Abstract

Considering the dynamic nature of new generation scientific problems, load balancing is a necessity to manage the load in an efficient manner. Load balancing systems are use to optimize the resource consumption, maximize the throughput, minimize response time, and to prevent overload in resources. In current research, we consider operational distributed systems with dynamic variables caused by different nature of the applications and heterogeneity of the various levels in the system. Conducted studies indicate that many different factors should be considered to select the load balancing algorithm, including the processing power, load transfer and communication delay of nodes. In this work, We aim to design a dashboard that is capable to merge the load balancing algorithms in different environments. We design an adaptive system infrastructure with the ability to adjust various factors in the run time of a load balancing algorithm. We propose a task and a resource allocation mechanism and further introduce a mathematical model of load balancing process in the system. We calculate a normalized hardware score that determines the maturity of system according to the environmental conditions of the load balancing process. Evaluation results confirm that the proposed method performs well and reduces the probability of system failure.

Highlights

  • In the next-generation high performance computing (HPC) systems, the scientific programs are going to get more complex with unpredictable requests what requires large scale and more powerful computing systems [3]

  • In distributed computing systems with mission of high performance computing, the main concern of managing resources is reaching to minimum execution time and maximum throughput in running scientific/industrial programs [10]

  • It is assumed that, according to the settings outlined, the load balancing process is started in the system, using both dynamic and predetermined formulas

Read more

Summary

Introduction

In the next-generation high performance computing (HPC) systems, the scientific programs are going to get more complex with unpredictable requests what requires large scale and more powerful computing systems [3]. DCS consists of a group of computers, each of which has an independent operating system and all are connected through a network [12]. This definition of distributed computing systems is very general and covers all types of purposes for user resource connectivity. In distributed computing systems with mission of high performance computing, the main concern of managing resources is reaching to minimum execution time and maximum throughput in running scientific/industrial programs [10]

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.