Network slicing with flexible mobility and QoS/QoE support for 5G Networks

Yousaf, Faqir Zarrar; Gramaglia, Marco; Friderikos, Vasilis; Gajic, Borislava; Hugo, Dirk; Sayadi, Bessem; Sciancalepore, Vincenzo; Crippa, Marcos Rates

doi:10.1109/iccw.2017.7962821

Cited by 45 publications

(39 citation statements)

References 1 publication

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“…This leads to challenges in optimizing network resources needed by the applications (i.e. network slices in 5G) [1]. It requires CEM frameworks to be designed with modular functions (sensing, perception, learning, etc.)…”

Section: A Operator-related Challengesmentioning

confidence: 99%

“…Today's networks are designed to deliver specific services by gathering users around it -a network-centric approach. In 5G, the network is designed and built to adapt to customer demands (i.e customer-centric approach) rather than expecting customers to adapt to the network as it is [1]. This leads to the application of DA and ML in network operations.…”

Section: B Network-related Challengesmentioning

confidence: 99%

“…[15]. The agent can facilitate a large range of devices and maintain intelligent traffic management and a flexible and adaptive response time function with proactive actions is likely required [1]. Lastly, the automated and data driven analysis needs to be enabled through learning.…”

Section: Da-driven Frameworkmentioning

confidence: 99%

“…The fifth generation (5G) networks are expected to support dynamic networking profiles with automated service provisioning [1], [2]. This sets the stage for challenging network requirements, where demands on resources are often dynamic and unpredictable depending on the content.…”

Section: Introductionmentioning

confidence: 99%

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Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives

Gacanin

Wagner

2019

IEEE Network

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With advancements of next-generation programmable networks a traditional rule-based decisionmaking may not be able to adapt effectively to changing network and customer requirements and provide optimal customer experience. Customer experience management (CEM) components and implementation challenges with respect to operator, network, and business requirements must be understood to meet required demands. This paper gives an overview of CEM components and their design challenges. We elaborate on data analytics and artificial intelligence driven CEM and their functional differences. This overview provides a path toward autonomous CEM framework in next-generation networks and sets the groundwork for future enhancements.

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Section: A Operator-related Challengesmentioning

confidence: 99%

Section: B Network-related Challengesmentioning

confidence: 99%

Section: Da-driven Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives

Gacanin

Wagner

2019

IEEE Network

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“…Ahmad et al has presented [2] a collaborative approach among OTTs and ISPs where they have modelled a QoE driven approach for solving the resource sharing problem while several OTT applications use the same ISPs network peripherals. F. Z. Yousaf et al proposed [21] a new network slicing aware orchestration framework with flexible network function control system while introducing a consistent QoS/QoE management framework. H. Koumaras et al have developed a testbed [22] which orchestrates SDN/NFVs while providing real-time transcoding and capability to monitor NFV load and QoE levels.…”

Section: Related Work On Qoe For Online Videomentioning

confidence: 99%

On the modelling of CDNaaS deployment

Bulkan

Dagiuklas

Iqbal

2018

Multimed Tools Appl

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With the increasing demand for over the top media content, understanding user perception and Quality of Experience (QoE) estimation have become a major business necessity for service providers. Online video broadcasting is a multifaceted procedure and calculation of performance for the components that build up a streaming platform requires an overall understanding of the Content Delivery Network as a service (CDNaaS) concept. Therefore, to evaluate delivery quality and predicting user perception while considering NFV (Network Function Virtualization) and limited cloud resources, a relationship between these concepts is required. In this paper, a generalized mathematical model to calculate the success rate of different tiers of online video delivery system is presented. Furthermore, an algorithm that indicates the correct moment to switch between CDNs is provided to improve throughput efficiency while maintaining QoE and keeping the cloud hosting costs as lowest possible.

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The realm of metaverse: A survey

Venugopal

Subramanian

Peatchimuthu

2023

Computer Animation & Virtual

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The next step of digital development is the metaverse, which has the potential to drastically alter how people use technology and expand the range of services available beyond conventional systems that can be accessed online. As the efficiency, performance, and quality of service access reach their peak levels, the focus has shifted to the user experience. Due to this, there is an increasing demand for more involved and thorough customer service, and service providers are willing to increase their present standards. Consumers are genuinely asking for tactile and immersive elements in their digital interfaces, but these features can only be made possible by the metaverse's potentially futuristic subfields of virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR). However, the metaverse may not be widely used due to significant security and privacy issues either from underlying technology or produced by the new digital environment. A variety of fundamental problems, such as scalability and interoperability, can arise in terms of ensuring security for the metaverse because of the metaverse's inherent properties, such as immersive realism, sustainability, and heterogeneity. In this survey, we propose a hypothetical meta‐stack framework to understand the various components in the realm of metaverse and then provide wide‐ranging insights on the most recent development in metaverse realm in the context of cutting‐edge technologies, security vulnerabilities and preventive measures specific to the metaverse and the research challenges pertaining to metaverse.

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Network slicing with flexible mobility and QoS/QoE support for 5G Networks

Cited by 45 publications

References 1 publication

Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives

Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives

On the modelling of CDNaaS deployment

The realm of metaverse: A survey

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