Abstract
Load-Balancing is a significant problem in heterogeneous distributed systems. There exist many load balancing algorithms, however, most approaches are very problem specific oriented and a comparison is therefore complex. This paper proposes a generic architectural pattern for a load balancing framework that allows for the plugging of different load balancing algorithms, reaching from unintelligent to intelligent ones, to ease the selection of the best algorithm for a certain problem scenario. As in complex network environments there is no “one-fits-all solution”, also the integration of several different algorithms shall be supported. The presented pattern assumes autonomous agents and decentralized control. It can be composed towards arbitrary network topologies, foresees exchangeable policies for load-balancing, and uses a black-board based communication mechanism to achieve high software architecture agility. The pattern has been implemented and first instantiations of it with three algorithms have been benchmarked.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Androutsellis-Theotokis, S., Spinellis, D.: A survey of peer-to-peer content distribution technologies. ACM Comput. Surv. 36(4), 335–371 (2004)
Barker, K., Chernikov, A., Chrisochoides, N., Pingali, K.: A load balancing framework for adaptive and asynchronous applications. IEEE Transactions on Parallel and Distributed Systems 15(2), 183–192 (2004)
Barker, K.J., Chrisochoides, N.P.: An evaluation of a framework for the dynamic load balancing of highly adaptive and irregular parallel applications. In: SC 2003: Proceedings of the 2003 ACM/IEEE conference on Supercomputing, p. 45 (2003)
Bravetti, M., Gorrieri, R., Lucchi, R., Zavattaro, G.: Quantitative information in the tuple space coordination model. Theor. Comput. Sci. 346(1), 28–57 (2005)
Bronevich, A.G., Meyer, W.: Load balancing algorithms based on gradient methods and their analysis through algebraic graph theory. J. Parallel Distrib. Comput. 68(2), 209–220 (2008)
Cabri, G., Leonardi, L., Zambonelli, F.: Mars: A programmable coordination architecture for mobile agents. IEEE Internet Computing 4(4), 26–35 (2000)
Chen, J.-C., Liao, G.-X., Hsie, S., Liao, C.-H.: A study of the contribution made by evolutionary learning on dynamic load-balancing problems in distributed computing systems. Expert Syst. Appl. 34(1), 357–365 (2008)
Chong, C.S., Sivakumar, A.I., Low, M.Y.H., Gay, K.L.: A bee colony optimization algorithm to job shop scheduling. In: WSC 2006: Proc. of the 38th conference on Winter simulation, pp. 1954–1961 (2006)
Cortés, A., Ripoll, A., Cedó, F., Senar, M.A., Luque, E.: An asynchronous and iterative load balancing algorithm for discrete load model. J. Parallel Distrib. Comput. 62(12), 1729–1746 (2002)
Craß, S., Kühn, E., Salzer, G.: Algebraic foundation of a data model for an extensible space-based collaboration protocol. In: 13th International Database Engineering & Applications Symposium, IDEAS (to appear, 2009)
Davidsson, P., Johansson, S., Svahnberg, M.: Characterization and evaluation of multi-agent system architectural styles. In: Garcia, A., Choren, R., Lucena, C., Giorgini, P., Holvoet, T., Romanovsky, A. (eds.) SELMAS 2005. LNCS, vol. 3914, pp. 179–188. Springer, Heidelberg (2006)
Dobson, S., Denazis, S., Fernández, A., Gaïti, D., Gelenbe, E., Massacci, F., Nixon, P., Saffre, F., Schmidt, N., Zambonelli, F.: A survey of autonomic communications. ACM Trans. Auton. Adapt. Syst. 1(2), 223–259 (2006)
Ducasse, S., Hofmann, T., Nierstrasz, O.: Openspaces: An object-oriented framework for reconfigurable coordination spaces. In: Porto, A., Roman, G.-C. (eds.) COORDINATION 2000. LNCS, vol. 1906, pp. 1–18. Springer, Heidelberg (2000)
Eager, D.L., Lazowska, E.D., Zahorjan, J.: Adaptive load sharing in homogeneous distributed systems. IEEE Trans. Softw. Eng. 12(5), 662–675 (1986)
Gelernter, D., Carriero, N.: Coordination languages and their significance. Commun. ACM 35(2), 97–107 (1992)
Georgousopoulos, C., Rana, O.F.: Combining state and model-based approaches for mobile agent load balancing. In: SAC 2003: Proceedings of the 2003 ACM symposium on Applied computing, pp. 878–885 (2003)
Godfrey, B., Lakshminarayanan, K., Surana, S., Karp, R., Stoica, I.: Load balancing in dynamic structured P2P systems. In: Proc. IEEE INFOCOM (2004)
Gomoluch, J., Schroeder, M.: Information agents on the move: A survey with load balancing with mobile agents. Software Focus 2(2) (2001)
Herrero, P., Bosque, J.L., Pérez, M.S.: An agents-based cooperative awareness model to cover load balancing delivery in grid environments. In: OTM Workshops (1), pp. 64–74 (2007)
Ho, C.K., Ewe, H.T.: Ant colony optimization approaches for the dynamic load-balanced clustering problem in ad hoc networks. In: Swarm Intelligence Symposium, Hawaii, pp. 76–83. IEEE, Los Alamitos (2007)
Hohpe, G., Woolf, B.: Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. Addison-Wesley, Reading (2003)
Hu, T.-L., Chen, G., Chen, K., Dong, J.-X.: An adaptive load balancing framework for parallel database systems based on collaborative agents, vol. 1, pp. 464–468. IEEE, Los Alamitos (2005)
Janssens, N., Steegmans, E., Holvoet, T., Verbaeten, P.: An agent design method promoting separation between computation and coordination. In: SAC 2004: Proceedings of the 2004 ACM symposium on Applied computing, pp. 456–461 (2004)
Johansson, S., Davidsson, P., Kristell, M.: Four multi-agent architectures for intelligent network load management. In: Karmouch, A., Magedanz, T., Delgado, J. (eds.) MATA 2002. LNCS, vol. 2521, pp. 239–248. Springer, Heidelberg (2002)
Karger, D.R., Ruhl, M.: Simple efficient load balancing algorithms for peer-to-peer systems. In: SPAA 2004: Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures, pp. 36–43 (2004)
Keren, A., Barak, A.: Adaptive placement of parallel java agents in a scalable computing cluster, vol. 10, pp. 971–976 (1998)
Krueger, P., Shivaratri, N.G.: Adaptive location policies for global scheduling. IEEE Trans. Softw. Eng. 20(6), 432–444 (1994)
Kühn, E., Mordinyi, R., Keszthelyi, L., Schreiber, C.: Introducing the concept of customizable structured spaces for agent coordination in the production automation domain. In: The 8th Int.Conference on Autonomous Agents and Multiagent Systems, AAMAS 2009 (2008)
Lemmens, N., de Jong, S., Tuyls, K., Nowé, A.: Bee behaviour in multi-agent systems, pp. 145–156 (2008)
Lin, F.C.H., Keller, R.M.: The gradient model load balancing method. IEEE Trans. Softw. Eng. 13(1), 32–38 (1987)
Murata, Y., Takizawa, H., Inaba, T., Kobayashi, H.: A distributed and cooperative load balancing mechanism for large-scale p2p systems. In: SAINT-W 2006: Proceedings of the International Symposium on Applications on Internet Workshops, pp. 126–129. IEEE, Los Alamitos (2006)
Pietro Picco, G., Murphy, A.L., Roman, G.-C.: Lime: Linda meets mobility. In: ICSE 1999: Proceedings of the 21st international conference on Software engineering, pp. 368–377. IEEE, Los Alamitos (1999)
Putrycz, E.: Design and implementation of a portable and adaptable load balancing framework. In: CASCON 2003: Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research, pp. 238–252. IBM Press (2003)
Rahman, M.A.: Load balancing in dht based p2p networks. In: 5th Int. Conference on Electrical and Computer Engineering, ICECE 2008, pp. 164–171 (2008)
Rajagopalan, A., Hariri, S.: An agent based dynamic load balancing system, pp. 164–171 (2000)
Sesum-Cavic, V., Kühn, E.: Instantiation of a generic model for load balancing with intelligent algorithms. In: Hummel, K.A., Sterbenz, J.P.G. (eds.) IWSOS 2008. LNCS, vol. 5343, pp. 311–317. Springer, Heidelberg (2008)
Stützle, T., Hoos, H.: Max-min ant system. Future Generation Comput. Syst. 16(9), 889–914 (2000)
Thant, H., San, K., Tun, K., Naing, T., Thein, N.: Mobile agents based load balancing method for parallel applications. In: 6th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2005 (2005)
Tian, J., Liu, Y., Yang, X.-H., Du, R.: Design and analysis of a novel load-balancing model based on mobile agent. In: Yeung, D.S., Liu, Z.-Q., Wang, X.-Z., Yan, H. (eds.) ICMLC 2005. LNCS (LNAI), vol. 3930, pp. 70–80. Springer, Heidelberg (2006)
Tolksdorf, R., Menezes, R.: Using swarm intelligence in linda systems. In: Omicini, A., Petta, P., Pitt, J. (eds.) ESAW 2003. LNCS (LNAI), vol. 3071, pp. 49–65. Springer, Heidelberg (2004)
Une, H., Qian, F.: Network load balancing algorithm using ants computing. In: IAT 2003: Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology, p. 428 (2003)
Wang, Y., Liu, J.: Macroscopic model of agent-based load balancing on grids. In: AAMAS 2003: Proceedings of the second international joint conference on Autonomous agents and multiagent systems, pp. 804–811. ACM, New York (2003)
Xu, M., Guan, J.: Routing based load balancing for unstructured p2p networks. Future Generation Communication and Networking 2, 332–337 (2007)
Xu, Z., Bhuyan, L.: Effective load balancing in p2p systems. In: CCGRID 2006: Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid, pp. 81–88. IEEE, Los Alamitos (2006)
Zhu, Y., Hu, Y.: Efficient, proximity-aware load balancing for dht-based p2p systems. IEEE Trans. on Parallel and Distributed Systems 16(4), 349–361 (2005)
Zoels, S., Despotovic, Z., Kellerer, W.: Load balancing in a hierarchical dht-based p2p system, pp. 353–361. IEEE, Los Alamitos (2007)
Zomaya, A.Y., Teh, Y.-H.: Observations on using genetic algorithms for dynamic load-balancing. IEEE Transactions on Parallel and Distributed Systems 12(9), 899–911 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kühn, E., Sesum-Cavic, V. (2009). A Space-Based Generic Pattern for Self-Initiative Load Balancing Agents. In: Aldewereld, H., Dignum, V., Picard, G. (eds) Engineering Societies in the Agents World X. ESAW 2009. Lecture Notes in Computer Science(), vol 5881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10203-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-10203-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10202-8
Online ISBN: 978-3-642-10203-5
eBook Packages: Computer ScienceComputer Science (R0)