A method and system for realizing network dynamic load balancing

Abstract

The embodiment of the present invention discloses a method and system for implementing network dynamic load balancing. The method includes: dividing a large-scale distributed system network into several local areas, and initializing the network topology population in the local area; Construct a multi-objective function according to multiple constraints in the local area, calculate the individual fitness of the individual in the population according to the multi-objective function, and select an individual with a higher fitness as the parent; perform a genetic operator on the parent , form offspring; Substitute the offspring into the multi-objective function to calculate its regret value, and judge whether the regret value of the offspring is less than the regret value of the parent generation; when the judgment result is yes, then use the The offspring replace the parent to form a new population; when the judgment result is no, the offspring are discarded. The system of the present invention can be used to implement the method. The technical scheme of the invention adopts a distributed strategy, the algorithm is simple, and has good adaptability.

Description

Technical field [0001] The present invention relates to the Internet field, in particular to a method and system for realizing network dynamic load balancing. Background technique [0002] With the rapid development of computer and network technology, the application of large-scale distributed systems is becoming more and more extensive, such as network streaming media on-demand, multi-party online games, distance education, online medical care, etc., all belong to large-scale distributed systems. Due to the large number of users and scattered locations, large distributed systems are prone to problems such as slow system operation and low efficiency when faced with large system access and complex business processing requirements, resulting in unbalanced network load. At present, the general method to solve the problem of low operating efficiency of large-scale distributed systems is to continuously improve the performance of the network server according to actual needs. However,...

AI Technical Summary

Problems solved by technology

Its advantage is that it does not need to increase the operating cost of the system. The disadvantage is that its algorithm complexity is high, there is a defect of single point failure, and it cannot be applied to a dynamic and real-time environment, and its adaptability is poor.

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