QoE Support for Multi-Layered Multimedia Applications

TL;DR

This paper introduces a new multi-layered user utility model for multimedia applications within the Network Utility Maximization framework, addressing challenges in rate allocation and proposing an admission control approach to enhance QoS and QoE.

Contribution

It presents a novel multi-layered utility model based on human visual perception and proposes an admission control method to improve QoE in multi-layered multimedia networks.

Findings

Multi-layered utility model captures user experience more accurately.

Rate allocation with multi-layered utility can oscillate without proper control.

Proposed admission control improves QoS and QoE for multimedia applications.

Abstract

Congestion control protocol and bandwidth allocation problems are often formulated into Network Utility Maximization (NUM) framework. Existing solutions for NUM generally focus on single-layered applications. As applications such as video streaming grow in importance and popularity, addressing user utility function for these multi-layered multimedia applications in NUM formulation becomes vital. In this paper, we propose a new multi-layered user utility model that leverages on studies of human visual perception and quality of experience (QoE) from the fields of computer graphics and human computer interaction (HCI). Using this new utility model to investigate network activities, we demonstrate that solving NUM with multi-layered utility is intractable, and that rate allocation and network pricing may oscillate due to user behavior specific to multi-layered applications. To address this, we propose a new approach for admission control to ensure quality of service (QoS) and quality of experience (QoE).