Load-balancing and high-availability sub system used for distribution-type system and method

Abstract

The invention provides a load-balancing and high-availability sub system used for a distribution-type system and a method. The sub system comprises at least two service supplier modules, a registration center module and at least one client module. The service supplier modules calculate values of servicing rights of the service supplier modules, register services and the values of the servicing rights in the registration center module and calculate probability distribution of service suppliers of the services. The registration center module carries out a uniform naming service in the structure of a naming tree on the services registered by the service supplier modules and stores a service supplier list corresponding to each service and probability distribution of each corresponding service supplier. The client module obtains the corresponding service supplier list and the probability distribution of the corresponding service supplier according to the service name to be obtained and selects a service supplier randomly through a load-balancing algorithm. If the service supplier is available, a service module is directly called; if the service supplier is unavailable, another available service supplier is selected through a high-availability algorithm.

Description

technical field [0001] The invention relates to the field of distributed systems, in particular to a load balancing and high availability subsystem and method for distributed systems. Background technique [0002] In most distributed systems, a large number of users access a certain resource concurrently. At this time, if the resource is concentrated on one server, it is obvious that this server will be under tremendous pressure. In this case, the CPU, memory, and I / O system of this server will soon reach the upper limit of performance, and eventually become the performance bottleneck of the system. Since a single server always has a performance upper limit no matter how its hardware configuration is improved, if the concurrent user scale continues to expand, a single server obviously cannot meet the ever-expanding concurrent scale. Only by adopting the server cluster method can the cluster scale be dynamically adjusted according to the concurrent scale effectively, and fin...

AI Technical Summary

Problems solved by technology

First of all, the schedule table is in the central control system, which means that the central control system needs to coordinate the execution of each client request; secondly, coordinating each client request consumes the resources of the central control system, which may lead to the emergence of bottlenecks; finally, When a server goes down or a new server is added, the schedule needs to consider the previous schedule to regenerate the schedule

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