Brief Announcement: Rapid Mixing of Local Dynamics on Graphs

In peer-to-peer networks, it is desirable that the logical topology of connections between the constituting nodes make a well-connected graph, i.e., a graph with low diameter and high expansion. At the same time, this graph should evolve only through local modifications. These requirements prompt the following question: are there local graph dynamics that i) create a well-connected graph in equilibrium, and ii) converge rapidly to this equilibrium? In this paper we provide an affirmative answer by exhibiting a local graph dynamic that mixes provably fast. Specifically, for a graph on N nodes, mixing has occurred after each node has performed O(polylog(N)) operations. This is in contrast with previous results, which required at least Omega(N polylog(N)) operations per node before the graph had properly mixed

Rapid Mixing of Local Dynamics on Graphs

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Finding a Bounded-Degree Expander Inside a Dense One

International audienceIt follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V,E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V,E_H)$ of $G$ of constant maximum degree which is also an expander. As with other consequences of the MSS theorem, it is not clear how one would explicitly construct such a subgraph. We show that such a subgraph (although with quantitatively weaker expansion and near-regularity properties than those predicted by MSS) can be constructed with high probability in linear time, via a simple algorithm. Our algorithm allows a distributed implementation that runs in $\mathcal O(\log n)$ rounds and does $\mathcal O(n)$ total work with high probability. The analysis of the algorithm is complicated by the complex dependencies that arise between edges and between choices made in different rounds. We sidestep these difficulties by following the combinatorial approach of counting the number of possible random choices of the algorithm which lead to failure. We do so by a compression argument showing that such random choices can be encoded with a non-trivial compression. Our algorithm bears some similarity to the way agents construct a communication graph in a peer-to-peer network, and, in the bipartite case, to the way agents select servers in blockchain protocols

Expanders via Local Edge Flips

Designing distributed and scalable algorithms to improve network connectivity is a central topic in peer-to-peer networks. In this paper we focus on the following well-known problem: given an n-node d-regular network for d = Ω(log n), we want to design a decentralized, local algorithm that transforms the graph into one that has good connectivity properties (low diameter, expansion, etc.) without affecting the sparsity of the graph. To this end, Mahlmann and Schindelhauer introduced the random “flip” transformation, where in each time step, a random pair of vertices that have an edge decide to ‘swap a neighbor’. They conjectured that performing O(nd) such flips at random would convert any connected d-regular graph into a d-regular expander graph, with high probability. However, the best known upper bound for the number of steps is roughly O(n17d23), obtained via a delicate Markov chain comparison argument. Our main result is to prove that a natural instantiation of the random flip produces an expander in at most steps, with high probability. Our argument uses a potential-function analysis based on the matrix exponential, together with the recent beautiful results on the higher-order Cheeger inequality of graphs. We also show that our technique can be used to analyze another well-studied random process known as the ‘random switch’, and show that it produces an expander in O(nd) steps with high probability

Expanders via local edge flips in quasilinear time

International audienceMahlmann and Schindelhaue [24] proposed the following simple process, called flip-chain, for transforming any given connected d-regular graph into a d-regular expander: In each step, a random 3-path abcd is selected, and edges ab and cd are replaced by two new edges ac and bd, provided that ac and bd do not exist already. A motivation for the study of the flip-chain arises in the design of overlay networks, where it is common practice that adjacent nodes periodically exchange random neighbors, to maintain good connectivity properties. It is known that the flip-chain converges to the uniform distribution over connected d-regular graphs, and it is conjectured that an expander graph is obtained after O(nd log n) steps, w.h.p., where n is the number of vertices. However, the best known upper bound on the number of steps is O(n^2 d^2 √ log n) [1], and the best bound on the mixing time of the chain is O(n^16 d^36 log n) [11, 6]. We provide a new analysis of a natural flip-chain instantiation, which shows that starting from any connected d-regular graph, for d = Ω(log^2 n), an expander is obtained after O(nd log^2 n) steps, w.h.p. This result is tight within logarithmic factors, and almost matches the conjectured bound. Moreover, it justifies the use of edge flip operations in practice: for any d-regular graph with d = poly(log n), an expander is reached after each vertex participates in at most poly(log n) operations, w.h.p. Our analysis is arguably more elementary than previous approaches. It uses the novel notion of the strain of a cut, a value that depends both on the crossing edges and their adjacent edges. By keeping track of the cut strains, we form a recursive argument that bounds the time before all sets of a given size have large expansion, after all smaller sets have already attained large expansion