Design a real-time video streaming application that allows users to stream live video and interact with viewers in real-time. Explain how different cloud services, such as AWS Elemental Media Live for video encoding, AWS Elemental Media Package for content packaging, and Amazon CloudFront for content delivery, can be utilized to ensure a seamless and scalable real-time video streaming experience.

Middleware Technologies

Topic : Real-time Video Streaming Application

We’ll go through a Case study on Real-time Video Streaming Application:

Overview:

Let us take an application STARtube is a platform that allows users to stream live video content, such as gaming, events, workshops, and more. Users can create their channels, go live, and interact with viewers in real-time.

Features:

User Registration and Authentication: Users can sign up with their email or social media accounts. Authentication ensures secure access to the platform.

 

Channel Creation: Once registered, users can create their own channels. Each channel has a unique name and description.

 

Live Streaming: STARtube offers a user-friendly interface for going live. Users can choose to stream from their device's camera or external cameras. Low-latency streaming ensures minimal delay between the live event and viewer reception.

 

Real-time Chat: Viewers can interact with the streamer and each other through a real-time chat feature, fostering engagement and community building.

 

Monetization Options: STARtube supports multiple monetization options, including ads, subscriptions, and virtual gifts that viewers can purchase and send to streamers.

 

Quality Settings: Both streamers and viewers can adjust the streaming quality based on their internet speed and device capabilities.

 

Notifications: Users receive notifications when their favorite streamers go live, new content is uploaded, or when they receive interactions (likes, comments, gifts).

 

Discoverability: The platform recommends streams to users based on their interests, viewing history, and trending content.

 

Technical Challenges:

 

Low Latency: Achieving low latency in real-time streaming is challenging due to the time required for encoding, transmission, and decoding. Advanced video codecs and optimized network protocols are crucial.

 

Scalability: Handling a large number of concurrent viewers and streamers requires a scalable infrastructure with load balancing and efficient resource management.

 

Content Delivery: Implementing a Content Delivery Network (CDN) ensures that the stream is distributed efficiently to viewers around the world.

 

Security: Ensuring content security and preventing unauthorized access to streams is essential. Encryption and secure authentication mechanisms are needed.

 

Chat System: Implementing a real-time chat system that can handle high loads and provide a smooth user experience requires robust backend infrastructure.

 

Outcome:

STARtube becomes a popular platform for both streamers and viewers. It hosts a wide range of live content, from gaming tournaments to educational workshops. The platform's interactive features and monetization options attract a dedicated user base, making it a successful real-time video streaming application.

 

Here's a high-level overview of how you could design a real-time video streaming application using the mentioned AWS services:

 

1. AWS Elemental Media Live (Video Encoding): This service is used to encode the live video feed into multiple adaptive bit-rate streams that cater to various device capabilities and network conditions. The service can take a single high-quality video input and create multiple output streams at different bit rates and formats.

 

2. AWS Elemental Media Package (Content Packaging): Once the video is encoded, it needs to be properly packaged for delivery to end-users. AWS Elemental Media Package can dynamically package the encoded streams into the appropriate formats like HLS or DASH and handle things like encryption and content protection.

 

3. Amazon CloudFront (Content Delivery): This service acts as a Content Delivery Network (CDN) that helps distribute the video streams efficiently to viewers across the globe. CloudFront provides low-latency, high-speed delivery by caching content at edge locations close to the viewers. This reduces the load on your main server and ensures a smooth viewing experience.

 

Here's how these services work together:

 

1. Video Ingestion: The live video feed from the source (camera or encoder) is sent to AWS Elemental Media Live for encoding. It transcodes the raw video input into various bit rates and formats.

 

2. Packaging and Encryption: AWS Elemental Media Package receives the encoded streams and packages them into formats like HLS or DASH. It can also apply encryption and digital rights management (DRM) if needed to protect the content.

 

3. Content Distribution: Amazon CloudFront is configured to serve the packaged video streams. It caches the content at edge locations to ensure low-latency delivery to viewers. This minimizes the load on the main server, allowing for smooth and scalable content distribution.

 

4. Viewing Experience: Viewers access the live streams via web or mobile applications. They receive the video content from the nearest CloudFront edge location, resulting in reduced buffering and better quality.

 

5. Real-time Interaction: To facilitate real-time interaction, you might integrate features like live chat or comments. This interaction layer can be built using AWS services like Amazon API Gateway for managing APIs, AWS Lambda for serverless functions, and Amazon DynamoDB for storing chat/comment data.

 

6. Scaling: As the viewer count grows, the architecture scales automatically. AWS services are designed to handle increased traffic by provisioning resources dynamically.

 

By using AWS Elemental Media Live for encoding, AWS Elemental Media Package for content packaging, and Amazon CloudFront for content delivery, you ensure a seamless and scalable real-time video streaming experience for users while also enabling real-time interactions. Remember to configure proper security measures, such as authentication and authorization, to protect your content and users' interactions.

 

System Design

Introduction

The process of translating requirements into a visual representation of the software is called design. The goal of the designing phase is to develop a solution for the issue that the requirement document has identified. In this phase, the requirements are converted into software, shifting the focus from the problem to the solution domain.                                                                    Three distinct outputs are frequently produced by the design process:  

1. Architecture Design
2. High Level Design
3. Detailed Design

The identification of components or subsystems and their interrelationships is the main emphasis of architecture design. The modules that should be built for creating the system are identified by the high level design. The focus of thorough design is on the software implementation of the modules.

A solution, or "How to" method, for developing a new system is system design. There are various steps in the crucial phase. It offers the knowledge of procedural specifics required for putting the system that was suggested in the feasibility study into action. The emphasis is on converting design criteria into performance requirements.

Methodology / Objective

The main objectives of the designs are:                                                                           

1.   Practicality

2.   Efficiency

3.   Flexibility

4.   Completeness

5.   Security

6.   Verifiability

7.   Traceability

Context Flow Diagram

 

          The Context Flow Diagram (CFD) describes the external entities acting on the system. The environment in which the system is used is depicted in the figure.

 

Data Flow Diagram

 

          A Data Flow Diagram (DFD) is a graphical representation of the “flow” of data through an Information System. A DFD also can be used for the visualization of Data Processing. It is common practice for a designer to draw a context-level DFD first which shows the interaction between the system and outside entities. This context-level DFD is then “exploded” to show more detail of the system being modeled.

 

The DFD uses four symbols, and are explained below:

 

*       A SQUARE, which defines the source or destination of system data also called an external entity, is not responsible for any task performed by the system.

                                                                               ⬜       

*       An ARROW represents data flow. It represents the path over which data travels in the system. A data flow can move between processes, flow into or out of data stores to and from external entities. It must be must be given a name the arrow head showing the direction of flow.

                                                                →

*       A CIRCLE or BUBBLE represents a process that transforms data from one to another by performing some tasks with the data. The process name must be given a general idea of its function.

       ◯

 

*       Two HORIZONTAL PARALLEL LINES represents data store, a data store is a place where data is held temporarily from one transaction to the next or is stored permanently.

Data flow diagram describes what data flow (logical) rather than how they are processed, so it does not depend on hardware, Software, data structure or file organization.

                                                             ━━

                                                             ━━

 

TOP Level DFD – Level 1

DFD – Level 2: Broadcasting videos

 

DFD Level 3:Login process and subscription charge payment

 

DFD Level 4:Uploading videos and sending comment

 

DFD Level 5: Publishing events and broadcasting events