A Resource Allocation Mechanism for Video Mixing as a Cloud Computing Service in Multimedia Conferencing Applications

TL;DR

This paper presents a resource allocation mechanism for cloud-based video mixing in multimedia conferencing, optimizing scalability and QoS through an ILP model and heuristic, outperforming existing solutions in supporting more users.

Contribution

It introduces a novel resource allocation approach for cloud video mixing that enhances scalability and QoS in multimedia conferencing applications.

Findings

Supports more participants than existing methods.

Maintains QoS by ensuring end-to-end delay constraints.

Demonstrates effectiveness through simulation results.

Abstract

Multimedia conferencing is the conversational exchange of multimedia content between multiple parties. It has a wide range of applications (e.g. Massively Multiplayer Online Games (MMOGs) and distance learning). Many multimedia conferencing applications use video extensively, thus video mixing in conferencing settings is of critical importance. Cloud computing is a technology that can solve the scalability issue in multimedia conferencing, while bringing other benefits, such as, elasticity, efficient use of resources, rapid development, and introduction of new applications. However, proposed cloud-based multimedia conferencing approaches so far have several deficiencies when it comes to efficient resource usage while meeting Quality of Service (QoS) requirements. We propose a solution to optimize resource allocation for cloud-based video mixing service in multimedia conferencing applications, which can support scalability in terms of number of users, while guaranteeing QoS. We formulate the resource allocation problem mathematically as an Integer Linear Programming (ILP) problem and design a heuristic for it. Simulation results show that our resource allocation model can support more participants compared to the state-of-the-art, while honoring QoS, with respect to end-to-end delay.