Fine-grained network traffic scheduling method and system under network function virtualization

Abstract

The invention discloses a fine-grained network traffic scheduling method and system under network function virtualization and belongs to the field of network function virtualization. The scheduling method is a distributed method. Each network node can carry out network traffic scheduling after each network node acquires partial network state information. Specifically, according to the method, different control policies are carried out at each moment according to current states of each network node and links, and data packet queue information of different network traffic. The control policies comprise an access control policy, a processing control policy and a transmission control policy. The data packet queue information is updated according to results of the policies. The scheduling system is responsible for maintaining queues, collecting network state information and acquiring a scheduling result through utilization of the scheduling method according to the information. Network functions are used for performing specific tasks according to the scheduling result. According to the scheduling method and the system, the network traffic is dynamically scheduled according to the currentnetwork states, a whole network system is guaranteed to be in a stable state, and the total average throughput is optimized.

Description

technical field [0001] The invention belongs to the field of network function virtualization, and more specifically relates to a fine-grained network flow scheduling method and system in a network function virtualization environment. Background technique [0002] Traditional network equipment based on proprietary hardware is expensive, difficult to manage, poor in flexibility, and takes a long time to deploy services. It is increasingly unable to adapt to the rapid development of network requirements. Network function virtualization is to deploy network functions to general-purpose servers in the form of software through virtualization technology, so as to reduce costs, improve flexibility, facilitate management, and shorten service deployment time. Network functions usually form services in the form of service chains. A service chain defines multiple network functions that network flows need to pass through in sequence. The network flow needs to start from the source node,...

AI Technical Summary

Problems solved by technology

First of all, most network flow scheduling methods are coarse-grained static scheduling, which is based on the average flow of network flow over a period of time. This kind of static scheduling can only be applied when the network flow is relatively stable. If it is large, the performance of the network system cannot be guaranteed to be optimal, and it may even cause congestion of a certain node on the network.

Secondly, many network flow scheduling methods are a centralized method that needs to know the global network status (such as node and link status) to schedule, so a centralized control node is required to collect the status of each network node and link information, which increases the complexity of the implementation and causes unnecessary communication overhead

In addition, some network flow scheduling methods lack access control means and cannot be applied to situations where the network flow exceeds the capacity of the network system

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