What is load balancing and how does it relate to cloud computing? Well, before I will answer that question, I want to define what load balancing is first and foremost. Load balancing is just a method which allows you to strike the right balance of the amount of work that is being ‘loaded’ on various pieces of hardware and equipment.
You could think of this as workers that are given the same amount of load to make things more efficient and so that they would not be depleted of energy, time, and resources since everything well-balanced.
So, I want to go back to my previous question: how does this relate to cloud computing? Read through the rest of the article to find the answer that you seek.

Different Types

There are actually many different types of load balancing algorithms being used in cloud computing. They are:

  • Dynamic Algorithm

In this algorithm, the program will search for the server with the lightest load and will try to balance the load of other servers by putting some on the new server. This is all done in real-time and using this algorithm will ensure smooth operation across the board.

  • Static Algorithm

In static load balancing algorithms, the work is divided equally to all servers by default. However, one major downside to this is that the load balancing algorithm will only start balancing the tasks when a new one is created.

  • Round Robin Algorithm

This is arguably the easier load balancing algorithm out there. Basically, the algorithm will find a random node and would then start assigning the load on a round-robin basis. This would result in a much faster response with the downside that there are some nodes that are given the bulk of the task while others are still left under-utilized.

  • Weighted Round Robin Algorithm

To solve the huge limitation of the round-robin algorithm, this algorithm works by assigning different nodes some weights and will be given tasks based on the weight threshold it can carry.
Although this doesn’t entirely solve the problem of the traditional round-robin style, it still does a pretty good job of dividing the weight of the tasks as they are created.

  • Opportunistic

This algorithm makes sure that every node is being utilized no matter the weight of the task is at hand. The tasks will be assigned randomly but the idea is that all of the nodes will be used.

  • Minimum to Minimum

This algorithm is best suited for smaller tasks. Basically, the machine would give the load to all of the nodes regardless of the weight of the tasks. It assigns a minimum value and will be given to a specific node for completion.

  • Maximum to Minimum

This algorithm is the same as the one above but the bigger load takes precedence over the minimum loads.

Conclusion

So, how do these all relate to cloud computing? Such algorithms will ensure that every node is being utilized by giving certain weighted loads for them to complete. This makes cloud computing so efficient and cost-effective.

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