Method and system for realizing dynamic load balancing in distributed network

Abstract

The invention provides a dynamic load balance achieving method and system in a distributed network. The dynamic load balance achieving method comprises the steps of confirming a node average load calculation value of the distributed network, comparing the node average load calculation value with a lower limit threshold value and an upper limit threshold value respectively, setting at least one node in the distributed network to be in a dormant state when the node average load calculation value is smaller than the lower limit threshold value, and awakening at least one dormant node in the distributed network when the node average load calculation value is larger than the upper limit threshold value. The dynamic load balance achieving method and system enables a part of nodes when the network load is low and awakens the part of nodes when the network load is high, well achieves load balance among network nodes, meanwhile improves the energy consumption efficiency of the distributed network and reduces the energy consumption of a network system.

Description

technical field [0001] The invention relates to network communication technology, in particular to a method and system for realizing dynamic load balancing in a distributed network. Background technique [0002] With the continuous development of cloud computing technology, the scale of cloud computing data centers is getting larger and larger, and the density of physical servers in data centers is also increasing. Traditional data processing and analysis methods are limited by the CPU and memory of a single machine, and they will encounter bottlenecks when performing massive calculations. In this case, many new distributed network technologies have been born and widely used, such as Hadoop and so on. Hadoop is a software framework capable of distributed processing of large amounts of data, which greatly facilitates programmers to run their programs on distributed network systems without distributed parallel programming. [0003] At the same time as the birth of new techno...

AI Technical Summary

Problems solved by technology

A team at Stanford University believes that there is a lot of room for improvement in terms of energy saving in distributed networks, and proposes to adopt a new algorithm for node data; the University of California, Berkeley established a model based on nodes, working hours, and power, and believes that this model can Achieved better results; Swiss scientists modified the block allocation algorithm of the distributed network, thereby reducing the energy consumption of the distributed network; in addition, dynamic voltage adjustment is also widely used by researchers to reduce network energy consumption, but the disadvantage is that it requires special hardware environment

[0004] At the same time, people began to realize that optimizing energy consumption efficiency and optimizing load performance have the same value. It is not enough to simply emphasize load balancing or simply emphasize energy saving without taking into account the overall performance of the system.

However, there is still a lack of technology that can take into account both dynamic load balancing and energy saving in the application of distributed networks in the existing technology

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