A critical point for random graphs with a given degree sequence
Random Graphs 93 Proceedings of the sixth international seminar on Random graphs and probabilistic methods in combinatorics and computer science
The strong convergence of maximal degrees in uniform random recursive trees and dags
Random Structures & Algorithms
The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
The degree sequence of a scale-free random graph process
Random Structures & Algorithms
Random Structures & Algorithms
The Diameter of a Scale-Free Random Graph
Combinatorica
Percolation Search in Power Law Networks: Making Unstructured Peer-to-Peer Networks Scalable
P2P '04 Proceedings of the Fourth International Conference on Peer-to-Peer Computing
The Maximum Degree of the Barabási–Albert Random Tree
Combinatorics, Probability and Computing
Analyzing and characterizing small-world graphs
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Distance estimation and object location via rings of neighbors
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
The Volume of the Giant Component of a Random Graph with Given Expected Degrees
SIAM Journal on Discrete Mathematics
Could any graph be turned into a small-world?
Theoretical Computer Science - Complex networks
Object location using path separators
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
Greedy routing in tree-decomposed graphs
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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We investigate the complexity of searching for a given vertex in a scale-free graph, using only locally gathered information. In such graphs, the number of nodes of degree x is proportional to x-β for some constant β 0. We consider two random scale-free graph models: the Chung-Lu model and the Móri model (a generalization of the Barabási-Albert model) proving two lower bounds of Ω(n/ logΘ(β) n) and Ω(n1/2) on the expected time to find the worst-case target, under a restrictive model of local information.