METHOD OF THE SERVER HORIZONTAL LOAD BALANCING FOR REDUCING ENERGY CONSUMPTION
DOI:
https://doi.org/10.20535/2411-2976.12024.39-49Keywords:
Telecommunication services, cloud environment, resource management, load balancing, dynamic method, GPSS, application processing, energy efficiencyAbstract
Background. Server horizontal load balancing is a crucial aspect of modern computing systems, particularly in cloud computing environments. The efficient management of incoming flows of applications is essential to ensure optimal resource utilization and minimize energy consumption. This study focuses on developing a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing.
Objective. The primary objective is to develop a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing. This involves identifying the maximum permissible number of applications that can simultaneously enter the system for service, ensuring that the volume of resources used is close to the total maximum possible amount of resources. The method aims to minimize the variance of the elements of the sequence of maximum allowable numbers of applications and the dispersion of the elements of the sequences of volumes of resources used.
Methods. The method involves several key steps:
Input Load Smoothing Scheme: A static control method is proposed to smooth the incoming load. This involves developing a scheme for smoothing the incoming load, which is a set of values of the maximum allowable number of requests (sequence {ki}) arriving at the system input for a small time interval ∆ti. The sequence is selected to ensure that the volume of resources used is close to the total maximum possible amount of resources.
Genetic Algorithm: The selection of the sequence {ki} is carried out using a genetic algorithm. The algorithm involves crossover, mutation, and selection operations to minimize the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used.
Resource Allocation: The method involves allocating resources for the maintenance of a given type of service. The parameters of the server, which are characterized as the resources of the system serving the applications, are usually calculated for the average values of the parameters of the input stream.
Delay Introduction: To manage the application processing process and prevent resource shortages, a delay is introduced for a part of the applications that coincide with a surge in load. The delay time is determined so that delayed applications do not enter the system until the previous burst of load is successfully serviced in the resource-consuming functional block.
Results. The results of the study include the development of a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing. The method involves the use of a genetic algorithm to select the sequence {ki} that minimizes the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used.
Conclusions. The study concludes that the proposed method for managing the incoming flow of applications can effectively reduce energy consumption in server horizontal load balancing. The method involves the use of a genetic algorithm to select the sequence {ki} that ensures efficient use of system resources and minimizes the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used. The method can be applied in various scenarios where efficient use of system resources is crucial, such as in cloud computing environments.
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