Methodology for Load Balancing in Multi‐Agent System Using SPE Approach - Security Issues and Privacy Concerns in Industry 4.0 Applications - Wiley Online Library

In today's scenario a large number of applications are built using Multi-Agent System. The Multi-Agent System (MAS) is a system composed of the coalition and the interaction of several agents distributed in various environments. Thus, there exists the problem of load imbalance between the agents in the system. The load imbalance will result in poor performance of the system. The agents in MAS utilize the system resources such as CPU capacity, memory and communication bandwidth. The agents of the system span the entire machine and so agents do have variable workload patterns depending on the communication among agents. Due to this, some of the agents have more workload while others have less workload. So if the load can be distributed among the agents in such a way that no agent is idle or no agent is overloaded then we can obtain a better performance. In this chapter, we developed an algorithm for load balancing that addresses the load imbalance among agents in MAS using Software Performance Engineering (SPE) approach. The algorithm is implemented using JADE [1] and NetLogo [2]. The results are validated and discussed.

References

Bellifemine F., Bergenti F., Caire G., Poggi A. (2005) Jade — A Java Agent Development Framework. In: Bordini R.H., Dastani M., Dix J., El Fallah Seghrouchni A. (eds.), Multi-Agent Programming. Multiagent Systems, Artificial Societies, and Simulated Organizations (International Book Series), vol 15. Springer, Boston, MA. 10.1007/0-387-26350-0_5
10.1007/0‐387‐26350‐0_5
Google Scholar
Website: https://ccl.northwestern.edu/netlogo/
Google Scholar
A. Dorri, S. S. Kanhere and R. Jurdak, “Multi-Agent Systems: A Survey,” in IEEE Access, vol. 6, pp. 28573-28593, 2018, doi: 10.1109/ACCESS.2018.2831228.
10.1109/ACCESS.2018.2831228
Web of Science® Google Scholar
Jing Xie and Chen-Ching Liu, Multi-agent systems and their applications, Journal of International Council on Electrical Engineering , 2017, Vol. 7, No. 1, 188–197, 10.1080/22348972.2017.1348890
10.1080/22348972.2017.1348890
Google Scholar
A. Sekala, G.Cwikala and G.Kosti, The role of multi-agent systems in improving performance of manufacturing robotized cells, IOP Conf. Series: Materials Science and Engineering 95 (2015) 012097 doi:10.1088/1757-899X/95/1/012097
10.1088/1757‐899X/95/1/012097
Google Scholar
S. Ajitha, T.V. Suresh Kumar, Assessing performance of agents in a MAS: an experimental Study, International Journal of Advanced Research in Computer Science, Vol. 9, No. 5, September-October 2018, ISSN No. 0976-5697.
Google Scholar
S. Ajitha, Modeling the Negotiation of Agents in MAS and Predicting the Performance – an SPE Approach, Informatica, An International Journal of Computing and Informatics, Vol. 43, No. 3, 2019.
Google Scholar
Chang Ouk Kim, Ick-Hyun Kwon, Choonjong Kwak (2010), “Multi-agent based distributed inventory control model”, Expert Systems with Applications 37 (2010) 5186–5191
10.1016/j.eswa.2009.12.073
Web of Science® Google Scholar
I.F. Barcelos Tronto, J.D. Simões da Silva, N. Sant'Anna The artificial neural networks model for software effort estimation INPE ePrint:sid.inpe.br/ ePrint@80/2006/12.20.23.38 v1 2006-12-21
Google Scholar
Man-Yi Chen, Ding-Fang Chen, “ Early cost estimation of strip-steel coiler using BP neural network”, Proceedings of the first international conference on machine learning and cybernetic, Beijing 4-5 Nov. 2002
Google Scholar
Wei Liu, Xiaoling Huang, Guanwang, Tianyou Chai, “ The modeling and application of cost prediction based on neural networks”, 2004 5th Asian Control Conference.
Google Scholar
Evangelin Geetha D, Ch. Ram Mohan Reddy, Suresh Kumar T V and Rajani Kanth K: “ JAPET: A Java Based tool for performance evaluation of software systems”. Proceedings of international conference on software knowledge information management and application, 12-15, December 2006 at Chiang Mai, Thailand, pp. 64-69.
Google Scholar

Security Issues and Privacy Concerns in Industry 4.0 Applications