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Hovhannes Harutyunyan

Publications and source records attributed to Hovhannes Harutyunyan.

2 recordsLinked to original sources

Sparse Relaxed Broadcast Graphs

Broadcasting in graphs refers to the information dissemination problem in which a source node has an atomic piece of information to be distributed to all the nodes of a graph. In the standard telephone model, broadcasting proceeds as a sequence of synchronous rounds, where, at each round, every informed node can transfer the information to at most one of its neighbors. The broadcast time of a graph $G$ is the maximum, taken over every node $v\in V(G)$, of the minimum number of rounds required for broadcasting from $v$ in $G$. We study the network design problem that, for every $ε> 0$, asks for the minimum number of edges of $n$-node graphs with broadcast time close to optimal, i.e., at most $(1+ε)\log_2n$. Let $ϕ=(1+\sqrt{5})/2$ be the golden ratio, and let $α=1/\log_2ϕ-1\simeq 0.44$. We show that, for every $n\geq 1$, and for every $ε\in(0,α)$, it suffices to add $O(n^{1-ε/α})$ edges to a well chosen $n$-node tree for designing an $n$-node graph with broadcast time $(1+ε)\log_2n$. This asymptotic bound on the additional number of edges improves the previsouly known bound $O(n^{1-ε})$, and has implications to the design of graphs with minimum broadcast cost, defined as number of edges times broadcast time. Moreover, we show that, for infinitely many values of $n$, $Ω(n)$ edges must be added to some tree for designing an $n$-node graph with broadcast time $\lceil\log_2 n\rceil+1$. Therefore, our bound $O(n^{1-ε/α})$ on the additional number of edges for $0<ε<α$ is asymptotically tight at the two extremities of the interval $(0,α]$, as it is $O(n)$ when $ε\to 0$, and $O(1)$ when $ε=α$. Finally, we show that, for every $n$, there exists an $n$-node graph with broadcast time $\lceil\log_2 n\rceil+1$ and at most $2n-4\lceil\log_2n\rceil+O(1)$ edges.

cs.DM↗

Online Domination: The Value of Getting to Know All your Neighbors

We study the dominating set problem in an online setting. An algorithm is required to guarantee competitiveness against an adversary that reveals the input graph one node at a time. When a node is revealed, the algorithm learns about the entire neighborhood of the node (including those nodes that have not yet been revealed). Furthermore, the adversary is required to keep the revealed portion of the graph connected at all times. We present an algorithm that achieves 2-competitiveness on trees and prove that this competitive ratio cannot be improved by any other algorithm. We also present algorithms that achieve 2.5-competitiveness on cactus graphs, $(t-1)$-competitiveness on $K_{1,t}$-free graphs, and $Θ(\sqrtΔ)$ for maximum degree $Δ$ graphs. We show that all of those competitive ratios are tight. Then, we study several more general classes of graphs, such as threshold, bipartite planar, and series-parallel graphs, and show that they do not admit competitive algorithms (that is, when competitive ratio is independent of the input size). Previously, the dominating set problem was considered in a slightly different input model, where a vertex is revealed alongside its restricted neighborhood: those neighbors that are among already revealed vertices. Thus, conceptually, our results quantify the value of knowing the entire neighborhood at the time a vertex is revealed as compared to the restricted neighborhood. For instance, it was known in the restricted neighborhood model that 3-competitiveness is optimal for trees, whereas knowing the neighbors allows us to improve it to 2-competitiveness.

cs.DS↗