Abstract
Due to the vigorous development of the network, a variety of application software has been widely used. In order to serve more users, it is necessary to build middleware servers (Application Servers). If the middleware server was overloaded, it will result in poor performance. Besides, it is simply waste of resources if loading was idle. So the server with or without load balancing becomes an important issue. The proposed LAPO algorithm in this paper can dynamically allocate each middleware server for each user. And firstly, it improves the POCA algorithm that spends a lot of computation time to determine the optimal combination of solutions. Secondly, it can uniformly distribute each user on the servers; and finally, propose the model for best combination of load balancing solution. By using the SAP ERP ECC 6.0 for implementation, this study can verify that the LAPO is not only more efficient in computation time than POCA, but also more in line with the actual situation of the enterprises use. Moreover, we comment the results of experiments and some limitations.
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References
SAP, TADM10_1 : SAP NetWeaver AS Implementation & Operation 1 (2008)
SAP, TADM10_2 : SAP NetWeaver AS Implementation & Operation 1 (2008)
Sharifian, S., Motamedi, S.A., Akbari, M.K.: A content-based load balancing algorithm with admission control for cluster web servers. Future Generation Computer Systems 24, 775–787 (2008)
Krueger, P., Chawla, R.: The Stealth Distributed Schedular. In: Procedding 11th Int’l Conference Distributed Computing Systems, Order No. 2144, pp. 336–343. IEEE CS Press, Los Alamitos (1991)
Livny, M., Melman, M.: Load Balancing in Homogeneous Broadcast Distributed Systems. In: Computer Network Performance Symposium, pp. 336–343 (May 1991)
Huang, Z., Liang, B.: A New Content-Aware Dynamic Load Balancing Algorithm for Web Server Clusters. Sciverse Science Direct (December 2011)
Sriram Iyengar, M., Singhal, M.: Effect of network latency on load sharing in distributed systems. J. Parallel Distrib. Comput. Sciverse Science Direct 66, 839–853 (2006)
Ting, P.-H.: A Research of User Distributions in Enterprise Systems. Universal Computer Science 12(2), 160–186 (2006)
Song, J., Iyengar, A., Levy-Abegnoli, E., Dias, D.: Architecture of a Web server accelerator. Computer Networks 38, 75–97 (2002)
Challenger, J., Dantzig, P., Iyengar, A.: A scalable and highly available system for serving dynamic data at frequently accessed websites. In: Proceedings of ACM/IEEE SC 1998 (November 1998)
Challenger, J., Iyengar, A., Dantzig, P.: A scalable system for consistently caching dynamic web data. In: Proceedings of IEEE INFOCOM 1999 (March 1999)
Iyengar, A., Challenger, J.: Improving web server performance by caching dynamic data. In: Proceedings of the USENIX Symposiumon Internet Technologies and Systems (December 1997)
Maddah, B., El-Taha, M., Tayeh, R.A.: Optimal allocation of servers and processing time in a load balancing system. Computers & Operations Research 37, 2173–2181 (2010)
Tari, Z., Broberg, J., Zomayab, A.Y., Baldoni, R.: A least flow-time first load sharing approach for distributed server farm. Science Direct 65, 832–842 (2005)
Sharifian, S., Motamedi, S.A., Akbari, M.K.: A predictive and probabilistic load-balancing algorithm for cluster-based web servers. Science Direct, Applied Soft Computing 11, 970–981 (2011)
Casalicchio, E., Cardellini, V., Colajanni, M.: Content-aware dispatching algorithms for cluster-based web servers. Cluster Computing 5, 65–74 (2002)
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Chuang, YC., Hsu, P., Wang, M., Lin, MT., Cheng, M.S. (2013). User Distributions in N-Tier Platform with Effective Memory Reusability. In: Ramanna, S., Lingras, P., Sombattheera, C., Krishna, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2013. Lecture Notes in Computer Science(), vol 8271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44949-9_5
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DOI: https://doi.org/10.1007/978-3-642-44949-9_5
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