Congestion Control In Computer Networks

Last Updated on August 9, 2023 by Mayank Dham

In the ever-expanding digital landscape, computer networks serve as the intricate web that connects individuals, businesses, and nations across the globe. The relentless growth in data consumption and the emergence of cutting-edge technologies have intensified the demand for seamless and efficient network communication. However, with this exponential increase in data traffic comes the inevitable challenge of congestion.

Congestion, a phenomenon akin to traffic congestion on busy city streets, occurs when network resources are strained beyond their capacity, resulting in data packet delays, increased latency, and degraded network performance. Left unaddressed, congestion can lead to service disruptions, financial losses, and even critical data loss. Thus, the need for robust congestion control mechanisms has never been more crucial.

What is Congestion Control in Computer Networks?

Congestion control in computer networks refers to the set of techniques, mechanisms, and protocols designed to manage and regulate the flow of data traffic within a network to prevent congestion. It is a vital aspect of network management, aimed at ensuring the efficient and reliable transfer of data while avoiding the degradation of network performance due to overload.

When the demand for network resources exceeds its capacity, congestion occurs. Similar to traffic congestion on busy roads, network congestion leads to delays, increased latency, packet loss, and reduced throughput. This can severely impact the overall user experience, hinder critical applications, and result in a loss of productivity and revenue for businesses.

The primary goal of congestion control is to balance the usage of available network resources, preventing any single component from becoming overwhelmed. It achieves this by actively monitoring network conditions, detecting congestion indicators, and taking appropriate actions to alleviate congestion or prevent it from occurring in the first place.

Effects of Congestion Control in Computer Networks

Here are some of the key effects of congestion control:

• Improved Network Stability: Congestion control prevents network resources from becoming overwhelmed, which helps maintain network stability. By regulating the flow of data and ensuring that the network operates within its capacity limits, congestion control reduces the likelihood of network failures or crashes due to congestion-related issues.

• Reduced Latency and Packet Loss: Congestion can lead to increased latency, causing delays in data transmission. With congestion control mechanisms in place, the network can better manage data traffic, leading to reduced latency and minimizing packet loss. This results in faster data transfers and a more responsive network.

• Enhanced Throughput: By preventing congestion, congestion control allows for the optimal utilization of network resources. This leads to improved throughput, allowing more data to be transmitted in a given time, which is crucial for handling large data volumes and supporting high-bandwidth applications.

• Fairness in Resource Allocation: Congestion control algorithms, such as TCP, are designed to allocate network resources fairly among different flows or connections. This ensures that no single application or user dominates the available resources, promoting a balanced distribution of bandwidth.

• Better User Experience: Smooth data flow and reduced latency translate to an enhanced user experience. With congestion control in place, users can access online services, websites, and applications more reliably and without frustrating delays.

• Mitigation of Network Congestion Collapse: In the absence of congestion control, network congestion can snowball into a phenomenon known as "congestion collapse." This occurs when a sudden surge in data traffic overwhelms the network, leading to widespread congestion and rendering the network almost unusable. Effective congestion control helps prevent such catastrophic scenarios.

Congestion Control Algorithms

A system called congestion control regulates the flow of data packets into the network, allowing for more efficient use of a shared network infrastructure and preventing congestive collapse. Congestive-Avoidance Algorithms (CAA) are used as a technique to prevent congestive collapse in a network at the TCP layer. The following are two congestion control algorithms:

Leaky Bucket Algorithm

• The leaky bucket method finds applications for shaping or rate-limiting network traffic.
• For traffic shaping algorithms, a token bucket execution and a leaky bucket execution are typically utilized.
• With the help of this method, the network’s transmission rate may be managed, and burst traffic can be turned into a constant stream.
• When compared to the leaky-bucket algorithm, the drawbacks include the ineffective utilization of available network resources.
• The bandwidth and other extensive network resources are not being utilized efficiently.

To further understand, let’s look at an example.

Think of a bucket that has a tiny hole in the bottom. No matter how quickly water enters the bucket, the pace at which it exits remains constant. Water that is added after the bucket is full flows over the edges and is lost.

Similar to this, each network interface has a leaky bucket, and the leaky bucket method involves the following steps:

• Packets are dropped into the bucket when the host wants to send them.
• The network interface broadcasts packets at a consistent pace because the bucket leaks at a constant rate.
• The leaky bucket converts chaotic traffic into regular traffic.
• The bucket actually functions as a finite queue with a finite rate of output.

Token bucket Algorithm

• The output architecture of the leaky bucket method is stiff at an average rate irrespective of the bursty traffic.
• When there are significant bursts, certain applications allow the output to accelerate. This needs a more adaptable algorithm, ideally one that never loses data. A token bucket approach is thus useful for rate-limiting or filtering network traffic.
• It is a control algorithm that suggests the best times to send traffic. Based on how many tokens are visible in the bucket, this ranking is generated.
• Tokens are in the bucket. Each token designates a packet of a specific size. To allow sharing of a packet, tokens in the bucket are erased.
• When tokens are displayed, a flow of transmit traffic also does so.
• If there is no token, no flow will send packets. As a result, a flow transfers traffic in good tokens in the bucket up to its peak burst rate.

Need of token bucket Algorithm:-

The leaky bucket algorithm enforces output pattern at the average rate, no matter how bursty the traffic is. So in order to deal with the bursty traffic we need a flexible algorithm so that the data is not lost. One such algorithm is the token bucket algorithm.

Steps of this algorithm can be described as follows:

• In regular intervals tokens are thrown into the bucket.
• The bucket has a maximum capacity.
• If there is a ready packet, a token is removed from the bucket, and the packet is sent.
• If there is no token in the bucket, the packet cannot be sent.

Conclusion
In the dynamic world of computer networks, congestion control emerges as a paramount aspect that ensures the smooth, reliable, and efficient flow of data traffic. From the early days of TCP’s pioneering congestion control algorithms to the modern-day intelligent adaptive mechanisms, the pursuit of optimal network performance has remained a constant endeavor. The article has provided a comprehensive exploration of congestion control in computer networks, delving into its significance, underlying principles, and various algorithms employed to mitigate congestion.

As networks continue to evolve and accommodate ever-increasing data demands, the role of congestion control becomes even more critical. The impact of congestion can be far-reaching, affecting businesses, consumers, and even critical infrastructure. By implementing robust congestion control mechanisms, network administrators can foster a network environment that thrives on stability, fairness, and seamless data transfer.

FAQs (Frequently Asked Questions) on congestion control in computer networks:

Here are some FAQs on congestion control in computer networks.

1. Why is congestion control important in computer networks?
Congestion control is vital in computer networks to prevent network overload, reduce latency, and avoid data packet loss. It ensures fair resource allocation, prevents network instability, and enables a better user experience for various applications and users sharing the same network.

2. How does TCP congestion control work?
TCP employs a combination of slow start, congestion avoidance, and fast retransmit mechanisms to manage data flow. It dynamically adjusts the transmission rate based on network feedback to avoid congestion and achieve efficient data transfer.

3. What are some common congestion control algorithms besides TCP?
Apart from TCP, there are other congestion control algorithms such as Explicit Congestion Notification (ECN), Stream Control Transmission Protocol (SCTP), and Data Center TCP (DCTCP), each designed to address specific network scenarios and requirements.

4. How do AI and machine learning enhance congestion control?
Artificial intelligence and machine learning algorithms enable networks to learn from historical data and adapt to varying traffic patterns. They can predict congestion, optimize transmission rates, and dynamically adjust congestion control parameters to improve overall network efficiency.

5. How does congestion control impact real-time applications?
Congestion control is crucial for real-time applications like video conferencing and online gaming, which require low latency and minimal packet loss. Effective congestion control ensures that these applications function smoothly and deliver a seamless user experience.

6. Can congestion control be applied to wireless networks?
Yes, congestion control is equally important in wireless networks to manage limited bandwidth and avoid data collisions. Algorithms like the Leaky Bucket Algorithm and variants of TCP are adapted to suit the specific challenges of wireless environments.