved it using the Lagrangian relaxation method. The tier‐2 devices become clients seeking content sharing services from tier‐1 devices. A strong motivation in this work is to raise a user's perception of the grade of service known as quality of experience (QoE). We analyzed the challenge for QoE assessment in resource‐constrained smartphones under the proposed model of enhanced D2D communication. Our focus is to establish a framework to evaluate QoE for applications and services over LTE‐A/5G networks with an improved D2D communication level. The simulation and the experimental results validate the claim that substantial improvements in QoE are possible with the proposed mathematical model for selecting and placing tier‐1 mobile devices and maintaining a DHT for D2D communication.

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“…In [32], the authors focused on RRM in cognitive radio by organizing the techniques into the four steps of spectrum sharing: spectrum sensing, spectrum allocation, spectrum access and spectrum handoff. Other surveys that included RRM as a part of their study are presented in [33] and [34], which emphasized wireless scheduling strategies based on quality of experience (QoE) awareness and interference mitigation techniques in femtocell networks, respectively. Compared to previous surveys, this study focuses on the RRM techniques for 5G HetNets, which will be different from the LTE/LTE-A HetNets.…”

Section: Introductionmentioning

confidence: 99%

Survey of Radio Resource Management in 5G Heterogeneous Networks

et al. 2020

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Radio resource management (RRM) for future fifth-generation (5G) heterogeneous networks (HetNets) has emerged as a critical area due to the increased density of small-cell networks and radio access technologies. Recent research has mostly concentrated on resource management, including spectrum utilization and interference mitigation, but the complexities of these resources have been given little attention. This paper provides an overview of the issues arising from future 5G systems and highlights their importance. The different approaches used in recently published surveys categorizing RRM schemes are discussed, and the survey method is presented. We report on a survey of HetNet RRM schemes that have been studied recently, with a focus on the joint optimization of radio resource allocation with other mechanisms. These RRM schemes were subcategorized according to their optimization metrics and qualitatively analyzed and compared. An analysis of the complexity of RRM schemes in terms of implementation and computation is presented. Several potential scopes of research for future RRM in 5G HetNets are also identified.

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A survey on QoE-oriented wireless resources scheduling

Cited by 24 publications

References 159 publications

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

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

Enhancing quality of experience using peer‐to‐peer overlay on device‐to‐device communications

Survey of Radio Resource Management in 5G Heterogeneous Networks

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