# Resource Allocation Mechanism for Media Handling Services in Cloud Multimedia Conferencing

## TL;DR

This paper presents a resource allocation mechanism for media handling in cloud-based multimedia conferencing, optimizing resource use and scalability while ensuring QoS through ILP formulation and heuristics.

## Contribution

It introduces a novel resource allocation and scaling solution that composes media services and guarantees QoS in cloud multimedia conferencing.

## Key findings

- Efficient resource allocation meets QoS in multimedia conferencing.
- The heuristic outperforms baseline methods in simulations.
- Scalability is improved for varying participant numbers and distributions.

## 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). Media handling services (e.g., video mixing, transcoding, and compressing) are critical to multimedia conferencing. However, efficient resource usage and scalability still remain important challenges. Unfortunately, the cloud-based approaches proposed so far have several deficiencies in terms of efficiency in resource usage and scaling, while meeting Quality of Service (QoS) requirements. This paper proposes a solution which optimizes resource allocation and scales in terms of the number of participants while guaranteeing QoS. Moreover, our solution composes different media handling services to support the participants' demands. We formulate the resource allocation problem mathematically as an Integer Linear Programming (ILP) problem and design a heuristic for it. We evaluate our proposed solution for different numbers of participants and different participants' geographical distributions. Simulation results show that our resource allocation mechanism can compose the media handling services and allocate the required resources in an optimal manner while honoring the QoS in terms of end-to-end delay.

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Source: https://tomesphere.com/paper/1903.11722