Difference Between Latency and Throughput
Last Updated :
16 Sep, 2024
Difference Between Latency and Throughput: In a computer network computers are connected using different types of devices like routers switches, etc that form the network. One of the most fundamental concepts in computer networking is to test the connectivity between two computers, here is where different measures to evaluate the performance of the network come into play.
Latency is the measure of the delay users encounter when sending or receiving data over a network. Throughput, on the other hand, determines the network's capacity to accommodate multiple users simultaneously, indicating how many users can access the network concurrently.
Latency and Throughput are two of the most important network performance evaluation measures. In this article, we have provided everything about what is latency, what is throughput, the difference between latency and throughput, and the similarities between latency and throughput.
What is Latency in Networking?
Latency in networking refers to the time delay or lag that exists between a request and the response to that request, in simple words it is the time taken by a single data packet to travel from the source computer to the destination computer.
How Latency is measured?
It is measured in milliseconds (ms), Latency is considered an important measure of performance when dealing with real-time systems like online meets, online video games, etc. High latency could lead to a bad user experience due to delay and data loss. To measure latency in real-time tools like ping tests are used.
What is Throughput in Networking?
Throughput on the other hand refers to the amount of data that can be transferred over a network in a given period. Some may confuse it with Bandwidth as they are almost the same with just a single difference bandwidth refers to the theoretical value of the data rate through a network while throughput refers to the real data rates observed, for example for a 100 Mbps connection the bandwidth is 100 megabits a second (Mbps) but the throughput may defer due to various factors.
How Throughput is measured?
It is measured in bits per second (bps) but in practice, it is mostly measured in megabits per second (Mbps). It is measured using tools like network traffic generators or by simulating a data transfer through the network and by measuring the rate at which the data is transmitted as the throughput.
Bandwidth in Computer Networks
In the context of a computer network `Bandwidth` is one of the fundamental concepts that refers to the capacity of the network to transfer data from one machine or node to another. In simple terms, bandwidth is the maximum available data transfer limit of a computer network for e.g. network connection offered by an ISP generally offers a fixed bandwidth like 100 mbps (megabits per second) which means you have a network connection using which you can transfer a maximum of 100 megabits of data per second (upload or download).
But the actual capacity of the network may defer depending on various factors like network traffic, latency etc so the throughput received may be less or more than the assigned bandwidth value. Bandwidth is measured in mbps (megabits a second) referring to the amount of data in mega bits that can be transferred over a network in 1 second of time.
Difference Between Latency and Throughput
Now that we have a good understanding of both these terms we can move to the difference between them,
Aspects | Latency | Throughput |
Definition | The time delay between a request and a response. | Amount of data that can be transferred in a period of time. |
Measuring Unit | Millisecond (ms). | bits per second (bps), Megabits per second (Mbps). |
Represents | How quickly a single request is processed. | How much data is been transferred over a network in a period of time. |
Affecting Factors | Network distance, congestion, processing delays. | Network bandwidth, congestion, packet loss, topology. |
impact on performance | High latency can lead to a slow and interrupted network experience. | Low throughput can lead to slow and inefficient data transfer. |
Measures | Latency is a measure of time. | Throughput is a measure of data transfer. |
Importance | Critical for real-time applications like an online meet app. | Important for data-intensive applications like file transfer apps. |
Example | The time it takes for a website to load. | The amount of data that can be downloaded per second. |
Relationship between Bandwidth, Latency, and Throughput
Now that we have a decent understanding of these networking terms bandwidth, latency, and throughput, how they play a vital role when optimizing a computer network, and how these concepts help to determine the performance and efficiency of the network for data transmission. let's discuss the relationship between these concepts.
Though latency and bandwidth are not directly related which means changing bandwidth will not affect latency much for e.g. increasing bandwidth does not guarantee low latency. In the case of throughput and bandwidth, throughput is highly affected by bandwidth as throughput is the actual data transfer rate observed on a network increasing the bandwidth will directly increase the throughput of the network.
In the case of throughput and latency, they have an inverse relationship so if the latency of a network is high the throughput will accordingly decrease as due to high latency it will increase the time for data to traverse the network which will reduce the data transfer rate.
In simple terms, bandwidth, latency, and throughput are related to each other where bandwidth determines the network data transfer capacity, latency represents the time delay in data transfer, and throughput is the actual transfer speed observed in a computer network.
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Conclusion - Latency vs Throughput
Understanding the distinction between latency and throughput is crucial for evaluating the performance of systems, networks, and applications. Latency directly impacts user experience, while throughput reflects the system's ability to handle high data loads. Balancing both metrics is essential to ensure efficient, responsive, and scalable systems in various domains, such as gaming, cloud computing, and real-time applications.
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