Load balancing is a critical technique in computing and networking that involves distributing workloads across multiple computing resources, such as servers, network links, or other infrastructure components. The primary goal of load balancing is to optimize resource use, maximize throughput, minimize response time, and avoid overloading any single resource[1][3][4][5][8][9][13][15].
Key Functions and Benefits
Efficiency and Performance Optimization: Load balancing helps to ensure that no single server bears too much demand. By spreading the load evenly, it enhances the overall performance of the system and speeds up the response time for users[1][3][4][5][8][9][13][15].
High Availability and Fault Tolerance: It increases the availability of applications and websites by redistributing the load to other servers in case one fails. This redundancy helps to maintain service continuity and reduces the risk of downtime[1][3][4][5][8][9][13][15].
Scalability: Load balancing facilitates easy scaling of applications by allowing additional servers to be added or removed dynamically based on the demand without disrupting the service[1][3][4][5][8][9][13][15].
Types of Load Balancing Algorithms
Load balancing algorithms can be broadly classified into two categories: static and dynamic[1][2][3][4][5][6][7][8][9][11][13][14][15].
Static Load Balancing: This method does not consider the current state of the network or the servers. It might use simple algorithms like Round Robin, where requests are distributed sequentially among the servers[2][6][7][11][14].
Dynamic Load Balancing: This approach considers the current state of the network or the servers to make intelligent decisions about distributing the load. Examples include the Least Connections algorithm, which routes traffic to the server with the fewest ...
