The Max-Distance Network Creation Game on General Host Graphs

In this paper we study a generalization of the classic \emph{network creation game} in the scenario in which the $n$ players sit on a given arbitrary \emph{host graph}, which constrains the set of edges a player can activate at a cost of $\alpha \geq 0$ each. This finds its motivations in the physical limitations one can have in constructing links in practice, and it has been studied in the past only when the routing cost component of a player is given by the sum of distances to all the other nodes. Here, we focus on another popular routing cost, namely that which takes into account for each player its \emph{maximum} distance to any other player. For this version of the game, we first analyze some of its computational and dynamic aspects, and then we address the problem of understanding the structure of associated pure Nash equilibria. In this respect, we show that the corresponding price of anarchy (PoA) is fairly bad, even for several basic classes of host graphs. More precisely, we first exhibit a lower bound of $\Omega (\sqrt{ n / (1+\alpha)})$ for any $\alpha = o(n)$. Notice that this implies a counter-intuitive lower bound of $\Omega(\sqrt{n})$ for very small values of $\alpha$ (i.e., edges can be activated almost for free). Then, we show that when the host graph is restricted to be either $k$-regular (for any constant $k \geq 3$), or a 2-dimensional grid, the PoA is still $\Omega(1+\min\{\alpha, \frac{n}{\alpha}\})$, which is proven to be tight for $\alpha=\Omega(\sqrt{n})$. On the positive side, if $\alpha \geq n$, we show the PoA is $O(1)$. Finally, in the case in which the host graph is very sparse (i.e., $|E(H)|=n-1+k$, with $k=O(1)$), we prove that the PoA is $O(1)$, for any $\alpha$.Comment: 17 pages, 4 figure

Multiple-Edge-Fault-Tolerant Approximate Shortest-Path Trees

Let $G$ be an $n$-node and $m$-edge positively real-weighted undirected graph. For any given integer $f \ge 1$, we study the problem of designing a sparse \emph{f-edge-fault-tolerant} ($f$-EFT) $\sigma${\em -approximate single-source shortest-path tree} ($\sigma$-ASPT), namely a subgraph of $G$ having as few edges as possible and which, following the failure of a set $F$ of at most $f$ edges in $G$, contains paths from a fixed source that are stretched at most by a factor of $\sigma$. To this respect, we provide an algorithm that efficiently computes an $f$-EFT $(2|F|+1)$-ASPT of size $O(f n)$. Our structure improves on a previous related construction designed for \emph{unweighted} graphs, having the same size but guaranteeing a larger stretch factor of $3(f+1)$, plus an additive term of $(f+1) \log n$. Then, we show how to convert our structure into an efficient $f$-EFT \emph{single-source distance oracle} (SSDO), that can be built in $\widetilde{O}(f m)$ time, has size $O(fn \log^2 n)$, and is able to report, after the failure of the edge set $F$, in $O(|F|^2 \log^2 n)$ time a $(2|F|+1)$-approximate distance from the source to any node, and a corresponding approximate path in the same amount of time plus the path's size. Such an oracle is obtained by handling another fundamental problem, namely that of updating a \emph{minimum spanning forest} (MSF) of $G$ after that a \emph{batch} of $k$ simultaneous edge modifications (i.e., edge insertions, deletions and weight changes) is performed. For this problem, we build in $O(m \log^3 n)$ time a \emph{sensitivity} oracle of size $O(m \log^2 n)$, that reports in $O(k^2 \log^2 n)$ time the (at most $2k$) edges either exiting from or entering into the MSF. [...]Comment: 16 pages, 4 figure