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Register a new userRouting in Unit Disk Graphs without Dynamic Headers
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Added by
Max Willert
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Let $Vsubsetmathbb{R}^2$ be a set of $n$ sites in the plane. The unit disk graph $DG(V)$ of $V$ is the graph with vertex set $V$ in which two sites $v$ and $w$ are adjacent if and only if their Euclidean distance is at most $1$. We develop a compact routing scheme for $DG(V)$. The routing scheme preprocesses $DG(V)$ by assigning a label $l(v)$ to every site $v$ in $V$. After that, for any two sites $s$ and $t$, the scheme must be able to route a packet from $s$ to $t$ as follows: given the label of a current vertex $r$ (initially, $r=s$) and the label of the target vertex $t$, the scheme determines a neighbor $r$ of $r$. Then, the packet is forwarded to $r$, and the process continues until the packet reaches its desired target $t$. The resulting path between the source $s$ and the target $t$ is called the routing path of $s$ and $t$. The stretch of the routing scheme is the maximum ratio of the total Euclidean length of the routing path and of the shortest path in $DG(V)$, between any two sites $s, t in V$. We show that for any given $varepsilon>0$, we can construct a routing scheme for $DG(V)$ with diameter $D$ that achieves stretch $1+varepsilon$ and label size $O(log Dlog^3n/loglog n)$ (the constant in the $O$-Notation depends on $varepsilon$). In the past, several routing schemes for unit disk graphs have been proposed. Our scheme is the first one to achieve poly-logarithmic label size and arbitrarily small stretch without storing any additional information in the packet.
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Let $S$ be a set of $n$ sites, each associated with a point in $mathbb{R}^2$ and a radius $r_s$ and let $mathcal{D}(S)$ be the disk graph on $S$. We consider the problem of designing data structures that maintain the connectivity structure of $mathcal{D}(S)$ while allowing the insertion and deletion of sites. For unit disk graphs we describe a data structure that has $O(log^2n)$ amortized update time and $O((log n)/(loglog n))$ amortized query time. For disk graphs where the ratio $Psi$ between the largest and smallest radius is bounded, we consider the decremental and the incremental case separately, in addition to the fully dynamic case. In the fully dynamic case we achieve amortized $O(Psi lambda_6(log n) log^{9}n)$ update time and $O(log n)$ query time, where $lambda_s(n)$ is the maximum length of a Davenport-Schinzel sequence of order $s$ on $n$ symbols. This improves the update time of the currently best known data structure by a factor of $Psi$ at the cost of an additional $O(log log n)$ factor in the query time. In the incremental case we manage to achieve a logarithmic dependency on $Psi$ with a data structure with $O(alpha(n))$ query and $O(logPsi lambda_6(log n) log^{9}n)$ update time. For the decremental setting we first develop a new dynamic data structure that allows us to maintain two sets $B$ and $P$ of disks, such than at a deletion of a disk from $B$ we can efficiently report all disks in $P$ that no longer intersect any disk of $B$. Having this data structure at hand, we get decremental data structures with an amortized query time of $O((log n)/(log log n))$ supporting $m$ deletions in $O((nlog^{5}n + m log^{9}n) lambda_6(log n) + nlogPsilog^4n)$ overall time for bounded radius ratio $Psi$ and $O(( nlog^{6} n + m log^{10}n) lambda_6(log n))$ for general disk graphs.
Given a set P of n points in the plane, a unit-disk graph G_{r}(P) with respect to a radius r is an undirected graph whose vertex set is P such that an edge connects two points p, q in P if the Euclidean distance between p and q is at most r. The length of any path in G_r(P) is the number of edges of the path. Given a value lambda>0 and two points s and t of P, we consider the following reverse shortest path problem: finding the smallest r such that the shortest path length between s and t in G_r(P) is at most lambda. It was known previously that the problem can be solved in O(n^{4/3} log^3 n) time. In this paper, we present an algorithm of O(lfloor lambda rfloor cdot n log n) time and another algorithm of O(n^{5/4} log^2 n) time.
Weak unit disk contact graphs are graphs that admit representing nodes as a collection of internally disjoint unit disks whose boundaries touch if there is an edge between the corresponding nodes. In this work we focus on graphs without embedding, i.e., the neighbor order can be chosen arbitrarily. We give a linear time algorithm to recognize whether a caterpillar, a graph where every node is adjacent to or on a central path, allows a weak unit disk contact representation. On the other hand, we show that it is NP-hard to decide whether a tree allows such a representation.
Greedy routing has been studied successfully on Euclidean unit disk graphs, which we interpret as a special case of hyperbolic unit disk graphs. While sparse Euclidean unit disk graphs exhibit grid-like structure, we introduce strongly hyperbolic unit disk graphs as the natural counterpart containing graphs that have hierarchical network structures. We develop and analyze a routing scheme that utilizes these hierarchies. On arbitrary graphs this scheme guarantees a worst case stretch of $max{3, 1+2b/a}$ for $a > 0$ and $b > 1$. Moreover, it stores $mathcal{O}(k(log^2{n} + log{k}))$ bits at each vertex and takes $mathcal{O}(k)$ time for a routing decision, where $k = pi e (1 + a)/(2(b - 1)) (b^2 text{diam}(G) - 1) R + log_b(text{diam}(G)) + 1$, on strongly hyperbolic unit disk graphs with threshold radius $R > 0$. In particular, for hyperbolic random graphs, which have previously been used to model hierarchical networks like the internet, $k = mathcal{O}(log^2{n})$ holds asymptotically almost surely. Thus, we obtain a worst-case stretch of $3$, $mathcal{O}(log^4 n)$ bits of storage per vertex, and $mathcal{O}(log^2 n)$ time per routing decision on such networks. This beats existing worst-case lower bounds. Our proof of concept implementation indicates that the obtained results translate well to real-world networks.
In this article, we study a variant of the minimum dominating set problem known as the minimum liars dominating set (MLDS) problem. We prove that the MLDS problem is NP-hard in unit disk graphs. Next, we show that the recent sub-quadratic time $frac{11}{2}$-factor approximation algorithm cite{bhore} for the MLDS problem is erroneous and propose a simple $O(n + m)$ time 7.31-factor approximation algorithm, where $n$ and $m$ are the number of vertices and edges in the input unit disk graph, respectively. Finally, we prove that the MLDS problem admits a polynomial-time approximation scheme.
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