Load balancing method and device based on source IP address

Abstract

The invention discloses a load balancing method and a load balancing device based on a source IP address. The method comprises the steps of searching for the longest mask matching in a routing table by using the source ip address of a message, and acquiring a load balancing factor corresponding to the source ip address from the routing table; and selecting a corresponding member outlet used for forwarding the message according to the load balancing factor. The scheme of the method provided by the invention is simple in implement, and achieves planning and dynamic adjustment of load balancing by using the longest mask matching algorithm of the routing table of existing network equipment, with no need for very complex hardware design and lots of memory.

Description

technical field [0001] The present invention relates to a load balancing technology, in particular to a method and device for load balancing based on a source IP address. Background technique [0002] Load balancing is a very important application in network planning, which can achieve the purpose of expanding bandwidth and link protection at the same time. At present, the commonly used load balancing methods mainly include the following two schemes. Scheme 1 uses a hash (hash) algorithm based on the fixed field of the received message, and then selects the final exit according to the hash value and the number of members of the load balancing group. Solution 2, based on the current load state of the members of the load balancing group, select the lightest link to fully utilize the bandwidth. [0003] However, both of the above two schemes have certain defects: scheme 1 is based on fixed fields, and the Hash algorithm is generally CRC (cyclic redundancy check) or XOR algorit...

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Problems solved by technology

[0003] However, both of the above two schemes have certain defects: scheme 1 is based on fixed fields, and the Hash algorithm is generally CRC (cyclic redundancy check) or XOR algorithm, so it is impossible to plan the state of load balancing, and the final actual load balancing The effect may not be ideal

However, the implementation of this solution is relatively complicated, and it needs to record a large number of flow states, which consumes a lot of memory; at the same time, the selection of the path is completely based on the current load, and it is impossible to do pre-planning

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