A Warning Propagation-Based Linear-Time-and-Space Algorithm for the Minimum Vertex Cover Problem on Giant Graphs

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A Warning Propagation-Based Linear-Time-and-Space Algorithm for the Minimum Vertex Cover Problem on Giant Graphs Hong Xu Kexuan Sun Sven Koenig T. K. Satish Kumar {hongx, kexuansu, skoenig}@usc.edu tkskwork@gmail.com January 3, 218 University of Southern California, Los Angeles, California 989, the United States of America The 15th International Symposium on Artificial Intelligence and Mathematics (ISAIM 218) Fort Lauderdale, Florida, the United States of America

Summary The minimum vertex cover (MVC) problem is a classical computer science problem. Local search algorithms often require a good starting state. For giant graphs, it is desirable to develop a linear-time-and-space algorithm to find a vertex cover as small as possible. We developed MVC-WP, a family of warning propagation-based linear-time-and-space algorithms. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 1 / 22

Agenda Motivation MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Experimental Evaluation Conclusion and Future Work Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 2 / 22

Agenda Motivation MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Experimental Evaluation Conclusion and Future Work

Motivation: The Minimum Vertex Cover (MVC) Problem The minimum vertex cover (MVC) problem is a classical computer science problem. On a graph G = V, E, a vertex cover (VC) is a subset of vertices S V such that every edge in G has at least one endpoint vertex in S. The MVC problem is to find a VC of minimum cardinality. Applications: Computer network security (Filiol et al. 27) Crew scheduling (Sherali et al. 1984) Construction of phylogenetic tree (Abu-Khzam et al. 24) Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 3 / 22

Motivation: A Linear Algorithm for the MVC Problem For giant graphs: Exact algorithms in general do not scale well. Local search algorithms require a small VC as a starting state (Andrade et al. 212; Cai 215; Cai et al. 213; Pullan 29). A linear-time-and-space algorithm to construct a small VC is desirable. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 4 / 22

Agenda Motivation MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Experimental Evaluation Conclusion and Future Work

Warning Propagation (WP) for the MVC Problem An iterative algorithm proposed and has only been used for theoretical analysis of properties of MVC on infinite graphs by (Weigt et al. 26). 1 u v u 1 v (a) u sends a message of to v since one of its incoming messages from other vertices is 1. (b) u sends a message of 1 to v since all other incoming messages are. There is a message of either or 1 along each direction of each edge. Assume that u and v are two adjacent vertices. u sends v a message of 1 to warn v to indicate that u will not be selected in the vertex cover. Otherwise, u sends v a message of. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 5 / 22

Basic Idea Observation: Warning propagation (WP) does not work well in practice (slow to converge, output often not good). But, each iteration uses only linear amount of time and space. Basic idea of a linear-time-and-space algorithm: Run a few iterations of warning propagation and extract a vertex cover afterwards. However, can we improve the output by having some processing before and after warning propagation iterations? Yes. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 6 / 22

Major Steps of MVC-WP MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Prune Leaves Initialize Messages Run Warning Propagation Iterations Remove Redundant Vertices Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 7 / 22

Major Steps of MVC-WP MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Prune Leaves Initialize Messages Run Warning Propagation Iterations Remove Redundant Vertices

Prune Leaves A leaf vertex is a vertex of degree 1. Idea: Adding a leaf vertex into the vertex cover is no better than adding its neighbor. Adding the blue vertex to the vertex cover is at least as good as adding the red vertex. Therefore, we can remove the two colored vertices from the graph. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 8 / 22

Major Steps of MVC-WP MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Prune Leaves Initialize Messages Run Warning Propagation Iterations Remove Redundant Vertices

Initialize Messages: Assuming Random Graph Models Standard warning propagation initialize all messages to zero, but we should be able to do better. We treat the pruned graph as if it were generated by a random graph model (but the input graph itself is not required to be generated by a random graph model). Erdős-Rényi: Vertex degrees follow a Poisson distribution (P(d) c d /d!). Scale-free: Vertex degrees follow a power law (P(d) d λ ). Basic idea: Initialize messages based on the values of the messages when warning propagation converges on an infinitely large random graph from analytical results. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 9 / 22

Warning Propagation (WP) for the MVC Problem An iterative algorithm proposed and has only been used for theoretical analysis of properties of MVC on infinite graphs by (Weigt et al. 26). 1 u v u 1 v (a) u sends a message of to v since one of its incoming messages from other vertices is 1. (b) u sends a message of 1 to v since all other incoming messages are. There is a message of either or 1 along each direction of each edge. Assume that u and v are two adjacent vertices. u sends v a message of 1 to warn v to indicate that u will not be selected in the vertex cover. Otherwise, u sends v a message of. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 1 / 22

Initialize Messages: Convergent Message Values on Infinite Graphs On a given infinitely large random graph, let p denote the probability that a message is zero and assume that p is constant for all messages. u 1 p = d=1 v p d 1 P(d) Erdős-Rényi: p = 1 W(c)/c (Weigt et al. 26) scale-free: p = (ζ(λ) 1)/(ζ(λ) + 1 2 λ ) Randomly initialize messages according to the calculated p. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 11 / 22

Major Steps of MVC-WP MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Prune Leaves Initialize Messages Run Warning Propagation Iterations Remove Redundant Vertices

Run Warning Propagation Iterations Average VC Size 2.44 2.42 2.4 2.38 2.36 2.34 2.32 2.3 2.28 1 5 MVC-WP-ER MVC-WP-SF 1 2 3 4 5 M How many iterations? We choose M = 3: A small number but has fairly good effectiveness. M: Number of iterations Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 12 / 22

Major Steps of MVC-WP MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Prune Leaves Initialize Messages Run Warning Propagation Iterations Remove Redundant Vertices

Remove Redundant Vertices Proposed by (Cai 215). Starting from a vertex cover, for each edge, if it has both endpoint vertices in the vertex cover, mark them as removable. Recursively remove removable vertices and update marks of other vertices accordingly. Guaranteed to output a minimal vertex cover. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 13 / 22

Agenda Motivation MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Experimental Evaluation Conclusion and Future Work

Benchmark Instances Network repository (http://networkrepository.com/) misc networks (397) web networks (18) brain networks (26) Street networks (8) (http: //www.cc.gatech.edu/dimacs1/archive/streets.shtml) All graphs have more than 1, vertices. We have also converted these graphs in various formats to the DIMACS format: http://files.hong.me/papers/xu218b-data Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 14 / 22

Algorithms Our Algorithms: MVC-WP-ER: Assuming Erdős-Rényi random graphs. MVC-WP-SF: Assuming scale-free random graphs. Competitors: MVC-2 (Vazirani 23) ConstructVC (Cai 215) R (Andrade et al. 212) MVC-MPL (Xu et al. 217) MVC-L (Xu et al. 217) To ensure fair comparison, leaf pruning and redundant vertex removal are also applied to each algorithm. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 15 / 22

Results Our Alternative Misc Web Street Brain Algorithm Algorithm (397) (18) (8) (26) MVC-WP-ER MVC-WP-SF ConstructVC 211/39/147 12/1/5 8// //26 MVC-2 241/46/11 16/1/1 8// 26// R 376/16/5 17/1/ 8// 26// MVC-MPL 317/18/62 17/1/ 1//7 26// MVC-L 364/19/14 17/1/ 8// 26// ConstructVC 29/38/15 11/1/6 8// //26 MVC-2 249/45/13 15/1/2 8// 26// R 377/15/5 17/1/ 8// 26// MVC-MPL 316/18/63 17/1/ 1//7 26// MVC-L 363/21/13 17/1/ 8// 26// Comparison of sizes of vertex covers produced by MVC-WP-ER and MVC-WP-SF, respectively, with those of alternative algorithms. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 16 / 22

Results: Misc Networks Number of Benchmark Instances 15 1 5 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-ER - VC Size of an Alternative Algorithm) / Larger VC Size (%) (a) MVC-WP-ER versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Number of Benchmark Instances 15 1 5 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-SF - VC Size of an Alternative Algorithm) / Larger VC Size (%) (b) MVC-WP-SF versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 17 / 22

Results: Web Networks Number of Benchmark Instances 8 6 4 2 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-ER - VC Size of an Alternative Algorithm) / Larger VC Size (%) (a) MVC-WP-ER versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Number of Benchmark Instances 8 6 4 2 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-SF - VC Size of an Alternative Algorithm) / Larger VC Size (%) (b) MVC-WP-SF versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 18 / 22

Results: Brain Networks Number of Benchmark Instances 25 2 15 1 5 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-ER - VC Size of an Alternative Algorithm) / Larger VC Size (%) (a) MVC-WP-ER versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Number of Benchmark Instances 25 2 15 1 5 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-SF - VC Size of an Alternative Algorithm) / Larger VC Size (%) (b) MVC-WP-SF versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 19 / 22

Results: Street Networks Number of Benchmark Instances 8 6 4 2 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-ER - VC Size of an Alternative Algorithm) / Larger VC Size (%) (a) MVC-WP-ER versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Number of Benchmark Instances 8 6 4 2 ConstructVC MVC-2 R MVC-L MVC-MPL 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 (VC Size of MVC-WP-SF - VC Size of an Alternative Algorithm) / Larger VC Size (%) (b) MVC-WP-SF versus ConstructVC/MVC-2/R/MVC-L/MVC-MPL Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 2 / 22

Is the Message Initialization Useful? MVC-WP-1: The standard message initialization, i.e., all messages are. Number of Benchmark Instances 25 2 15 1 5 MVC-WP-ER MVC-WP-SF < 8-8 -6-4 -2 2 4 6 8 > 8 (VC Size of MVC-WP - VC Size of MVC-WP-1) / Larger VC Size (%) Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 21 / 22

Agenda Motivation MVC-WP: Warning Propagation-Based Linear-Time-and-Space Algorithms Experimental Evaluation Conclusion and Future Work

Conclusion and Future Work We need a linear-time-and-space algorithm for the MVC problem, because local search algorithms require a good starting vertex cover. We developed MVC-WP, warning propagation-based linear-time-and-space algorithms that find small vertex covers for giant graphs. Our experimental results showed that MVC-WP outperformed other competitors and each step of MVC-WP is important. We have compiled various sets of graphs in many different formats into a set of giant graphs in the DIMACS format: http://files.hong.me/papers/xu218b-data (Future work) Combine MVC-WP with local search algorithms. Apply similar techniques on other combinatorial problems. Xu et al. (University of Southern California) A Warning Propagation-Based Linear-Time-and-Space Algorithm for the MVC Problem 22 / 22

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References II W. Pullan. Optimisation of unweighted/weighted maximum independent sets and minimum vertex covers. In: Discrete Optimization 6.2 (29), pp. 214 219. doi: 1.116/j.disopt.28.12.1. H. D. Sherali and M. Rios. An Air Force Crew Allocation and Scheduling Problem. In: The Journal of the Operational Research Society 35.2 (1984), pp. 91 13. V. V. Vazirani. Approximation Algorithms. Springer, 23. M. Weigt and H. Zhou. Message passing for vertex covers. In: Physical Review E 74.4 (26), p. 4611. doi: 1.113/PhysRevE.74.4611. H. Xu, T. K. S. Kumar, and S. Koenig. A Linear-Time and Linear-Space Algorithm for the Minimum Vertex Cover Problem on Giant Graphs. In: the International Symposium on Combinatorial Search. 217, pp. 173 174.