Abstract
This paper presents the application of the Ant Colony Optimization (ACO) meta-heuristic to a new NP-hard problem involving the replication of multi-quality database-driven web applications (DA s) by a large application service provider (ASP). The ASP must assign DA replicas to its network of heterogeneous servers so that user demand is satisfied at the desired quality level and replica update loads are minimized. Our ACO algorithm, AntDA , for solving the ASP’s replication problem has several novel or infrequently seen features: ants traverse a bipartite graph in both directions as they construct solutions, pheromone is used for traversing from one side of the bipartite graph to the other and back again, heuristic edge values change as ants construct solutions, and ants may sometimes produce infeasible solutions. Testing shows that the best results are achieved by using pheromone and heuristics to traverse the bipartite graph in both directions. Additionally, experiments show that AntDA outperforms several other solution methods.
Research funded by NSF grant 998404-0010819000.
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References
Bright, L., Raschid, L.: Using latency-recency profiles for data delivery on the web. In: VLDB, pp. 550–561 (2002)
Cherniack, M., Galvez, E.F., Franklin, M.J., Zdonik, S.: Profile-driven cache management. In: Proceedings of the International Conference on Data Engineering (ICDE), pp. 645–656. IEEE Computer Society, Los Alamitos (2003)
Mayer, C.B.: Quality-based Replication of Freshness-Differentiated Web Applications and Their Back-end Databases. Ph.D thesis, Arizona State University (2005)
Mazzola, J.B., Neebe, A.W.: Lagrangian-relaxation-based solution procedures for a multiproduct capacitated facility location problem with choice of facility type. European Journal of Operational Research 115, 285–299 (1999)
Pirkul, H., Jayaraman, V.: A multi-commodity, multi-plant, capacitated facility location problem: Formulation and efficient heuristic solution. Computers and Operations Research 25(10), 869–878 (1998)
Dawande, M., Kalagnanam, J., Keskinocak, P., Ravi, R., Salman, F.S.: Approximation algorithms for the multiple knapsack problem with assignment restrictions. Combinatorial Optimization 4(2), 171–186 (2000)
Shachnai, H., Tamir, T.: Noah’s bagels - some combinatorial aspects. In: International Conference on Fun with Algorithms (1998)
Alaya, I., Solnon, C., Ghédira, K.: Ant algorithm for the multidimensional knapsack problem. In: International Conference on Bioinspired Optimization Methods and their Applications, pp. 63–72 (2004)
Leguizamon, G., Michalewicz, Z.: A new version of ant system for subset problems. In: Proceeding of the 1999 Congress on Evolutionary Computation, pp. 1459–1464. IEEE Press, Los Alamitos (1999)
Cordón, O., Fernández de Viana, I., Herrera, F.: Analysis of the best-worst ant system and its variants on the QAP. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 228–234. Springer, Heidelberg (2002)
Foong, W.K., Maier, H.R., Simpson, A.R.: Ant colony optimization for power plant maintenance scheduling optimization. In: Genetic and Evolutionary Computation Conference (GECCO), pp. 249–256. ACM, New York (2005)
Lourenço, H.R., Serra, D.: Adaptive search heuristics for the generalized assignment problem. Mathware and Soft Computing 9(2), 209–234 (2002), On-line journal. Articles available at: http://docto-si.ugr.es/Mathware/ENG/mathware.html
Stützle, T., Dorigo, M.: ACO algorithms for the quadratic assignment problem. In: New Ideas in Optimization, pp. 33–50. McGraw-Hill, New York (1999)
Bonabeau, E., Dorigo, M., Theraulaz, T.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)
Dorigo, M., Stützle, T.: Ant Colony Optimization. The MIT Press, Cambridge (2004)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics–Part B 26(1), 29–41 (1996)
Eyckelhof, C.J., Snoek, M.: Ant systems for a dynamic TSP. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 88–99. Springer, Heidelberg (2002)
Blum, C., Sampels, M.: An ant colony optimization algorithm for shop scheduling problems. J. of Mathematical Modelling and Algorithms 34(3), 285–308 (2004)
Comellas, F., Ozón, J.: An ant algorithm for the graph colouring problem. In: First International Workshop on Ant Colony Optimization (ANTS 1998) (1998)
Costa, D., Hertz, A.: Ants can colour graphs. J. of the Operational Research Society 48, 295–305 (1997)
Gambardella, L.M., Dorigo, M.: An ant colony system hybridized with a new local search for the sequential ordering problem. INFORMS Journal on Computing 12(3), 237–255 (2000)
LINDO Systems, Inc.: Lingo (2006), http://www.lindo.com
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Mayer, C.B., Dressler, J., Harlow, F., Brault, G., Candan, K.S. (2006). Replicating Multi-quality Web Applications Using ACO and Bipartite Graphs. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_24
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DOI: https://doi.org/10.1007/11839088_24
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