In grid computing, if the system load in each of resources is almost equal, this indicates correct resource usage. This paper presents an agent based load balancing model. Instead of balancing the load in the grid by job migration technique or by moving an entire process to underloaded resources. The proposed agent based load balancing model aims to take advantage of the agent’s characteristics to generate an autonomous system. It also has a distinct advantage over other agent-based load balancing models in terms of resource utilization. The performance evaluation shows that the proposed model can enhance the overall performance of grid computing.
YagoubiB. and SlimaniY., Load Balancing Strategy For Grid Computing, Journal of Information Technology and Applications1(4) (March 2007), 285–296.
2.
YagoubiB. and MeddeberM., Distributed load balancing model for grid computing, ARIMA Journal12 (2010), 43–60.
3.
KlusáčekD. and RudováH., Alea 2 job scheduling simulator, In Proceedings of the 3rd International Conference on Simulation Tools and Techniques, 2010, Torremolinos, MalaMA, Spain.
4.
younesH. et al., New load balancing Framework based on mobile AGENT and ant-colony optimization technique, Conference Intelligent Systems and Computer Vision (ISCV), 2017, Fès, morocco.
5.
SatymbekovM.N.PakI.T.NaizabayevaL. and NurzhanovCh.A., Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes, Open Engineering7(1) (December 2017), 485–490.
6.
RathoreN., Efficient agent based priority scheduling and load balancing using fuzzy logic in grid computing, I-Manager’s Journal on Computer Science3(3) (2015), 11–22.
7.
RathoreN. and ChanaI., Job Migration Policies for Grid Environment, Wireless Personal Communication, Springer Publication-New-York (USA)89(1) (March 2016), 241–269.
8.
BuyyaR. and MurshedM., Gridsim: A toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing, The Journal of Concurrency and Computation: Practice and Experience (CCPE)14 (2002), 13–15.
9.
SurosR. and SerranoJ.F., Communication complexity in high-speed distributed computer network in an agent based architecture for grids service Ray Tracing View project, International Journal of Advanced Computer Research, 22 February 2018, Vol 8(35) ISSN (Print), 2249–7277.
10.
BanerjeeS. and HeckerJ., Multi-agent system approach to load-balancing and resource allocation for distributed computing, First Complex Systems Digital Campus World E-Conference, 2015.
