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A Load Balancing Policy for Distributed Web Service

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DOI: 10.4236/ijcns.2010.38087    4,664 Downloads   8,724 Views   Citations


The proliferation of web services; and users appeal for high scalability, availability and reliability of web servers to provide rapid response and high throughput for the Clients’ requests occurring at anytime. Distributed Web Servers (DWSs) provide an effective solution for improving the quality of web services. This paper addresses un-regulated jobs/tasks migration among the servers. Considering distributed web services with several servers running, a lot of bandwidth is wasted due to unnecessary job migration. Having considered bandwidth optimization, it is important to develop a policy that will address the bandwidth consumption while loads/tasks are being transferred among the servers. The goal of this work is to regulate this movement to minimize bandwidth consumption. From literatures, little or no attention was given to this problem, making it difficult to implement some of these policies/schemes in bandwidth scarce environment. Our policy “Cooperative Adaptive Symmetrical Initiated Dynamic/Diffusion (CASID)” was developed using Java Development Environment (JADE) a middle ware service oriented environment which is agent-based. The software was used to simulate events (jobs distribution) on the servers. With no job transfer allowed when all servers are busy, any over loaded server process jobs internally to completion. We achieved this by having two different agents; static cognitive agents and dynamic cognitive agents. The results were compared with the existing schemes. CASID policy outperforms PLB scheme in terms of response time and system throughput.

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The authors declare no conflicts of interest.

Cite this paper

S. Eludiora, O. Abiona, G. Aderounmu, A. Oluwatope, C. Onime and L. Kehinde, "A Load Balancing Policy for Distributed Web Service," International Journal of Communications, Network and System Sciences, Vol. 3 No. 8, 2010, pp. 645-654. doi: 10.4236/ijcns.2010.38087.


[1] W. Winston, “Optimality of the Shortest Line Discipline,” Journal of Applied Probability, Vol. 14, No. 1, 1977, pp. 181-189.
[2] J. Cao, Y. Sun, X. Wang and S. K. Das, “Scalable Load Balancing in Distributed Web Servers Using Mobile Agents,” Journal of Parallel and Distributed Computing, Vol. 63, No. 10, 2003, pp. 996-1005.
[3] N. Nehra, R. B. Patel and V. K. Bhat, “A Framework for Distributed Dynamic Load Balancing in Heterogeneous Cluster,” Journal of Computer Science, Vol. 3, No. 1, 2007, pp. 14-24. 14-24.pdf.
[4] R. B. Patel and N. Aggarwal, “Load Balancing on Open Networks: A Mobile Agent Approach,” Journal of Com- puter Science, Vol. 2, No. 4, 2006, pp. 337-346. http:// www.scipub.orga/fulltext/jcs/jcs24337-346.pdf.
[5] M. Aramudhan and V. R. Uthaiaraj, “LDMA and WLD- MA: Load Balancing Strategies for Distributed LAN and WAN Environments,” International Journal of Computer Science and Network Security, Vol. 6, No. 9B, September 2006. 11.pdf.
[6] M. Saeb and C. Fathy, “Modified Diffusion Dynamic Load Balancing Employing Mobile Agents,” Computer Engi- neering Department, Arab Academy for Science, Techno- logy & Maritime Transport, Alexandria, 2001. http://www.
[7] S. Penmatsa and A. T. Chronopoulos, “Dynamic Multi- User Load Balancing in Distributed Systems,” Proceedings of IEEE International Parallel and Distributed Processing Symposium, Long Beach, 26-30 March 2007, pp. 122-131.
[8] Y. Fu, H. Wang, C. Y. Lu and S. Ramu, “Distributed Uti- lization Control for Real-Time Clusters with Load Balancing,” Proceedings of the 27th IEEE International Real- Time Systems Symposium, Rio de Janeiro, 5-8 December 2006, pp. 137-146.
[9] L. Chu, K. Shen and T. Yang, “Cluster Load Balancing for Fine-Grain Network Services,” Technical Report TR- CS2002-02, Department of Computer Science, University of California, Santa Barbara, 2002.
[10] J. Ghanem, C. T. Abdallah, M. M. Hayat, J. Chiasson and J. D. Birdwell, “Distributed Load Balancing in the Prese- nce of Node Failure and Network Delays,” 2006. http://
[11] K. Barker and N. Chrisochoides, “Practical Performance Model for Optimizing Dynamic Load Balancing of Ad- aptive Applications,” Proceedings of the 19th IEEE Inter- national Parallel and Distributed Processing Symposium, Denver, Vol. 1, 4-8 April 2005, pp. 28-37.
[12] F. Leon, M. H. Zaharia and D. Galea, “A Simulator for Load Balancing Analysis in Distributed Systems,” In: A. Valachi, D. Galea, A. M. Florea, M. Craus, Ed., Thenologii Informationale, Editura Unvierisitatii, Suceava, 2003, pp. 53-59.
[13] K. Y. Kabalan, W. W. Smari and J. Y. Hakimian, “Adaptive Load Sharing in Heterogeneous Systems Polices, Mo- difications, and Simulation,” 2009. http://ducati.doc.ntu. issue%20karatza/kabalan/kabalan.pdf.
[14] K. S. Chatrapati, K. P. Chand, Y. R. Kumar and A. V. Babu, “A Novel Approach for Effective Dynamic Load Balancing by Using Tendensive Weight,” International Journal of Computer Science and Network Security, Vol. 8, No. 6, June 2008, pp. 42-48.
[15] M. Gerla and L. Kleinrock, “On the Topological Design of Distributed Computer Networks,” IEEE Transactions on Communications, Vol. 25, No. 1, 1977, pp. 48-60.
[16] M. Andreolini and E. Casalicchio, “A Cluster-Based Web System Providing Differentiated and Guaranteed Services,” Cluster Computing, Vol. 7, No. 1, 2004, pp. 7-19.
[17] M. Andreolini and S. Casolari, “A Distributed Architecture for Gracefully Degradable Web-Based Services,” Pro- ceedings of IEEE International Symposium on Network Computing and Applications, Cambridge, 24-26 July 2006, pp. 235-238.
[18] MathWorks, Inc., 2008.

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