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Efficient and optimised resource allocation for augmented, virtual and mixed reality applications

Iftikhar, Mohsin ; Landfeldt, Björn LU ; Zhong, Ziyu LU ; Alsamahi, Maryam and Murtaza, Mohsin (2024) In Lecture Notes on Data Engineering and Communications Technologies
Abstract
Extended Reality (XR) serves as a broad term that encompasses several immersive technologies, including Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR). Currently, most XR devices are connected by cables, which restrict user mobility and negatively impact the overall Quality of Experience (QoE) for users. XR devices face limitations not only in terms of connectivity but also in their processing and storage capabilities, which restrict their ability to handle complex tasks and store large amounts of data. Typically, data from these devices is offloaded and processed in a nearby edge cloud, which provides a more efficient and responsive environment for handling computationally intensive tasks. Optimizing resource... (More)
Extended Reality (XR) serves as a broad term that encompasses several immersive technologies, including Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR). Currently, most XR devices are connected by cables, which restrict user mobility and negatively impact the overall Quality of Experience (QoE) for users. XR devices face limitations not only in terms of connectivity but also in their processing and storage capabilities, which restrict their ability to handle complex tasks and store large amounts of data. Typically, data from these devices is offloaded and processed in a nearby edge cloud, which provides a more efficient and responsive environment for handling computationally intensive tasks. Optimizing resource allocation in the edge cloud for mobile users of XR applications poses significant challenges. This is due to the need to balance diverse requirements such as low latency, high bandwidth, and efficient processing, while also addressing the constraints of edge computing environments. As a result, cloud providers face significant challenges in meeting deadlines and ensuring each user's Quality of Service (QoS) requirements, particularly given the diverse characteristics of the users. To date, various scheduling mechanisms have been proposed for the edge cloud to meet QoS requirements, addressing the challenges of ensuring optimal performance and reliability in edge computing environments. This paper emphasizes the various challenges that edge clouds face from the perspective of ensuring high QoE for users of Extended Reality (XR) applications. We present a detailed problem scenario and provide an overview of the most relevant work in this domain, emphasizing key studies and findings that address the challenges and potential solutions in this area. This includes discussions on how edge computing can enhance XR applications by mitigating latency and bandwidth issues, as well as the integration of various technologies to support these demanding applications. We further present a detailed use case for VR applications, showcasing our contributions through the collection of a comprehensive real-world dataset. This dataset offers critical insights into the practical applications of VR, enabling us to analyze its effectiveness and identify areas for enhancement. By leveraging this data, we can develop more tailored solutions that meet the evolving needs of VR users across various industries. Finally, the paper concludes by outlining potential future directions related to our current research, providing a roadmap for further exploration and development in this area. (Less)
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author
; ; ; and
organization
alternative title
Effektiv och optimerad resursallokering för förstärkt, virtuell och blandad verklighetsapplikationer
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
FOCUS-2024
series title
Lecture Notes on Data Engineering and Communications Technologies
pages
10 pages
publisher
Springer
ISSN
2367-4520
2367-4512
project
ELLIIT LU P01: WP2 Networking solutions
language
English
LU publication?
yes
id
cadb020f-9103-4259-92b6-953f84688cba
date added to LUP
2025-12-15 11:06:23
date last changed
2025-12-17 09:39:28
@inproceedings{cadb020f-9103-4259-92b6-953f84688cba,
  abstract     = {{Extended Reality (XR) serves as a broad term that encompasses several immersive technologies, including Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR). Currently, most XR devices are connected by cables, which restrict user mobility and negatively impact the overall Quality of Experience (QoE) for users. XR devices face limitations not only in terms of connectivity but also in their processing and storage capabilities, which restrict their ability to handle complex tasks and store large amounts of data. Typically, data from these devices is offloaded and processed in a nearby edge cloud, which provides a more efficient and responsive environment for handling computationally intensive tasks. Optimizing resource allocation in the edge cloud for mobile users of XR applications poses significant challenges. This is due to the need to balance diverse requirements such as low latency, high bandwidth, and efficient processing, while also addressing the constraints of edge computing environments. As a result, cloud providers face significant challenges in meeting deadlines and ensuring each user's Quality of Service (QoS) requirements, particularly given the diverse characteristics of the users. To date, various scheduling mechanisms have been proposed for the edge cloud to meet QoS requirements, addressing the challenges of ensuring optimal performance and reliability in edge computing environments. This paper emphasizes the various challenges that edge clouds face from the perspective of ensuring high QoE for users of Extended Reality (XR) applications. We present a detailed problem scenario and provide an overview of the most relevant work in this domain, emphasizing key studies and findings that address the challenges and potential solutions in this area. This includes discussions on how edge computing can enhance XR applications by mitigating latency and bandwidth issues, as well as the integration of various technologies to support these demanding applications. We further present a detailed use case for VR applications, showcasing our contributions through the collection of a comprehensive real-world dataset. This dataset offers critical insights into the practical applications of VR, enabling us to analyze its effectiveness and identify areas for enhancement. By leveraging this data, we can develop more tailored solutions that meet the evolving needs of VR users across various industries. Finally, the paper concludes by outlining potential future directions related to our current research, providing a roadmap for further exploration and development in this area.}},
  author       = {{Iftikhar, Mohsin and Landfeldt, Björn and Zhong, Ziyu and Alsamahi, Maryam and Murtaza, Mohsin}},
  booktitle    = {{FOCUS-2024}},
  issn         = {{2367-4520}},
  language     = {{eng}},
  month        = {{12}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes on Data Engineering and Communications Technologies}},
  title        = {{Efficient and optimised resource allocation for augmented, virtual and mixed reality applications}},
  year         = {{2024}},
}