Scalable and Cost-effective Live Video Encoding and Delivery in Cloud

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Live media streaming has become one of the most important applications over the Internet. However, having an all-round scalable, reliable, responsive and cost-effective solution for delivery of live video over multiple platforms is still a challenge. To deliver live video over a variety of platforms like laptops, mobile phones, tablets, gaming consoles, etc., the video needs to be encoded to appropriate format based on the device on which it is to be rendered. This is due to the heterogeneity and limited computing resources present in the devices. The traditional way of using hardware encoder has been known to be expensive and inefficient. Cloud provides virtually infinite on-demand resources for encoding and streaming. The main idea of this proposal is to vary the number of encoding/transcoding and streaming servers dynamically based on the user demand for each type of stream. We proposed a framework to deliver live video over multiple platforms and used Artificial Neural Networks (ANN) to predict user demand in [1]. This report is an extension to [1]. In this report, we formulate the resource allocation problem as a Multi-objective Integer Linear Programming (ILP) problem based on ANN predictions.

Journal

  • ITE Technical Report

    ITE Technical Report 39.20 (0), 13-16, 2015

    The Institute of Image Information and Television Engineers

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