Kurento Media Server (KMS) is an open-source media server that allows developers to build real-time multimedia applications and services. It provides a set of media processing capabilities, including audio and video recording, playback, streaming, and manipulation.

The architecture of Kurento Media Server is based on a modular design that allows it to be easily extended and customized to meet specific requirements. The main components of Kurento Media Server are:

• Media Processing Elements (MPEs): These are the functional modules that perform the actual media processing tasks, such as encoding, decoding, filtering, and mixing. MPEs can be combined in different ways to create complex media processing pipelines.

• Pipeline: A pipeline is a logical sequence of MPEs that are connected to form a processing graph. Each MPE in the pipeline processes the media data and passes it on to the next MPE in the sequence.

• WebRTC Signaling: Kurento Media Server uses WebRTC signaling protocols to establish and manage real-time communication sessions between endpoints. The signaling messages are used to negotiate the session parameters, exchange media data, and control the media processing pipeline.

• Media Server API: Kurento Media Server provides a RESTful API that allows developers to control the media processing pipeline and configure the MPEs. The API also provides access to various media statistics, such as bitrates, frame rates, and packet loss.

• Media Server Client: The media server client is the end-user application that uses the Kurento Media Server to perform real-time media processing tasks. The client can be a web-based application, a mobile application, or a desktop application.

Overall, the architecture of Kurento Media Server is designed to be flexible and scalable, allowing developers to create customized media processing solutions for a wide range of use cases.

         +-------------------+
         | Media Server API   |
         +-------------------+
         |                   |
         | RESTful Interface |
         |                   |
         +-------------------+
         |                   |
         | Media Processing  |
         |                   |
         +---------+---------+
                   |
                   |
                   v
         +---------+---------+
         |   Pipeline        |
         +---------+---------+
                   |
                   |
                   v
         +---------+---------+
         | Media Processing  |
         | Element (MPE)     |
         +---------+---------+
                   |
                   |
                   v
         +---------+---------+
         |   WebRTC Signaling |
         +-------------------+

As shown in the diagram, the Media Server API provides a RESTful interface for controlling the media processing pipeline and accessing media statistics. The pipeline consists of a sequence of MPEs that process media data, and the WebRTC Signaling is used to establish and manage real-time communication sessions between endpoints. The Media Server Client interacts with the Media Server API to control the pipeline and perform real-time media processing tasks.

WebRTC Signalling​

WebRTC signaling is an essential component of the real-time communication system enabled by Kurento Media Server. It enables endpoints to negotiate and establish communication channels over the internet.

In the context of Kurento Media Server, WebRTC signaling is used to establish and manage real-time communication sessions between endpoints. This includes protocols like SDP (Session Description Protocol) and ICE (Interactive Connectivity Establishment).

Here's how WebRTC signaling works within Kurento Media Server:

• WebRTC Offer/Answer: When an endpoint wants to establish a WebRTC session with another endpoint, it sends an offer message that includes information about its capabilities, such as the codecs it supports, and the transport protocols it can use. The other endpoint responds with an answer message that includes its capabilities.

• ICE Candidates: Once the endpoints have exchanged offer and answer messages, they need to determine the best network path to use for the communication session. Each endpoint generates a list of ICE candidates, which are potential network paths that can be used for communication. The endpoints exchange these ICE candidates and use them to establish a direct peer-to-peer connection.

• SDP Negotiation: Once the endpoints have established a direct connection, they use the Session Description Protocol (SDP) to negotiate the details of the communication session. This includes the media types (e.g., audio or video), the codecs, and the transport protocols to be used for each media type.

• Media Pipeline: Once the SDP negotiation is complete, Kurento Media Server sets up a media processing pipeline based on the negotiated parameters. The pipeline consists of a sequence of Media Processing Elements (MPEs) that process the media data, such as encoding, decoding, filtering, and mixing.

• Real-time Communication: With the media pipeline in place, the endpoints can start to exchange media data in real-time, using the agreed-upon media formats and protocols.

In summary, WebRTC signaling within Kurento Media Server is used to establish and manage real-time communication sessions between endpoints. It enables endpoints to negotiate the details of the communication session, determine the best network path, and establish a direct peer-to-peer connection. Once the connection is established, Kurento Media Server sets up a media processing pipeline that processes the media data in real-time.

              Endpoint A                  Endpoint B
                  |                            |
                  |                            |
                  |                            |
           (1) Offer SDP               (2) Answer SDP
                  |                            |
                  |                            |
                  |                            |
     +--------------+--------------+ +--------------+--------------+
     |                              | |                              |
     |  (3) ICE Candidate Exchange  | |  (3) ICE Candidate Exchange  |
     |                              | |                              |
     +--------------+--------------+ +--------------+--------------+
                  |                            |
                  |                            |
                  |                            |
            (4) SDP Negotiation          (4) SDP Negotiation
                  |                            |
                  |                            |
                  |                            |
     +--------------+--------------+ +--------------+--------------+
     |                              | |                              |
     |       (5) Real-time           | |       (5) Real-time           |
     |    Communication Begins      | |    Communication Begins      |
     |                              | |                              |
     +------------------------------+ +------------------------------+

The diagram shows two endpoints, A and B, that want to establish a WebRTC communication session using Kurento Media Server. Here's how the signaling process works:

• Endpoint A sends an Offer SDP message to Kurento Media Server, which includes information about its capabilities, such as the codecs it supports, and the transport protocols it can use.
• Kurento Media Server forwards the Offer SDP message to Endpoint B, which responds with an Answer SDP message that includes its capabilities.
• Endpoint A and Endpoint B exchange ICE candidates, which are potential network paths that can be used for communication. The ICE candidates are used to determine the best network path for the communication session.
• Endpoint A and Endpoint B negotiate the details of the communication session using SDP. They agree on the media types (e.g., audio or video), the codecs, and the transport protocols to be used for each media type.
• With the communication parameters negotiated, real-time communication begins between Endpoint A and Endpoint B. Media data is exchanged using the agreed-upon media formats and protocols. In summary, WebRTC signaling within Kurento Media Server enables endpoints to negotiate and establish real-time communication sessions, using protocols like SDP and ICE. The signaling process ensures that the endpoints agree on the media formats, codecs, and transport protocols to be used for the communication session, and establish a direct peer-to-peer connection for efficient data transfer.

ICE Candidates​

In WebRTC, Interactive Connectivity Establishment (ICE) is used to establish a direct peer-to-peer connection between endpoints, which is necessary for real-time communication. ICE candidates are network addresses that are used by ICE to establish a direct connection between endpoints.

In WebRTC, there are two types of ICE candidates: host candidates and server-reflexive candidates.

• Host Candidates: A host candidate is an IP address and port number associated with the device where the endpoint is running. These are local network addresses of the endpoint's machine that can be used for direct communication if both endpoints are on the same network.

• Server-Reflexive Candidates: Server-reflexive candidates are network addresses that are obtained by sending a request to a STUN (Session Traversal Utilities for NAT) server. These candidates are obtained by using a NAT traversal technique that allows the endpoint to determine its public IP address and port number, which can be used for communication with endpoints outside of its local network.

To determine the ICE candidates, WebRTC endpoints perform a series of steps:

• Each endpoint collects a list of its local IP addresses and ports. These are the host candidates.

• Each endpoint sends a STUN request to a STUN server. The STUN server responds with a server-reflexive candidate, which includes the public IP address and port number of the endpoint.

• If the endpoints are unable to establish a direct connection using host and server-reflexive candidates, they may also use other types of candidates such as relay candidates, which are obtained by using a TURN (Traversal Using Relay NAT) server.

• The endpoints exchange their list of ICE candidates over the signaling channel and use them to establish a direct connection.

The ICE negotiation process continues until a direct connection is established between the endpoints or until all candidate types have been exhausted. The ICE negotiation process is important for WebRTC communication because it allows endpoints to establish a direct connection even when they are behind firewalls and NATs that would otherwise prevent direct communication.

Configuring ICE​

To configure ICE candidates in Kurento Media Server, you typically follow these steps:

• Collect the local IP addresses and ports that can be used as ICE candidates for the WebRTC endpoint.

• Create an IceCandidate object for each candidate, specifying the candidate's transport protocol, IP address, port number, and any other relevant properties.

• Add the IceCandidate objects to the WebRTC endpoint's WebRtcEndpoint using the addIceCandidate method.

• Wait for the remote endpoint to send its SDP offer, which includes its own ICE candidates.

• Process the remote endpoint's SDP offer to determine its ICE candidates.

• Add the remote endpoint's ICE candidates to the WebRTC endpoint's WebRtcEndpoint using the addIceCandidate method.

• Start the ICE connectivity checks between the endpoints to determine the best candidate pair for establishing a direct connection.

// Create a new IceCandidate object with the candidate properties
IceCandidate candidate = new IceCandidate.Builder()
        .withFoundation("foundation")
        .withComponentId(1)
        .withTransport("UDP")
        .withPriority(12345678)
        .withIp("192.168.1.100")
        .withPort(1234)
        .withType(CandidateType.HOST)
        .withGeneration(0)
        .build();

// Get the WebRtcEndpoint to which the IceCandidate will be added
WebRtcEndpoint webRtcEndpoint = ...;

// Add the IceCandidate to the WebRtcEndpoint
webRtcEndpoint.addIceCandidate(candidate);

Bandwidth Management within KMS​

Bandwidth management and configuration is an important aspect of optimizing the performance of media streams in Kurento Media Server. Kurento provides several mechanisms to manage bandwidth usage, including:

1. Bitrate Adaptation: Kurento can automatically adjust the bitrate of media streams based on network conditions and available bandwidth. This can help improve the quality of media while avoiding congestion and packet loss.

2. Dynamic Bandwidth Allocation: Kurento can allocate bandwidth dynamically to media streams based on their priority, size, and other parameters. This can help ensure that critical media streams receive sufficient bandwidth while minimizing the impact on other streams.

3. Congestion Control: Kurento can detect and respond to network congestion by reducing the bitrate of media streams or dropping packets selectively. This can help prevent network overload and improve overall performance.

To configure bandwidth management in Kurento Media Server, you can use the following settings:

• maxOutputBitrate: This property sets the maximum output bitrate that can be used by media streams in Kurento. It can be set globally or for individual media elements and endpoints.

• minOutputBitrate: This property sets the minimum output bitrate that should be used by media streams in Kurento. It can be used to ensure that media streams maintain a minimum quality level even in low bandwidth conditions.

• adaptationSet: This property configures the bitrate adaptation algorithm used by Kurento. It can be set to different values, such as "fixed", "fluid", or "manual", depending on the desired behavior.

• priority: This property sets the priority of individual media streams in Kurento. Higher priority streams will receive more bandwidth allocation and higher quality.

Example of configuring bandwidth using Kurento API​

from kurento_client import KurentoClient, MediaPipeline, WebRtcEndpoint

# Create a Kurento Client object
kurento_client = KurentoClient('ws://localhost:8888/kurento')

# Create a new media pipeline
pipeline = kurento_client.create('MediaPipeline')

# Create a WebRTC endpoint and connect it to the pipeline
webrtc = WebRtcEndpoint.Builder(pipeline).build()
webrtc.connect(webrtc)

# Configure bandwidth management settings
webrtc.set_max_output_bitrate(1000) # Set max output bitrate to 1000 kbps
webrtc.set_min_output_bitrate(500) # Set min output bitrate to 500 kbps
webrtc.set_priority(1) # Set priority to 1

# Start the media pipeline and WebRTC endpoint
pipeline.play()
webrtc.gather_candidates()

# Use the WebRTC endpoint to transmit and receive media

Media Profile in Kurento​

Example - configuring media profiles in KMS​

import org.kurento.client.*;
import org.kurento.client.MediaProfileSpecType;
import org.kurento.client.MediaProfileSpec;

// Create a new media pipeline
MediaPipeline pipeline = kurento.createMediaPipeline();

// Create a new WebRTC endpoint and connect it to the pipeline
WebRtcEndpoint webrtc = new WebRtcEndpoint.Builder(pipeline).build();
webrtc.connect(webrtc);

// Configure media profile settings
MediaProfileSpec mediaProfile = new MediaProfileSpec.Builder()
    .withVideoCodec(VideoCodec.H264)
    .withAudioCodec(AudioCodec.OPUS)
    .withTransport(Transport.TCP)
    .withMediaType(MediaProfileSpecType.WEBM)
    .withMaxVideoBitrate(2000)
    .withMaxAudioBitrate(128)
    .withMinVideoBitrate(1000)
    .withMinAudioBitrate(64)
    .build();
webrtc.setMediaProfile(mediaProfile);

// Start the media pipeline and WebRTC endpoint
pipeline.play();
webrtc.gatherCandidates();

// Use the WebRTC endpoint to transmit and receive media

Analytics in KMS​

Kurento Media Server supports integration with different analytics tools, such as monitoring systems, data processing platforms, and machine learning models.

from kurento_client import KurentoClient, MediaPipeline, MediaElement

# Create a Kurento client instance
kurento_client = KurentoClient('ws://<your-kms-address>:8888/kurento')

# Create a media pipeline
pipeline = kurento_client.create('MediaPipeline')

# Create a media element, for example a WebRTC endpoint
webrtc = pipeline.create('WebRtcEndpoint')

# Enable gathering of stats for the endpoint
webrtc.enable_stats_events('EndpointStats')

# Connect the endpoint to other media elements in the pipeline
# ...

# Start the pipeline
pipeline.play()

# Get stats for the endpoint
stats = webrtc.get_stats()

# Process the stats
# ...

# Release resources
webrtc.release()
pipeline.release()
kurento_client.close()

Use Case Studies​

AI Based QoS in KMS​

AI-based Quality of Service (QoS): Kurento can be integrated with AI algorithms to monitor and optimize the QoS of media streams. AI-based QoS algorithms can automatically adjust the media stream parameters such as resolution, bitrate, frame rate, and more based on network conditions, device capabilities, and user preferences.

Example of AI based QoS with Tensorflow​

from kurento_client import MediaPipeline, WebRtcEndpoint
import tensorflow as tf

class AIQoS:
    def __init__(self, pipeline: MediaPipeline, webrtc: WebRtcEndpoint):
        self.pipeline = pipeline
        self.webrtc = webrtc
        self.sess = tf.Session()
        self.graph = self.build_graph()
        self.qos = self.graph.get_tensor_by_name('qos:0')
        
    def build_graph(self):
        graph = tf.Graph()
        with graph.as_default():
            input_tensor = tf.placeholder(tf.float32, shape=[None, 2])
            output_tensor = tf.layers.dense(input_tensor, 1, activation=tf.sigmoid, name='qos')
        return graph
    
    def adjust_qos(self, bandwidth: float):
        input_data = [[self.webrtc.getMeasuredLatency(), bandwidth]]
        qos_value = self.sess.run(self.qos, feed_dict={self.graph.get_tensor_by_name('Placeholder:0'): input_data})
        self.webrtc.setVideoMaxBandwidth(qos_value * bandwidth)

Speech Recognition & NLP using KMS​

Machine Learning (ML) based image and speech recognition: Kurento can be integrated with ML libraries such as TensorFlow, Keras or OpenCV to perform tasks such as object detection, facial recognition, emotion detection, speech recognition, and more. Kurento can process media streams and provide results to the ML algorithms, which can then provide intelligent insights.

Natural Language Processing (NLP): Kurento can be integrated with NLP libraries such as NLTK or spaCy to perform tasks such as sentiment analysis, topic extraction, entity recognition, and more. Kurento can provide the audio or text data to NLP algorithms and receive intelligent insights.

Example KMS integration with Google Cloud Speech-to-Text API.​

from google.cloud import speech
import kurento_client

class SpeechRecognition:
    def __init__(self, pipeline: kurento_client.MediaPipeline, webrtc: kurento_client.WebRtcEndpoint, language_code: str):
        self.pipeline = pipeline
        self.webrtc = webrtc
        self.language_code = language_code
        self.client = speech.SpeechClient()
        self.streaming_config = speech.StreamingRecognitionConfig(
            config=speech.RecognitionConfig(
                encoding=speech.RecognitionConfig.AudioEncoding.OPUS,
                sample_rate_hertz=48000,
                language_code=language_code,
                model='default'
            ),
            interim_results=True
        )
        self.recognize_stream = self.client.streaming_recognize(self.streaming_config)

    def on_sdp_offer(self, offer, on_response):
        answer = offer
        answer.sdp = self.webrtc.process_offer(offer.sdp)
        on_response(answer)

    def on_ice_candidate(self, candidate):
        self.webrtc.add_ice_candidate(candidate)

    def start_recognition(self):
        self.webrtc.connect(self.pipeline)
        self.pipeline.play()
        self.webrtc.gatherCandidates()

        for chunk in self.webrtc.get_media_element().connect(self.pipeline).pull():
            if not self.webrtc.get_media_element().is_paused():
                self.recognize_stream.write(chunk)

        self.recognize_stream.close()

        for response in self.recognize_stream:
            for result in response.results:
                if result.is_final:
                    print(result.alternatives[0].transcript)
                else:
                    print(result.alternatives[0].transcript, end='')

Example: using the SpeechRecognition class​

import kurento_client
import sys
import time

kurento_client.KurentoClient.register_modules('kurento.modules.webRtcEndpoint', 'kmsserver.kurento')

pipeline = kurento_client.MediaPipeline()

webrtc = kurento_client.WebRtcEndpoint.Builder(pipeline).build()

speech_recognition = SpeechRecognition(pipeline, webrtc, 'en-US')

@speech_recognition.on('sdp_offer')
def on_sdp_offer(offer):
    print('Received SDP offer')
    answer = None
    speech_recognition.on_sdp_offer(offer, lambda a: nonlocal answer; answer = a)
    return answer

@speech_recognition.on('ice_candidate')
def on_ice_candidate(candidate):
    print('Received ICE candidate')
    speech_recognition.on_ice_candidate(candidate)

speech_recognition.start_recognition()

webrtc.connect(webrtc)

with open(sys.argv[1], 'rb') as f:
    while True:
        chunk = f.read(960)
        if not chunk:
            break
        webrtc.send_data(chunk)
        time.sleep(0.01)

webrtc.disconnect(webrtc)

pipeline.release()

UCAAS stands for Unified Communications as a Service. It is a cloud-based delivery model for enterprise communications applications, such as voice, video, messaging, and collaboration tools.

UCaaS enables businesses to access a suite of communication and collaboration tools through the internet, rather than deploying and maintaining their own hardware and software. This means that businesses can quickly and easily scale their communication capabilities up or down depending on their needs, without the need for significant capital expenditures or IT resources.

UCaaS also provides greater flexibility for remote and mobile workers, as they can access the same communication tools as in-office workers from anywhere with an internet connection. This can improve productivity and collaboration within teams, as well as with customers and partners.

Technology Landscape in UCaaS

UCaaS (Unified Communications as a Service) utilizes a variety of technologies to enable communication and collaboration. Here are some of the key technologies that are commonly used in UCaaS:

• Voice over Internet Protocol (VoIP): VoIP is a technology that enables voice calls over the internet, rather than using traditional phone lines. UCaaS providers often use VoIP to provide voice communication services to their customers.

• Session Initiation Protocol (SIP): SIP is a signaling protocol used to establish and manage communication sessions in UCaaS. It enables features such as call forwarding, conferencing, and call transfer.

• Web Real-Time Communication (WebRTC): WebRTC is a browser-based technology that allows audio and video communication to take place directly between browsers, without the need for any additional software or plugins. UCaaS providers may use WebRTC to enable browser-based video conferencing and other real-time communication features.

• Instant Messaging (IM): IM is a technology that allows users to send real-time text messages to one another. UCaaS providers may include IM as part of their collaboration tools, allowing users to chat with each other in real-time.

• Presence: Presence technology allows users to see the status of other users in real-time, indicating whether they are available, busy, or away. Presence is often used in UCaaS to enable more effective collaboration and communication between team members.

• Cloud Computing: UCaaS is delivered through the cloud, which allows users to access communication and collaboration tools from anywhere with an internet connection. Cloud computing also enables UCaaS providers to offer flexible and scalable services to their customers.

Security In UCaaS​

Security is a critical consideration for any UCaaS (Unified Communications as a Service) deployment. Here are some of the key security measures that are commonly used in UCaaS:

• Encryption: UCaaS providers often use encryption to protect communication and collaboration tools from unauthorized access. Encryption can prevent eavesdropping, data theft, and other security threats by encoding data in transit and at rest.

• Authentication: UCaaS providers often use authentication methods such as passwords, multi-factor authentication (MFA), and single sign-on (SSO) to verify the identity of users accessing communication and collaboration tools. This can help prevent unauthorized access and data breaches.

• Network Security: UCaaS providers often use network security measures such as firewalls, intrusion detection and prevention systems (IDS/IPS), and virtual private networks (VPNs) to protect against unauthorized access and other security threats.

• Data Backup and Recovery: UCaaS providers often implement backup and recovery solutions to protect against data loss due to natural disasters, hardware failures, and other unforeseen events.

• Compliance: UCaaS providers may comply with various security and privacy regulations such as HIPAA, GDPR, and PCI DSS, depending on the industry and jurisdiction. Compliance helps ensure that UCaaS providers are taking appropriate measures to protect their customers' data.

• User Education and Awareness: UCaaS providers often educate users about security best practices, such as strong passwords, avoiding phishing emails, and protecting sensitive data. This can help reduce the risk of security breaches caused by user error or negligence.

HooT as UCaaS

HooT.mx uses WebRTC (Web Real-Time Communication) to provide real-time audio and video conferencing capabilities in its web conferencing system. WebRTC is a browser-based technology that enables audio and video communication to take place directly between browsers, without the need for any additional software or plugins.

HooT.mx implements WebRTC through a variety of technologies and protocols, including:

• Signaling Server: HooT.mx uses a signaling server to facilitate communication between browsers. The signaling server is responsible for exchanging session descriptions, candidate addresses, and other metadata between browsers to establish a connection.

• TURN Server: HooT.mx uses a TURN (Traversal Using Relays around NAT) server to enable communication between browsers that are behind firewalls or NATs (Network Address Translators). The TURN server relays traffic between browsers to enable them to communicate even if they cannot connect directly.

• STUN Server: HooT.mx uses a STUN (Session Traversal Utilities for NAT) server to discover the public IP address and port of a browser. This information is necessary to establish a direct peer-to-peer connection between browsers when possible, rather than using the TURN server as an intermediary.

• WebSockets: HooT.mx uses WebSockets to enable real-time communication between browsers and the server. WebSockets provide a bidirectional communication channel between the browser and the server, allowing for real-time updates and messages to be exchanged.

Together, these technologies enable HooT.mx to provide real-time audio and video conferencing capabilities through the browser. Users can join a meeting simply by clicking a link and using their browser, without the need for any additional software or plugins.

Exploring the Architecture of HooT.mx​

The architecture of HooT.mx is designed to provide a scalable, modular, and extensible web conferencing system that can handle large online classrooms and meetings. Here are the main components of the architecture:

1. Client-side: HooT.mx's client-side architecture is based on HTML5 and JavaScript. This enables users to join a meeting using a web browser without the need for any additional software or plugins.

2. Web Server: HooT.mx's web server is built using the Play Framework, a web application framework written in Java. The web server provides the main interface for users to interact with the system, including joining meetings, creating breakout rooms, sharing content, and more.

3. Video Server: The video server is responsible for processing and distributing audio and video streams to meeting participants. It uses open source media servers such as Kurento and Jitsi to provide real-time audio and video conferencing.

4. Recording Server: HooT.mx's recording server is responsible for recording meetings and making them available for playback at a later time. It uses the open source HTML5-based player, which can play back recordings on any device that supports HTML5.

5. Database: HooT.mx's database stores all the metadata related to meetings, users, recordings, and other system components. It uses a SQL database to store this information.

6. Application Programming Interfaces (APIs): HooT.mx provides a set of APIs that enable developers to build custom applications and integrations. These APIs include the REST API, which provides programmatic access to the system's functionality, and the Events API, which enables developers to receive real-time updates on system events.

7. Plugins: HooT.mx's architecture also supports a wide range of plugins that extend the system's functionality. These plugins can be developed by the community or by third-party developers, and can be used to add features such as polling, closed captioning, and more.

Overall, the architecture of HooT.mx is designed to provide a flexible and extensible platform for online learning and collaboration. Its modular design and open APIs enable developers to build custom integrations and extend the functionality of the system as needed.

Hello World of WebRTC & VoIP​

This code creates a WebRTC Peer Connection object and adds an audio stream to it. It then creates a data channel for text chat.

When the user clicks the "call" button, the code creates a new remote Peer Connection, adds an audio stream to it, and listens for incoming text messages on the data channel. The code then exchanges SDP descriptions between the two Peer Connections to establish the VoIP communication.

The user can send text messages by typing them into the chat box and clicking the "send" button. The messages are sent over the data channel.

// Create a WebRTC Peer Connection object
const peerConnection = new RTCPeerConnection();

// Add audio stream to the Peer Connection
const localStream = await navigator.mediaDevices.getUserMedia({audio: true});
localStream.getTracks().forEach(track => peerConnection.addTrack(track, localStream));

// Create a data channel for text chat
const dataChannel = peerConnection.createDataChannel('chat', { ordered: true });

// Set up VoIP communication using WebRTC
const callButton = document.getElementById('call-button');
callButton.addEventListener('click', () => {
  const remotePeer = new RTCPeerConnection();

  // Add audio stream to the remote Peer Connection
  remotePeer.addEventListener('track', event => {
    const remoteAudio = document.getElementById('remote-audio');
    remoteAudio.srcObject = event.streams[0];
  });

  // Receive text messages through the data channel
  remotePeer.addEventListener('datachannel', event => {
    const dataChannel = event.channel;
    dataChannel.addEventListener('message', message => {
      const chatBox = document.getElementById('chat-box');
      chatBox.value += message.data;
    });
  });

  // Exchange SDP descriptions
  peerConnection.createOffer().then(offer => {
    peerConnection.setLocalDescription(offer);
    remotePeer.setRemoteDescription(offer);
    remotePeer.createAnswer().then(answer => {
      remotePeer.setLocalDescription(answer);
      peerConnection.setRemoteDescription(answer);
    });
  });
});

// Send text messages through the data channel
const chatBox = document.getElementById('chat-box');
const sendButton = document.getElementById('send-button');
sendButton.addEventListener('click', () => {
  const message = chatBox.value;
  dataChannel.send(message);
});

Kurento Media Server in more detail​

Kurento is an open-source media server that is designed to work with WebRTC (Web Real-Time Communication) to enable real-time audio and video communication in web applications. Kurento is built using Java, and it provides a variety of modules and APIs that enable developers to add advanced multimedia features to their web applications.

Here's how Kurento Media server works with WebRTC:

• Signaling: When two or more web clients want to establish a connection, they need to exchange signaling messages to negotiate the connection. Kurento provides a signaling server that can handle this process and ensure that the clients can establish a connection.

• WebRTC APIs: Kurento provides APIs for WebRTC, which enable developers to create multimedia web applications that can handle real-time audio and video communication.

• Media Processing: Kurento is designed to process media streams in real-time. It can perform a variety of operations on media streams, such as encoding, decoding, filtering, and mixing. These operations can be used to modify or enhance media streams in various ways.

• Media Pipeline: Kurento uses a media pipeline to process media streams. A media pipeline is a sequence of modules that are connected to each other. Each module performs a specific media processing task, and the output of one module is fed into the input of the next module in the pipeline.

• WebRTC Endpoints: Kurento provides WebRTC endpoints that enable clients to connect to the media pipeline. These endpoints can be used to send and receive media streams, and they can be customized to add various multimedia features to the web application.

Overall, Kurento Media server provides a powerful set of tools and APIs that enable developers to create multimedia web applications with advanced features. Its integration with WebRTC makes it an ideal choice for web applications that require real-time audio and video communication, such as video conferencing, live streaming, and online gaming.

Configuring Kurento​

Configuring Kurento Media Server for optimal performance can be a complex process, as it depends on various factors such as the hardware and network environment, the types of media streams being processed, and the specific use case of the application. However, here are some general guidelines that can help optimize the performance of Kurento Media Server:

• Hardware and Network Environment: Kurento Media Server's performance is affected by the hardware and network environment it runs on. To optimize performance, it is recommended to use a server with high CPU, RAM, and network bandwidth. Kurento Media Server should also be installed on a dedicated server to avoid resource contention with other applications.

• Use Efficient Codecs: Kurento Media Server supports a variety of audio and video codecs. To optimize performance, it is recommended to use efficient codecs that provide high quality at low bitrates. Some examples of efficient codecs are Opus for audio and VP9 for video.

• Optimize Media Pipeline: Kurento Media Server's media pipeline can be optimized for performance by reducing the number of modules used, minimizing the number of media streams being processed, and avoiding unnecessary media processing operations.

• Use Caching: Kurento Media Server provides caching mechanisms that can be used to store frequently accessed media streams in memory. This can help reduce the load on the server and improve performance.

• Load Balancing: To handle high traffic, multiple instances of Kurento Media Server can be deployed and load balanced using a load balancer. This helps distribute the load across multiple servers and ensures that each server is operating at optimal capacity.

• Monitoring and Optimization: Kurento Media Server provides various monitoring tools that can be used to monitor the performance of the system. These tools can be used to identify bottlenecks and optimize the system accordingly.

Overall, configuring Kurento Media Server for performance requires a deep understanding of the system's architecture and performance characteristics. By following the above guidelines and continuously monitoring and optimizing the system, it is possible to achieve optimal performance and provide a seamless multimedia experience to users.

Codecs supported by Kurento​

Kurento Media Server supports a wide range of codecs for audio and video streams. Here are some of the codecs supported by Kurento:

Audio Codecs:​

• Opus
• G.711
• G.722
• AAC
• MP3
• PCM

Video Codecs:​

• VP8
• VP9
• H.264
• H.265
• MPEG-4
• Theora

Kurento also supports several image and data codecs, such as JPEG, PNG, and JSON. Additionally, Kurento supports transcoding, which enables the server to convert media streams from one format to another, depending on the client's capabilities.

Sample code for using Kurento Media Server to process a video stream​

// This code creates a Kurento Media Pipeline and adds a GStreamerFilter to flip the video horizontally. Two WebRTC endpoints are then created, one for the video input and one for the output. The filter is connected between the two endpoints to process the video stream.
// The code then generates an SDP offer and sends it to a remote peer, which sends back an SDP answer. The local WebRTC endpoint then sets the SDP answer and starts sending and receiving video.


const kurentoClient = require('kurento-client');
const kurentoMediaPipeline = await kurentoClient.create('MediaPipeline');

// Create WebRTC endpoint for video input
const webRtcEndpoint = await kurentoMediaPipeline.create('WebRtcEndpoint');

// Add filter to process the video stream
const filter = await kurentoMediaPipeline.create('GStreamerFilter', { command: 'videoflip method=horizontal-flip' });
await webRtcEndpoint.connect(filter);

// Create WebRTC endpoint for video output
const webRtcEndpoint2 = await kurentoMediaPipeline.create('WebRtcEndpoint');
await filter.connect(webRtcEndpoint2);

// Start processing the video stream
await webRtcEndpoint.gatherCandidates();
await webRtcEndpoint2.gatherCandidates();

// Offer the SDP description to the remote peer
const offer = await webRtcEndpoint.generateOffer();
// Send the offer to the remote peer and receive the answer
const answer = await remotePeer.processOffer(offer.sdp);
// Set the SDP answer on the local WebRTC endpoint
await webRtcEndpoint2.processAnswer(answer.sdp);

// Start sending and receiving video
await webRtcEndpoint2.connect(webRtcEndpoint);
await webRtcEndpoint.connect(webRtcEndpoint2);