Resource Discovery in Non-Structured Peer to Peer Grid Systems Using the Shuffled Frog Leaping Algorithm

A. Ahmadian, M. Zavvar, A. Saeedi, F. Ramezani


In Peer to Peer (P2P) grid systems, users can utilize the resources of other machines for their tasks without involving themselves in the detailed aspects of addressing. One of the greatest challenges for these systems is finding the resource that matches the user’s request to minimize query traffic in the network. Thus, inspired by the Shuffled Frog Leaping Algorithm (SFLA), this article presents a new method for resource discovery in grid systems. This algorithm finds the resource that matches the user’s request via sending requests to the most suitable neighbors, thus preventing the flooding of requests and reducing traffic. The evaluation and comparison of the proposed method with the Genetic Algorithm (GA) and Differential Evolution Algorithm (DEA) indicate that it yields higher performance considering the speed and number of sent queries in the network.


Differential Evolution Algorithm; Genetic Algorithmm; Grid Systems; Peer to Peer Systems; Resource Discovery; Shuffled Frog Leaping Algorithm;

Full Text:



Balasangameshwara, J. & N. Raju, A hybrid policy for fault tolerant load balancing in grid computing environments. Journal of Network and computer Applications, 2012. 35(1): p. 412-422.

Foster, I. & C. Kesselman, The Grid 2: Blueprint for a new computing infrastructure. 2003: Elsevier.

Ennahbaoui, M. & H. Idrissi, Zero-Knowledge Authentication and Intrusion Detection System for Grid Computing Security, in Information Innovation Technology in Smart Cities. 2018, Springer. p. 199-212.

Reddy, T.S.K., D.N. Raju, P.R. Kumar & S.R. Kumar, Power Aware-Based Workflow Model of Grid Computing Using Ant-Based Heuristic Approach, in Big Data Analytics. 2018, Springer. p. 175- 184.

Benmalek, M., Y. Challal, A. Derhab & A. Bouabdallah, VerSAMI: Versatile and Scalable key management for Smart Grid AMI systems. Computer Networks, 2018.

Iamnitchi, A. & I. Foster, A peer-to-peer approach to resource location in grid environments, in Grid resource management. 2004, Springer. p. 413-429.

Navimipour, N.J., A.M. Rahmani, A.H. Navin & M. Hosseinzadeh, Resource discovery mechanisms in grid systems: A survey. Journal of Network and Computer Applications, 2014. 41: p. 389-410.

Noghabi, H.B., A.S. Ismail, A.A. Ahmed & M. Khodaei. An Optimized Search Algorithm for Resource Discovery in Peer to Peer Grid. in Informatics and Computational Intelligence (ICI), 2011 First International Conference on. 2011. IEEE.

Deng, Y., F. Wang & A. Ciura, Ant colony optimization inspired resource discovery in P2P Grid systems. The Journal of Supercomputing, 2009. 49(1): p. 4-21.

Trunfio, P., D. Talia, H. Papadakis, P. Fragopoulou, M. Mordacchini, M. Pennanen, K. Popov, V. Vlassov & S. Haridi, Peerto-Peer resource discovery in Grids: Models and systems. Future Generation Computer Systems, 2007. 23(7): p. 864-878.

Torkestani, J.A., A distributed resource discovery algorithm for P2P grids. Journal of Network and Computer Applications, 2012. 35(6): p. 2028-2036.

Yin, Y., H. Cui & X. Chen, The grid resource discovery method based on hierarchical model. Information Technology Journal, 2007. 6(7): p. 1090-1094.

Brocco, A., A. Malatras & B. Hirsbrunner, Enabling efficient information discovery in a self-structured grid. Future Generation Computer Systems, 2010. 26(6): p. 838-846.

Mastroianni, C., D. Talia & O. Verta, A super-peer model for resource discovery services in large-scale grids. Future Generation Computer Systems, 2005. 21(8): p. 1235-1248.

Papadakis, H., P. Trunfio, D. Talia & P. Fragopoulou, Design and implementation of a hybrid p2p-based grid resource discovery system, in Making Grids Work. 2008, Springer. p. 89-101.

Ebadi, S. & L.M. Khanli, A new distributed and hierarchical mechanism for service discovery in a grid environment. Future Generation Computer Systems, 2011. 27(6): p. 836-842.

Zhao, C., J. Yu & B. Chai. A study on mobile agent based resource management in grid. in International Conference on KnowledgeBased and Intelligent Information and Engineering Systems. 2007. Springer.

Kang, J. & K.M. Sim, A multiagent brokering protocol for supporting Grid resource discovery. Applied Intelligence, 2012. 37(4): p. 527-542.

Kaur, P. & S. Mehta, Resource provisioning and work flow scheduling in clouds using augmented Shuffled Frog Leaping Algorithm. Journal of Parallel and Distributed Computing, 2017. 101: p. 41-50.

Prakash, D., A. Tripathi & T.K. Sharma, Application of Shuffled Frog-Leaping Algorithm in Regional Air Pollution Control, in Soft Computing: Theories and Applications. 2018, Springer. p. 397-403.

Tong, X., Y. Ji, J. Lin, J. Zhu, F. Sun, Y. Zhong, Y. Yang & X. Zhu, Cooperative spectrum sensing based on a modified shuffled frog leaping algorithm in 5G network. Physical Communication, 2017. 25: p. 438-444.

Sharma, T.K. & M. Pant, Opposition-Based Learning Embedded Shuffled Frog-Leaping Algorithm, in Soft Computing: Theories and Applications. 2018, Springer. p. 853-861.

Sarathambekai, S. & K. Umamaheswari, Performance comparison of discrete particle swarm optimisation and shuffled frog leaping algorithm in multiprocessor task scheduling problem. International Journal of Advanced Intelligence Paradigms, 2017. 9(2-3): p. 139- 163.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN: 2180-1843

eISSN: 2289-8131