Ant colony optimization algorithm-based SBS (service-based software system) resource allocation method in cloud environment

Abstract

The invention relates to an ant colony optimization algorithm-based SBS (service-based software system) resource allocation method in a cloud environment. The method comprises the following steps of at first, acquiring a resource candidate resource allocation set of each component service in an SBS, acquiring a mapping relation between any resource attribute vector and component service average response time thereof, building a search map of SBS resource allocation application, and adjusting the resource candidate resource allocation set of each component service in the SBS by using a colony optimization algorithm to obtain the optimal combined resource allocation; finally, performing resource allocation on the SBS according to the optimal combined resource allocation. By the SBS resource allocation method, the resource using cost can be minimized under the condition that the allocation satisfies an SLA (service level agreement) constraint, so that the profit of a service provider is increased; when the scale of the SBS resource allocation is relatively large, the combined resource allocation approximate to optimal allocation can be guaranteed obtained by the method within relatively short time.

Description

technical field [0001] The invention belongs to the field of service-based software systems (SBS), and in particular relates to an SBS resource configuration method in a cloud environment based on an ant colony optimization algorithm. Background technique [0002] With the proliferation of cloud computing and the concept of "software as a service", service-based software systems (Service-Based Software systems, SBS) in the cloud environment have become a research hotspot at home and abroad. The elastic resource allocation feature of cloud computing enables enterprises and organizations to allocate virtualized resources according to actual business needs when deploying applications, thereby reducing resource waste. In business requirements, different quality of service attributes, such as response time, reliability, and throughput, are usually described through a service level agreement (SLA) between an application provider and an application user. Therefore, when deploying ...

AI Technical Summary

Problems solved by technology

The initial deployment is the prerequisite for the stable operation of the SBS system. The initial resource configuration is the main task in the initial deployment stage. At present, it is basically manually configured by the system deployment personnel. In practice, there are often a large number of combinations of service resource allocation strategies, and manual configuration is used. It is difficult to find an optimized deployment strategy from it, resulting in a waste of resources and reducing the service provider's revenue

However, a few automatic configuration methods, such as component replication or migration and SLA decomposition, have their limitations.

Due to the complexity of replica selection and replica deployment, the method of component replication or migration is more suitable for real-time resource scheduling in a dynamic environment, but it still has certain limitations when there are a large number of resource allocation combinations in a static environment; while the SLA decomposition method only Limited to applications composed of multi-layer linear logic structures, for SBS applications composed of multiple component services based on different business logics, it is difficult to determine the performance requirements of each component service according to the performance goals of the application in practice

It can be seen that the existing research work on initial resource deployment is less and has certain limitations.

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