Simulated evolution and simulated annealing algorithms for solving multi-objective open shortest path first weight setting problem

Optimal utilization of resources in present-day communication networks is a challenging task. Routing plays an important role in achieving optimal resource utilization. The open shortest path first (OSPF) routing protocol is widely used for routing packets from a source node to a destination node. This protocol assigns weights (or costs) to the links of a network. These weights are used to determine the shortest path between all sources to all destination nodes. Assignment of these weights to the links is classified as an NP-hard problem. This paper formulates the OSPF weight setting problem as a multi-objective optimization problem, with maximum utilization, number of congested links, and number of unused links as the optimization objectives. Since the objectives are conflicting in nature, an efficient approach is needed to balance the trade-off between these objectives. Fuzzy logic has been shown to efficiently solve multi-objective optimization problems. A fuzzy cost function for the OSPF weight setting problem is developed in this paper based on the Unified And-OR (UAO) operator. Two iterative heuristics, namely, simulated annealing (SA) and simulated evolution (SimE) have been implemented to solve the multi-objective OSPF weight setting problem using a fuzzy cost function. Results are compared with that found using other cost functions proposed in the literature (Sqalli et al. in Network Operations and Management Symposium, NOMS, 2006). Results suggest that, overall, the fuzzy cost function performs better than existing cost functions, with respect to both SA and SimE. Furthermore, SimE shows superior performance compared to SA. In addition, a comparison of SimE with NSGA-II shows that, overall, SimE demonstrates slightly better performance in terms of quality of solutions.

[1]  Thomas W. Reps,et al.  An Incremental Algorithm for a Generalization of the Shortest-Path Problem , 1996, J. Algorithms.

[2]  Panos M. Pardalos,et al.  Handbook of Massive Data Sets , 2002, Massive Computing.

[3]  Rong Qu,et al.  A hybrid scatter search meta-heuristic for delay-constrained multicast routing problems , 2010, Applied Intelligence.

[4]  Prithviraj Banerjee,et al.  Optimization by simulated evolution with applications to standard cell placement , 1991, DAC '90.

[5]  Ellen W. Zegura,et al.  How to model an internetwork , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[6]  Liu Dsosu,et al.  Fuzzy random measure and its extension theorem , 1983 .

[7]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[8]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[9]  Aluizio F. R. Araújo,et al.  MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives , 2008, Applied Intelligence.

[10]  Se-Young Oh,et al.  A new evolutionary programming approach based on simulated annealing with local cooling schedule , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[11]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[12]  Balram Suman,et al.  Study of simulated annealing based algorithms for multiobjective optimization of a constrained problem , 2004, Comput. Chem. Eng..

[13]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[14]  Jaymin Kessler,et al.  Using genetic algorithms to reorganize superpeer structure in peer to peer networks , 2007, Applied Intelligence.

[15]  Keith W. Ross,et al.  Computer networking - a top-down approach featuring the internet , 2000 .

[16]  A. Narayanan.  Probability and statistics in engineering and management science , 1972 .

[18]  S. Asadullah,et al.  Minimizing the Number of Congested Links in OSPF Routing , 2008, 2008 Australasian Telecommunication Networks and Applications Conference.

[19]  Kenneth L. Calvert,et al.  Modeling Internet topology , 1997, IEEE Commun. Mag..

[20]  Daniele Frigioni,et al.  Semidynamic Algorithms for Maintaining Single-Source Shortest Path Trees , 1998, Algorithmica.

[21]  Andries Petrus Engelbrecht,et al.  Fuzzy hybrid simulated annealing algorithms for topology design of switched local area networks , 2009, Soft Comput..

[22]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[23]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[24]  Andrew Lim,et al.  Particle Swarm Optimization and Hill Climbing for the bandwidth minimization problem , 2006, Applied Intelligence.

[25]  Prithviraj Banerjee,et al.  Empirical and theoretical studies of the simulated evolution method applied to standard cell placement , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[26]  Ujjwal Maulik,et al.  A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA , 2008, IEEE Transactions on Evolutionary Computation.

[27]  Sadiq M. Sait,et al.  Engineering Evolutionary Algorithm to Solve Multi-objective OSPF Weight Setting Problem , 2006, Australian Conference on Artificial Intelligence.

[28]  Nazish Hoda,et al.  Orthogonal simulated annealing for multiobjective optimization , 2010, Comput. Chem. Eng..

[29]  Salman A. Khan,et al.  Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks , 2009 .

[30]  I. Matsuba,et al.  Optimal simulated annealing method and its application to combinatorial problems , 1989, International 1989 Joint Conference on Neural Networks.

[31]  A.A. Ghazala,et al.  A Survey for Open Shortest Path First Weight Setting (OSPFWS) Problem , 2008, 2008 International Conference on Information Security and Assurance (isa 2008).

[32]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[33]  M. J. Frank.  On the simultaneous associativity of F(x, y) and x+y-F(x, y). (Short Communication). , 1978 .

[34]  Dominik Ślęzak,et al.  Convergence and Hybrid Information Technology - 5th International Conference, ICHIT 2011, Daejeon, Korea, September 22-24, 2011. Proceedings , 2011, ICHIT.

[35]  Didier Dubois,et al.  Operations in a Fuzzy-Valued Logic , 1979, Inf. Control..

[36]  M. J. Frank.  On the simultaneous associativity ofF(x,y) andx +y -F(x,y) , 1979 .

[37]  A. Odlyzko,et al.  Internet growth: is there a Moore's law for data traffic? , 2000 .

[38]  J. R. Shin,et al.  An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems , 2002 .

[39]  Tao Xiong,et al.  A combined SVM and LDA approach for classification , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[40]  Sun Jin Kim,et al.  Evolutionary algorithms for route selection and rate allocation in multirate multicast networks , 2007, Applied Intelligence.

[41]  Sadiq M. Sait,et al.  Fuzzy simulated evolution algorithm for multi-objective optimization of VLSI placement , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[42]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[43]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[44]  A.A. Ghazala,et al.  A New Approach for Open Shortest Path Weight Setting Problem (OSPFWSP) , 2008, 2008 Third International Conference on Convergence and Hybrid Information Technology.

[45]  Sadiq M. Sait,et al.  Iterative computer algorithms with applications in engineering - solving combinatorial optimization problems , 2000 .

[46]  C. Chatfield.  Probability and statistics in engineering and management science , 1973 .

[47]  Mikkel Thorup,et al.  Traffic engineering with traditional IP routing protocols , 2002, IEEE Commun. Mag..

[48]  Andries Petrus Engelbrecht,et al.  A fuzzy ant colony optimization algorithm for topology design of distributed local area networks , 2008, 2008 IEEE Swarm Intelligence Symposium.

[49]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[50]  Andries Petrus Engelbrecht,et al.  A new fuzzy operator and its application to topology design of distributed local area networks , 2007, Inf. Sci..

[51]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

[52]  Prithviraj Banerjee,et al.  ESp: Placement by simulated evolution , 1989, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[53]  Daniele Frigioni,et al.  Experimental analysis of dynamic algorithms for the single source shortest paths problem , 1998, JEAL.

[54]  Sadiq M. Sait,et al.  Multiobjective VLSI cell placement using distributed simulated evolution algorithm , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[55]  Mikkel Thorup,et al.  Increasing Internet Capacity Using Local Search , 2004, Comput. Optim. Appl..

[56]  Hongxing Li,et al.  Fuzzy Sets and Fuzzy Decision-Making , 1995 .

[57]  Sadiq M. Sait,et al.  An Enhanced Estimator to Multi-objective OSPF Weight Setting Problem , 2006, 2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006.

[58]  S. Weber.  A general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms , 1983 .

[59]  Sadiq M. Sait,et al.  Iterative Computer Algorithms and their Application to Engineering , 1999 .

[60]  Ju Li,et al.  A QoS-Tunable Scheme for ATM Cell Scheduling Using Evolutionary Fuzzy System , 2005, Applied Intelligence.

[61]  Panos M. Pardalos,et al.  A Genetic Algorithm for the Weight Setting Problem in OSPF Routing , 2002, J. Comb. Optim..