System and method for decentralized scheduling of autonomous flow engine load balancing clusters

A process engine and load balancing technology, which is applied in the field of cluster computing in the field of information technology, can solve problems such as single point of failure, long response time, and single-port performance bottlenecks, and achieve the effects of saving investment costs, fast request response, and good customer experience

Active Publication Date: 2012-03-28
京北方信息技术股份有限公司
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Problems solved by technology

[0007] The server side of the present invention does not set up a general scheduler, but adopts a multi-layer autonomous structure and a decentralized scheduling mode. Specifically, the server side includes several cluster node groups, each cluster n

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  • System and method for decentralized scheduling of autonomous flow engine load balancing clusters
  • System and method for decentralized scheduling of autonomous flow engine load balancing clusters
  • System and method for decentralized scheduling of autonomous flow engine load balancing clusters

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Embodiment Construction

[0056] The decentralized scheduling autonomous load balancing cluster system structure of the present invention is as follows: figure 1 As shown, the system is divided into N cluster node groups, each cluster node group is arranged with M cluster nodes, each node corresponds to a server computer, K engines are started on each cluster node, and each engine corresponds to an independent thread , the number of engines on nodes in different node groups can be different, but the number of engines on different nodes in the same node group must be the same, and the serial numbers of engines between node groups must be continuous. figure 1 The dashed arrows in indicate a synchronous call. The system is provided with a rotator at the client side.

[0057] N cluster node groups represent N engine line program number segments, and each cluster node group is responsible for calculating the cluster task request of the segment it belongs to. For example, the first group is responsible for...

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Abstract

The invention discloses a system and a method for decentralized scheduling of autonomous flow engine load balancing clusters and belongs to the technology of cluster computing in the technical field of information. In the system and the method, multilayer clustering is performed on a server flow engine, the server flow engine is divided into a plurality of cluster node groups, each cluster node group is divided into a plurality of cluster nodes, and each cluster node is subdivided into a plurality of flow engines; and different cluster node groups carry out autonomy, a total scheduler is cancelled, and the cluster nodes in the same cluster node group are mutually spared by adopting a heartbeat detection method. The conventional total scheduling function is transferred from a server system and is scattered into a client system, and the client system calculates a requested service provider by adopting a rotation method according to a flow engine list so as to reduce the scheduling pressure of a server. According to the system and the method, the problems of single-port bottlenecks and single-point failure of the conventional load balancing clusters are effectively solved through the decentralized scheduling, and the response speed and processing capacity of the clusters are improved.

Description

technical field [0001] The invention relates to a process engine load balancing cluster system and method, and belongs to the cluster computing field in the field of information technology. Background technique [0002] High-performance cluster is the key technology of large-scale concurrent information system, which directly affects the availability of large-scale information system. In particular, the process engine of the workflow management system needs a cluster system with fast response and strong scalability. A traditional load balancing cluster system generally has a general scheduler, and the general scheduler is responsible for allocating requests from external systems to each processing unit. [0003] This clustering approach has the following deficiencies: [0004] 1) The client call is first passed to the general scheduler of the cluster system, and then the general scheduler of the cluster system forwards the request to the corresponding cluster node accordin...

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Application Information

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IPC IPC(8): H04L12/56H04L29/08H04L12/803
Inventor 孙刚高昊江
Owner 京北方信息技术股份有限公司
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