scholarly journals A probabilistic context-aware approach for quality of experience measurement in pervasive systems

Author(s):  
Karan Mitra ◽  
Arkady Zaslavsky ◽  
Christer Åhlund
Author(s):  
Hassnaa Moustafa ◽  
V. Srinivasa Somayazulu ◽  
Yiting Liao

The huge changes in multimedia and video consumption styles are leading to different challenges for the current Internet architecture in order to support the required quality of experience. A comprehensive solution to these would help the service providers and over-the-top players (OTT) to differentiate their services and the network operators to handle ever growing demands on network resources in an era of slower growth in revenues. This chapter discusses the requirements for and approaches to enhanced content delivery architectures, video delivery standards and current and future content transport mechanisms. The chapter also discusses the Quality of Experience (QoE) metrics and management for video content and introduces context-awareness in the video delivery chain. It also provides several examples for context-aware content delivery and personalized services.


2019 ◽  
Vol 101 ◽  
pp. 1041-1061 ◽  
Author(s):  
Madalena Pereira da Silva ◽  
Alexandre Leopoldo Gonçalves ◽  
Mário Antônio Ribeiro Dantas

2016 ◽  
Vol 46 (11) ◽  
pp. 1525-1545 ◽  
Author(s):  
Md. Redowan Mahmud ◽  
Mahbuba Afrin ◽  
Md. Abdur Razzaque ◽  
Mohammad Mehedi Hassan ◽  
Abdulhameed Alelaiwi ◽  
...  

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sajeeb Saha ◽  
Md. Ahsan Habib ◽  
Tamal Adhikary ◽  
Md. Abdur Razzaque ◽  
Md. Mustafizur Rahman ◽  
...  

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