Abstract
Greedy embedding (or drawing) is a simple and efficient strategy to route messages in wireless sensor networks. For each source-destination pair of nodes s, t in a greedy embedding there is always a neighbor u of s that is closer to t according to some distance metric. The existence of greedy embeddings in the Euclidean plane \({\mathbb {R}}^2\) is known for certain graph classes such as 3-connected planar graphs. We completely characterize the trees that admit a greedy embedding in \({\mathbb {R}}^2\). This answers a question by Angelini et al. (Networks 59(3):267–274, 2012) and is a further step in characterizing the graphs that admit Euclidean greedy embeddings.
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Acknowledgements
M.N. received financial support by the “Concept for the Future” of KIT within the framework of the “German Excellence Initiative”. R.P. was supported by the German Research Foundation (DFG) within the Research Training Group GRK 1194 “Self-Organizing Sensor-Actuator Networks”.
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A preliminary version of this paper appeared in the European Symposium on Algorithms (ESA’13) [18].
Appendix
Appendix
Lemma 4.11 Consider angles \(0^\circ \le \varphi _4 \le 60^\circ \), \(90^\circ < \varphi _3 \le \varphi _2 \le \varphi _1 \le 120^\circ \), \(\varphi _1 + \cdots + \varphi _4 > 360^\circ \). Let the following two conditions hold:
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(i)
\(14 \varphi _1 + 12 \varphi _2 + 8 \varphi _3 + 15 \varphi _4 > 4500^\circ \).
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(ii)
For \(x := \min \Bigg \{ \frac{1}{7} \,(14 \varphi _1 + 12 \varphi _2 + 8 \varphi _3 + 15 \varphi _4 - 4500^\circ ), \varphi _4 \Bigg \}\) and \(p_1 \in [0^\circ , 90^\circ ]^{10}\), \(p_1 = (\beta _0, \ldots , \beta _4, \gamma _0, \ldots , \gamma _4)\) defined as:
$$\begin{aligned} \beta _0&= \varphi _4-x, \\ \beta _1&= 90^\circ - \frac{x}{2},\\ \beta _2&= \varphi _3 + \frac{\varphi _2}{2} + \frac{\varphi _1}{4} + \frac{\varphi _4-x}{8} - 157.5^\circ , \\ \beta _3&= \varphi _2 + \frac{\varphi _1}{2} + \frac{\varphi _4-x}{4} - 135^\circ , \\ \beta _4&= \varphi _1 - 90^\circ + \frac{\varphi _4-x}{2}, \\ \gamma _0&= 90^\circ - \frac{\varphi _4 - x}{2}, \\ \gamma _1&= x, \\ \gamma _2&= 168.75^\circ - \frac{\varphi _3}{2}- \frac{\varphi _2}{4} - \frac{\varphi _1}{8} - \frac{\varphi _4 - x}{16}, \\ \gamma _3&= 157.5^\circ - \frac{\varphi _2}{2} - \frac{\varphi _1}{4} - \frac{\varphi _4-x}{8}, \\ \gamma _4&= 135^\circ - \frac{\varphi _1}{2} - \frac{\varphi _4-x}{4}, \end{aligned}$$it holds: \( \omega (p_1) < 0 \).
Then, \(\{ 180^\circ , \varphi _1, \ldots , \varphi _4\} \in \mathcal P^{5}\).
Proof
Assume both conditions hold. See the construction in Fig. 22. The angles in \(p_1\) are chosen such that all five triangles are equilateral: we have \(\beta _1 = \alpha _1\) and \(\gamma _i = \alpha _i\) for \(i = 0,2,3,4\). Furthermore, \(\beta _0, \gamma _1, \beta _2, \beta _3, \beta _4 \le 60^\circ \). Consider the permutation \(\tau = (4, 0, 3, 2, 1)\). We verify the conditions in Observation 4.3:
We see that \(p_1\) lies in the polytope \(P_\tau =: P\), in particular, \(p_1 \in \partial P\).
We now define another point \(p_2 \in [0^\circ , 90^\circ ]^{10}\). Due to condition (i), there must exist \(90^\circ< \psi _i < \varphi _i\) for \(i=1,\ldots ,3\), \(0^\circ< \psi _4 < \varphi _4\), \(0^\circ< \varepsilon < \psi _4\) (for proper \(\psi _i\), \(\varepsilon \) can be chosen arbitrarily small), such that:
Consider the point \(p_2 = (\overline{\beta _0},\ldots ,\overline{\beta _4},\overline{\gamma _0},\ldots ,\overline{\gamma _4})\), such that:
The condition \(\sum _{i=0}^4 (\overline{\beta }_i + \overline{\gamma }_i) = 540^\circ \) holds, since
due to the choice of \(\psi _i\) and \(\varepsilon \). The rest of the conditions for \(p_2 \in P\) can be easily verified:
Apart from \(\overline{\gamma }_1 \ge 0^\circ \), all inequalities are strict. Since \(\gamma _1 > 0^\circ \), for each \(\lambda \in (0,1)\), the point \(\lambda p_1 + (1-\lambda ) p_2\) lies in the interior of P. Since \(\omega (p_1) < 0\) and \(\omega (p_2) > 0\) (due to \(\overline{\gamma }_1 = 0^\circ \)), by the mean value theorem, \(\omega (\lambda p_1 + (1-\lambda ) p_2) = 0\) for some \(\lambda \in (0,1)\). \(\square \)
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Nöllenburg, M., Prutkin, R. Euclidean Greedy Drawings of Trees. Discrete Comput Geom 58, 543–579 (2017). https://doi.org/10.1007/s00454-017-9913-8
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DOI: https://doi.org/10.1007/s00454-017-9913-8