scholarly journals Dynamic Load Balancing Policy in Grid Computing with Multi-Agent System Integration

Author(s):  
Bakri Yahaya ◽  
Rohaya Latip ◽  
Mohamed Othman ◽  
Azizol Abdullah
2002 ◽  
Vol 1 (2) ◽  
pp. 208-224 ◽  
Author(s):  
Frances M.T. Brazier ◽  
Frank Cornelissen ◽  
Rune Gustavsson ◽  
Catholijn M. Jonker ◽  
Olle Lindeberg ◽  
...  

2017 ◽  
Vol 7 (1) ◽  
pp. 485-490 ◽  
Author(s):  
M.N. Satymbekov ◽  
I.T. Pak ◽  
L. Naizabayeva ◽  
Ch.A. Nurzhanov

AbstractIn this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.


2008 ◽  
Vol 6 (3) ◽  
pp. 239-253 ◽  
Author(s):  
Qin Zheng ◽  
Chen-Khong Tham ◽  
Bharadwaj Veeravalli

2019 ◽  
Vol 4 (2) ◽  
pp. 63-70
Author(s):  
Dyah Ayu Wiranti ◽  
Kurnia Siwi Kinasih ◽  
Shinta Rizki Firdina Sugiono

In this modern era, the technology is growing rapidly, the Internet is misled. This condition will be related to the service provider or commonly referred to as a server. Increasing the number of clients, the server also has to work heavier so that it often occurs overload. The Load Balancing mechanism uses the Least Time First Byte and Multi Agent system methods. This mechanism allows the server to overcome the number of users who perform service requests so that the load from the server can be resolved. This solution is considered efficient and effective because the request process on the information system will be shared evenly on multiple server back ends. The results of the research that can be proved if using this mechanism the server can work well when the request is from a user or client dating, this method successfully distributes the balancer evenly through the server backend. So the server is no longer experiencing overload. This can be proved when a system that has used the load balancing method with 300 connections generates a throughput of 123.1 KB/s as well as response time value of 4.72 MS and a system that does not use the load balancing method has a throughput of 108.4 KB/s as well as a response time value of 120.3 Ms. Therefore by implementing load balancing the performance of the system can always be improved.


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