Rectangle-of-influence triangulations

Size: px
Start display at page:

Download "Rectangle-of-influence triangulations"

Transcription

1 CCCG 2016, Vancoer, British Colmbia, Ag 3 5, 2016 Rectangle-of-inflence trianglations Therese Biedl Anna Lbi Saeed Mehrabi Sander Verdonschot 1 Backgrond The concept of rectangle-of-inflence (RI) draings is old and ell-stdied in the area of graph draing. A graph has sch a draing if e can assign points to its ertices sch that for eery edge (, ) the spporting rectangle (i.e., the minimal closed axis-aligned rectangle R(, ) containing and ) contains no other points. In the original setp, the graph had to hae an edge for eery pair of points ith an empty spporting rectangle (the strong model, see e.g. [8]). Later papers focs on eak RI-draings, here for eery edge the spporting rectangle mst be empty, bt not all sch edges mst exist. Of particlar interest are planar eak RI-draings of planar graphs, since these can alays be deformed to reside on an n n-integer grid. See e.g. [9, 1]. Or Reslts: In this paper, e take to comptational geometry problems ho to trianglate a point set and ho to flip beteen to geometric trianglations and apply them in the setting of rectangle-of-inflence draings. In particlar, e sho that any point set can be trianglated (ith some exceptions near the conex hll edges, hich e sho to be necessary) sch that the reslting planar straightline graph (PSLG) is an RI-draing. Next, e trn to the problem of flipping among geometric trianglations, i.e., conerting one trianglation into another throgh the operation of flipping the diagonal of one qadrangle. We sho that any RI-trianglation can be conerted into any other RI-trianglation by O(n 2 ) sch flipping-operations (and Ω(n 2 ) flips are reqired for some RI-trianglations). Moreoer, all intermediate trianglations are also RI-trianglations. The main idea is that the L -Delanay-trianglation (defined belo) is an RI-trianglation; it hence sffices to find one flip-operation that gets the RI-trianglation closer to the L -Delanay-trianglation in some sense. We also stdy ho to flip from any trianglation to an RItrianglation hile getting closer. Existing literatre: Trianglating point sets and polygons is one of the standard problems in comptational geometry. Any set of n points can be tri- Daid R. Cheriton School of Compter Science, Uniersity of Waterloo, Waterloo, ON N2L 3G1, Canada, {albi,biedl, s2mehrabi}@aterloo.ca. TB and AL spported by NSERC. Comptational Geometry Lab, School of Compter Science, Carleton Uniersity, Ottaa, Ontario, Canada. sander@cg.scs.carleton.ca anglated in O(n log n) time (e.g. by compting the Delanay trianglation), and the interior of a polygon can be trianglated in O(n) time [4]. The Delanay trianglation has been generalied to other nit discs. In particlar, for any conex compact shape C, the C-Delanay-trianglation is a trianglation sch that for eery edge (, ) there exists a homothet of C that contains and and no other points [5]. Arenhammer and Palini [2] stdied a nmber of their properties. If C is a nit sqare (i.e., the nit-circle in the L -metric), then this trianglation is called the L -Delanay-trianglation. The L -Delanaytrianglation can be compted in O(n log n) time [5]. Obsere that the L -Delanay-trianglation is an RItrianglation, bt an RI-trianglation need not be a C-Delanay-trianglation for any C becase the spporting rectangles are not necessarily homothets of each other or expandable into sch. Flipping among trianglations is also a ell-stdied problem; see [3] for an oerie of many ariants and existing reslts. It is ery easy to see that any (geometric) trianglation T 1 can be flipped into any other trianglation T 2 ia the intermediary of the Delanay trianglation T D : We can alays find a flip that gets s closer to the Delanay trianglation (in the sense that some angle-sm increases), so keep flipping from T 1 ntil e reach T D. Also compte the flips from T 2 to T D, and reersing these flips and combining the to flip-seqences then gies the reslt. For C-Delanaytrianglations, a similar reslt holds: e can alays flip to get closer to the C-Delanay-trianglation [2]. Notation: Let P be a set of n points that e assme to be in general position in the sense that no to points are on a horiontal or ertical line, and no 4 points are on a sqare. For any to points p, q P, define the spporting rectangle R(p, q) to be the minimal axis-aligned rectangle containing p and q. Define a spporting sqare S(p, q) to be a minimal axis-aligned sqare containing p and q; S(p, q) is not niqe. For any to points p, q P, e call a spporting rectangle/sqare of (p, q) empty if it contains no points of P other than p and q. An edge (p, q) beteen points of P is called an RIedge (L -edge) if R(p, q) is empty (resp., some spporting sqare S(p, q) is empty). Note that an L - edge is an RI-edge. An RI-polygon is a polygon for hich eery edge is an RI-edge. A planar straight-line graph (PSLG) is a trianglation if eery interior face

2 28 th Canadian Conference on Comptational Geometry, 2016 a Figre 1: (Left) A trianglation. (, ) is not locally RI. (, ) is locally L (therefore locally RI), bt not globally L. (Right) A polygon (solid) ith its trapeoidation (thin dashed). Edge (b, f) old be added ith the first method, edge (c, e) ith the second. of the PSLG is a triangle. An RI-trianglation (L - trianglation) is a trianglation for hich eery edge is an RI-edge (L -edge). We sometimes se nrestricted trianglation for a trianglation that need not be an RI-trianglation. A trianglation is maximal if it contains as many edges as possible hile staying ithin the additional reqirements that e impose. Ths, a maximal RI-trianglation is an RI-trianglation ith as many edges as possible hile haing only RI-edges, and similarly for maximal L -trianglations. For an edge (, ) in a trianglation, ertex is facing (, ) if there exists an interior face {,, }. Eery interior edge has exactly to ertices facing it. We say that (, ) is locally RI (resp. locally L ) if R(, ) (resp.. some spporting sqare S(, )) contains none of the ertices facing (, ). Sometimes e say that an RI-edge (L -edge) is globally RI (globally L ). 2 RI-trianglating an RI-polygon We first sho that any RI-polygon P can be RItrianglated, i.e., made into a trianglation by adding only RI-edges in its interior (presming no extra points are inside P ). To do so, first find a trapeoidation of P, i.e., extend ertical sbdiision lines from all ertices. This can be done in linear time [4]. We add RI-edges in to ays. First, check hether there is any trapeoid that has ertical sbdiision lines on both its left and right sides, and for hich the to ertices, that cased these lines are on opposite sides (top/bottom) of the trapeoid. If so, add the diagonal (, ). This is an RI-edge since R(, ) is contained ithin the spporting rectangles of the top and bottom edge of T and the interior of P, all of hich are empty. See edge (b, f) in Fig. 1. Secondly, if no sch trapeoid exists, then any remaining face is x-monotone, i.e., it consists of to x- monotone chains from left to right. Since the first method does not apply, one of the to chains is a single edge. Consider one sch piece ith (say) the bottom chain a single edge (, ). All ertices in the top chain f b c d e C IV C I C III Q C II Figre 2: The maximal-hll of a set of points, and ho to add corner-points and edges to them. are otside R(, ) and hence hae larger x-coordinate than,. Let be a local maximm in the top chain, and connect the neighbors of. The ne edge is an RI-edge, becase its spporting rectangle is contained in the nion of the ones of the edges incident to as ell as R(, ) and the interior of P. See edge (c, e) in Fig. 1 (ith =f, =e, =d). So e add RI-edges ntil all interior faces are triangles. This takes linear time (once the trapeoidation is fond), since finding the local minimm/maximm for the second rle can be done in O(1) amortied time. Theorem 1 Eery RI-polygon can be trianglated sing only RI-edges in linear time. 3 Oter face considerations The remaining sections deal ith trianglations of point sets, rather than polygons. Here there arise some complications at the oter face. For any maximal (nrestricted) trianglation of P, the oter face consists of the conex hll CH (P ). If some edge of CH (P ) is not an RI-edge, then it obiosly cannot be in an RItrianglation. We begin by characteriing the oter face of any RI-trianglation. The maxima-hll: We need some definitions that are closely related to the rectilinear conex hll (see e.g. [10]) and the maxima of a set of ectors (see e.g. [7]). Define a first qadrant of a point p to be the set {(x, y) : x x(p), y y(p)}. Define the first-qadrantchain C I to be all those points p in P for hich the first qadrant relatie to p contains no other points of P ; e sort these points by increasing x-coordinate (hence by decreasing y-coordinate), and connect them ith straight-line segments in this order. Similarly define three other chains C II, C III, C IV sing the three other types of qadrants. Note that C I and C II share one endpoint (the one ith maximm x-coordinate), and similarly for the other chains, so e can combine the for polygonal chains into one closed polygonal chain that e call the maxima-hll MH (P ). Note that some chains may hae edges in common, bt no to edges cross, so MH (P ) may self-oerlap bt it has a elldefined interior region. See Fig. 2. II III I IV

3 CCCG 2016, Vancoer, British Colmbia, Ag 3 5, 2016 In the appendix, e proe the folloing. Lemma 2 For any point set P, the maxima-hll consists of L -edges (hence RI-edges). Lemma 3 For any point set P, any RI-edge (, ) is ithin the region bonded by MH (P ). Combining them gies: Corollary 1 An RI-trianglation is maximal if and only if its oter face consists of the maxima-hll. Adding corner-points: It ill be cmbersome to deal directly ith edges that are on the conex hll bt not RI-edges. To simplify or life, e add points as follos. For any point set P, let P + be the set obtained by adding for corner-points I, II, III, IV that form an axis-aligned rectangle (e rotate it slightly to be in general position) and are otside the bonding box of P, ith i in the ith qadrant relatie to all points of P. See Fig. 2. Notice that the conex hll of P + consists of L -edges. Lemma 4 Let T + be a maximal RI-trianglation of P +, and let T := T + { I, II, III, IV }. Then T is a maximal RI-trianglation of T. Proof. Clearly any edge of T is an RI-edge, so e only need to arge maximality. Assme (p, I ) is an edge in T + for some p II, III, IV. Then R(p, I ) contains no other point, and is to the right and/or aboe II, III, IV. So expanding R(p, I ) into the first qadrant of p does not add points of P, hence p is on the maxima-hll. So remoing { I, II, III, IV } from T + leaes an RI-trianglation here the oter face is the maxima-hll. By Corollary 1 this is maximal. 4 RI-trianglating a point set In this section, e stdy ho to find a maximal RItrianglation of a gien point set. It is obios that this exists (for example the L -Delanay trianglation ill do), bt or algorithm is especially simple. Theorem 5 A maximal RI-trianglation of a point set P can be compted in O(n log n) time, or O(n) time if P is sorted by x-coordinate. Proof. As before, add corner-points I, II, III, IV to obtain point set P +. Sort the points by x- coordinates, and add an edge beteen any to consectie points; these are clearly RI-edges. Also add the cycle I, II, III, IV ; these are also RI-edges. No e hae a PSLG hose faces consist of RI-polygons. Trianglate each polygon ith Theorem 1. We obtain an RI-trianglation T + of P +, and it is clearly maximal since all conex-hll edges are in it. By Lemma 4, deleting the for corner-points gies the reslt. 5 Flipping and RI-trianglations In this section, e inestigate flipping hile maintaining RI-trianglations or (if e start ith an nrestricted one) getting closer to an RI-trianglation. The natral intermediary here is the L -Delanay trianglation, hich is an RI-trianglation. So e sho that any trianglation can be flipped to an RI-trianglation hile getting closer, and then that any RI-trianglation can be flipped to the L -Delanay trianglation hile remaining an RI-trianglation throghot. 5.1 Flipping to an RI-trianglation Let P + be a point set for hich any conex hll edge is an RI-edge (e ill arge later ho to remoe this assmption). Let T be an arbitrary trianglation of P +. A bad triangle {,, } in T is a face {,, } sch that R(, ). After possible rotation, assme that is in the 2nd qadrant and is in the 4th qadrant relatie to, ith edge (, ) roted aboe. Define the special region of bad triangle {,, } to be all points p aboe (, ) ith x() x(p) x() (inclding ) and all points p to the right of (, ) ith y() x(p) y() (inclding ). See Fig. 3(a). The definition is symmetric for the other three possible rotations of a bad triangle. No define for any trianglation T the potential fnction Φ(T ) to be the sm, oer all bad triangles {,, }, of the nmber of points in the special region of {,, }. Lemma 6 Let T be any trianglation of P + ith Φ(T ) > 0. Then there exists an edge in T that e can flip so that the reslting trianglation T satisfies Φ(T ) < Φ(T ). Proof. Since Φ(T ) > 0, it mst hae at least one bad triangle, and hence edges that are not locally RI. Of all those edges, let (, ) be the one that maximies the L 1 -distance beteen its endpoints, ths x() x() + y() y() is maximm among all edges that are not locally RI. Since conex hll edges are RI-edges, e kno that (, ) is an interior edge and has to facing ertices. Let be a ertex facing (, ) that is in R(, ), and assme again that (after possible rotation) the bad triangle {,, } has (or ) in the 2nd (4th) qadrant of ith (, ) aboe. Let be the other ertex facing (, ). We claim that x() > x(). We kno that is aboe the line throgh (, ) since {,, } is a face. If e had x() < x(), then R(, ), and so (, ) is not locally RI bt its L 1 -distance is longer than the one of (, ), contradicting or choice of edge (, ). Therefore e kno x() > x(), and symmetrically one arges y() > y(). Notice that therefore qadrilateral {,,, } is conex and so edge (, ) is flippable. We claim that regardless of the position of, doing this

4 28 th Canadian Conference on Comptational Geometry, 2016 Lemma 7 Let T be a trianglation sch that all edges are locally RI and all oter face edges are globally RI. Then all edges are globally RI. (a) (b) Proof. Sppose that some edges of T are not globally RI, hence contain points inside their spporting rectangles. Let e = (, ) be the edge ith the closest sch point, say. Since e is an interior edge by assmption, it has to facing ertices; let be the ertex facing e that is on the same side of the spporting line of e as is. Sppose that and lie right of e, and is the left endpoint of e; see Fig. 1. Obsere that mst lie either aboe R(, ) (ithin the same x-range) or to the right of R(, ) (ithin the same y-rage), else some edge of {,, } old not be locally RI or {,, } old not be a face. Assme lies strictly aboe R(, ), ithin the same x-range. Then (, ) is also not globally RI, since lies in R(, ). Bt is closer to (, ) than to e, contradicting or choice of e. (c) Figre 3: (a) The special region (shaded) of bad triangle {,, }. (b-d) Possible positions of the other facing ertex. Light gray regions ere in the special region of the bad triangle {,, }. (d) flip improes the potential fnction. To sho this, e distingish here is located x() > x(), y() > y() (see Fig. 3(b)): In this case, neither of the to ne triangles {,, } and {,, } is bad. Since triangle {,, } sed to be bad, Φ decreases by at least 2. x() > x(), y() < y() (see Fig. 3(c)): In this case, the ne triangle {,, } is bad, bt {,, } is not. The special region of triangle {,, } is a strict sbset of the one for triangle {,, }, and in particlar, excldes. Hence Φ decreases. R(, ) (see Fig. 3(d)): In this case, both ne triangles {,, } and {,, } are bad. Bt both triangles {,, } and {,, } that ere remoed ere bad, and the special regions of the ne triangles are strict sbsets of the special regions of the old triangles that, in particlar, contain and only once, instead of tice. So again Φ decreases. The cases for x() < x(), y() > y() and for R(, ) are symmetric. Note in particlar that if Φ(T ) = 0, then it has no bad triangles (becase any bad triangle has at least to points in its special region); therefore it has no edge that is not locally RI. Ptting the to lemmas together, e can hence flip from any trianglation to an RI-trianglation hile steadily improing the potential-fnction. Initially there are O(n) bad triangles, each of hich defines a special region containing at most n points, so Φ(T ) O(n 2 ). Each flip improes the fnction, and e are done hen it is 0, hich means that the nmber of flips is O(n 2 ). We smmarie: Lemma 8 Any maximal trianglation of P + can be conerted into an RI-trianglation of P + sing O(n 2 ) flips. We arge in the appendix that this bond is sometimes tight. Lemma 9 There are trianglations that cannot be conerted into an RI-trianglation ith o(n 2 ) flips. Proof. Consider a set of points spread eenly oer to opposing conex chains, sch that the only possible RIedges beteen the to chains connect point i on the first chain to point i and i + 1 on the opposing chain (see Fig. 4). The edges connecting consectie points on each chain are not intersected by any other possible edge, hich implies that these edges are present in eery trianglation and can neer be flipped. Ths, the region beteen the to chains is independent of the otside regions. Frther, by constrction, this center region has a niqe RI-trianglation (Fig. 4, right). No consider a trianglation that incldes the long diagonal connecting one end of the first conex chain to the opposite end of the other chain (Fig. 4, left). Transforming this trianglation into the niqe RI-trianglation reqires Ω(n 2 ) flips, by an argment analogos to the one gien by Hrtado et al. [6, Theorem 3.8]

5 CCCG 2016, Vancoer, British Colmbia, Ag 3 5, 2016 Figre 4: Trning the trianglation on the left into an RI-trianglation reqires Ω(n 2 ) flips for the region beteen the chains to become the only possible RItrianglation shon on the right. Arbitrary point sets: It remains to arge ho to handle point sets P here not all conex-hll edges are RI-edges. Assme e are gien a maximal trianglation T of P, and e old like to flip that to a maximal RItrianglation T R. Add corner-points I, II, III, IV as before to obtain point set P + and connect them in a cycle. Connect i (for i {I, II, III, IV }) to all points p on the conex hll of P for hich qadrant i contains only p and i. This gies a trianglation T + of P + becase the conex hll is the oter face T. See Fig. 2. The conex hll of P + consists of RI-edges, so there exists a seqence σ of flips that trns T + into a maximal RI-trianglation T + R. Lemma 10 Throghot flip-seqence σ, all edges incident to corner-points are RI-edges. Therefore any edge being flipped is not incident to a corner-point. Proof. The first claim implies the second becase flipped edges ere not locally RI. We proe the first claim for I only. Apart from the edges to II and IV, ertex I has an edge only to a point p for hich the first qadrant is empty, so R( I, p) is empty and the claim holds. We no sho that any time e flip an edge (, ) sch that the ne edge is (, I ) for some,,, this ne edge is an RI edge. Since I is otside the bonding box of P, it is otside R(, ). Since (, ) as not locally RI (by or choice of edges to flip), therefore R(, ). In the naming of Fig. 3, e hae I = and the case of Fig. 3(b) applies since I is in the first qadrant of. We already kne that in this case (, ) is locally RI. Bt since = I, edge (, ) is globally RI: R(, I ) lies ithin the nion of R(, I ) and R(, I ) (both empty, becase these edges are incident to I and hence RI-edges), and the interior of triangles {,, } and {, I, } (hich are faces). We no create a seqence of flips and edge deletions for T that leads to a maximal RI-trianglation by mirroring the flip-seqence of T +. We maintain the claim that at any time trianglation T eqals T + ith the corner-points remoed. Clearly this holds initially. Say the next flip for T + as to flip (, ) to (, ). We kno, P. If, P, then (by indction) the 4-cycle,,, that exists in T + also exists in T, and so e can do the exact same flip in T and the claim holds. Else, one of, is a corner-point. Do an edge-deletion in T, i.e., remoe edge (, ) ithot adding a ne one. The claim still holds since one end of (, ) is not in P. We end ith a trianglation T R of P that eqals T + R ith the corner-points remoed. By Lemma 4, this is a maximal RI-trianglation. Theorem 11 We can conert any maximal trianglation into an RI-trianglation by doing O(n 2 ) flips and O(n) edge-deletions. 5.2 Flipping beteen RI-trianglations As explained earlier, to flip beteen maximal RItrianglations hile maintaining an RI-trianglation, it sffices to sho that eery maximal RI-trianglation can be flipped into the L -Delanay-trianglation. To proe this, e se again a potential-fnction argment, bt ith a different fnction. We need the folloing: Lemma 12 [2] Let T be a maximal trianglation here all edges are locally L. Then all edges are globally L. Or potential fnction depends on haing fixed, for eery edge (, ) of the crrent trianglation, a particlar spporting sqare S(, ), and conting the nmber of points of P in it. We define Ψ(T ) to be the sm, oer all edges (, ) of the nmber of points in S(, ). When e flip, e are free to choose a spporting sqare for the ne edge. Lemma 13 Let T be a maximal RI-trianglation that is not the L -Delanay trianglation. There exists an edge e sch that flipping e reslts in an RI-trianglation T and e can assign a spporting sqare to e sch that Ψ(T ) < Ψ(T ). Proof. By Lemma 12 T has some edge (, ) that is not locally L. Up to symmetry, e may assme that the height Y of R(, ) is no smaller than its idth. All spporting sqares of (, ) are then in the horiontal strip H of height Y beteen and. Since T is a maximal RI-trianglation, its oter face is the maxima-hll and consists of L -edges. So (, ) is an interior edge. Let and the to ertices facing (, ). We claim that both and mst be in strip H. To see this, recall that e hae an RI-trianglation, and hence rectangle R(, ) is empty. This rectangle bisects strip H. So if, say, is not in H, then at most one facing ertex is in H, hich means that to one side of R(, ) in H there is no facing ertex of (, ). We cold hence pick a spporting sqare S of (, ) that consists of

6 28 th Canadian Conference on Comptational Geometry, 2016 to the L -Delanay-trianglation hile maintaining an RI-trianglation. H S(, ) This bond is tight. Fig. 6 shos to RItrianglations of a point set that forms to conex chains. Hrtado et al. [6, Theorem 3.8] shoed that their flip distance is Ω(n 2 ) een ithot the restriction of sing only RI-trianglations. R Figre 5: Finding a spporting sqare for (, x). R(, ) extended to that side. Then S contains neither nor, and (, ) old be locally L, a contradiction. So both and are in strip H. By planarity they mst be on opposite sides of R(, ), say is to the left and is to the right. Qadrangle {,,, } hence is dran conex and edge (, ) is flippable. Define R be the minimm rectangle containing,,,, and notice that it is contained in the nion of the spporting rectangles of the edges (, ), (, ), (, ), (, ), (, ). Since e had an RI-trianglation, therefore R contains no points other than these 4. Also,,, are all on the bondary of R. Therefore R(, ) is empty and the ne edge (, ) is an RI-edge. No e explain ho to find a spporting sqare for (, ). Let X be the idth of R, and notice that X < Y, since X = Y old imply for points on a sqare and X > Y old mean that some sqare ithin R spports (, ) and does not contain,, contradicting that (, ) is not locally L. No consider the nion of R and the sqare S(, ) that as sed as spporting sqare for (, ). Since (, ) as not locally L, at least one of {, } is in S(, ), hence S(, ) R contains at most one more point than S(, ). Let R be the rectangle obtained by shrinking S(, ) R to height Y ε in sch a ay that, R. We choose ε so small that and remain in R and sch that Y ε > X. So R contains at least one feer points than S(, ). Finally shrink R in idth ntil it is a sqare; e can do this and retain and in it, since R is taller than R is ide. Using the reslting sqare for S(, ) decreases Ψ as desired. Theorem 14 Any maximal RI-trianglation T can be conerted into any other maximal RI-trianglation T by doing O(n 2 ) flips, and all intermediate trianglations are maximal RI-trianglations. Proof. As before it sffices to arge this if T is the L -Delanay trianglation. Compte an arbitrary set of spporting sqares for T. Initially there are O(n) edges in the trianglation, each of hich has at most n points in its spporting sqare, so Ψ(T ) O(n 2 ). Applying the aboe flip means that ith O(n 2 ) flips e get Figre 6: A pair of RI-trianglations sch that Ω(n 2 ) flips are reqired to transform one into the other. References [1] S. Alamdari and T. Biedl. Open rectangleof-inflence draings of non-trianglated planar graphs. In Proc. GD 12, pages , [2] F. Arenhammer and G. Palini. On shape Delanay tessellations. Inf. Process. Lett., 114(10): , [3] P. Bose and F. Hrtado. Flips in planar graphs. Compt. Geom., 42(1):60 80, [4] B. Chaelle. Trianglating a simple polygon in linear time. Discrete Compt. Geom., 6: , [5] R. Drysdale. A practical algorithm for compting the Delanay trianglation for conex distance fnctions. In Proc. SODA 90, pages , [6] F. Hrtado, M. Noy, and J. Urrtia. Flipping edges in trianglations. Discrete Compt. Geom., 22(3): , [7] H. T. Kng, F. Lccio, and F. P. Preparata. On finding the maxima of a set of ectors. J. ACM, 22(4): , [8] G. Liotta, A. Lbi, H. Meijer, and S. Whitesides. The rectangle of inflence draability problem. Compt. Geom., 10(1):1 22, [9] K. Mira, T. Matsno, and T. Nishieki. Open rectangle-of-inflence draings of inner trianglated plane graphs. Discrete Compt. Geom., 41(4): , [10] T. Ottmann, E. Soisalon-Soininen, and D. Wood. On the definition and comptation of rectlinear conex hlls. Inf. Sci., 33: , 1984.

7 CCCG 2016, Vancoer, British Colmbia, Ag 3 5, 2016 A Proof of Lemma 2 We first need a helper-reslt. Lemma 15 Let (, ) be any edge on the first-qadrant chain C I, say x() < x(). Let Q be the first qadrant of point (x(), y()), i.e., it has and on its bondary. Then no point (other than, ) is in Q. R(, ) (recall that (, ) is an RI-edge), they in fact mst hae y-coordinate at least y(), hence be aboe R(, ). In conseqence the only edge of C that can intersect R(, ) is the edge incident to p, bt this edge is also aboe (, ) since p is aboe. So all of C is aboe (, ) as desired. Proof. See Figre 2. Assme to the contrary that Q contained points other than,, and let be the one that maximies the x-coordinate. Since the first qadrants relatie to and are empty, mst be in R(, ). By general position e hae x() < x() < x() and y() < y() < y(). The first qadrant of cannot contain any other point, for all sch points old be to the right of (contradicting the choice of ). So point shold hae been in C I, contradicting that, ere consectie in C I. p C p To complete the proof of Lemma 2, note that for any edge (, ) on C I, rectangle R(, ) is part of this firstqadrant, so it is empty, and e can expand it into a sqare spporting, that is empty. So any edge on C I is an L -edge. Similar argments hold for the other three qadrant-chains, hich proes Lemma 2. Figre 7: For the proof of Lemma 3. B Proof of Lemma 3 Proof. We aim to sho that any RI-edge (, ) is on or belo C I C II. Similar proofs in the other three directions sho that (, ) is either on or enclosed by the maxima-hll as desired. Up to renaming and symmetry, e may assme that is left of and higher than. Consider the maximal ertical strip S containing (, ). This strip mst intersect C I C II, since the rightmost point of P is in C I and the leftmost of P is in C II. Let C be the part of C I C II ithin S, say its ends are p (on a ertical line ith ) and p (on a ertical line ith ). Applying Lemma 15 (or the eqialent for second qadrants) to the edge containing p shos that the ertical ray pard from p contains no other points of P. So either p =, or p is aboe. Similarly p = or p is aboe. In hat follos, e se the term ertex of C for a point on C that is also a point of P, hile point of C refers to an arbitrary point that belongs to C. If C has no ertices, then it is a single line segment p p, and by the aboe (, ) is belo that. So assme that C has ertices. Since C (as part of C I C II ) consists of an increasing chain folloed a decreasing chain, its minima (ith respect to y-coordinate) appear at the ends. Since p is aboe, therefore all ertices of C hae y-coordinate at least y(). Since none of these ertices are inside

On Plane Constrained Bounded-Degree Spanners

On Plane Constrained Bounded-Degree Spanners Algorithmica manscript No. (ill be inserted by the editor) 1 On Plane Constrained Bonded-Degree Spanners 2 3 Prosenjit Bose Rolf Fagerberg André an Renssen Sander Verdonschot 4 5 Receied: date / Accepted:

More information

On Plane Constrained Bounded-Degree Spanners

On Plane Constrained Bounded-Degree Spanners On Plane Constrained Bonded-Degree Spanners Prosenjit Bose 1, Rolf Fagerberg 2, André an Renssen 1, Sander Verdonschot 1 1 School of Compter Science, Carleton Uniersity, Ottaa, Canada. Email: jit@scs.carleton.ca,

More information

[1] Hopcroft, J., D. Joseph and S. Whitesides, Movement problems for twodimensional

[1] Hopcroft, J., D. Joseph and S. Whitesides, Movement problems for twodimensional Acknoledgement. The athors thank Bill Lenhart for interesting discssions on the recongration of rlers. References [1] Hopcroft, J., D. Joseph and S. Whitesides, Moement problems for todimensional linkages,

More information

Combinatorial and Geometric Properties of Planar Laman Graphs

Combinatorial and Geometric Properties of Planar Laman Graphs Combinatorial and Geometric Properties of Planar Laman Graphs Stephen Koboro 1, Torsten Ueckerdt 2, and Kein Verbeek 3 1 Department of Compter Science, Uniersity of Arizona 2 Department of Applied Mathematics,

More information

Non-convex Representations of Graphs

Non-convex Representations of Graphs Non-conex Representations of Graphs Giseppe Di Battista, Fabrizio Frati, and Marizio Patrignani Dip. di Informatica e Atomazione Roma Tre Uniersity Abstract. We sho that eery plane graph admits a planar

More information

Constrained Routing Between Non-Visible Vertices

Constrained Routing Between Non-Visible Vertices Constrained Roting Between Non-Visible Vertices Prosenjit Bose 1, Matias Korman 2, André van Renssen 3,4, and Sander Verdonschot 1 1 School of Compter Science, Carleton University, Ottawa, Canada. jit@scs.carleton.ca,

More information

Reconstructing Generalized Staircase Polygons with Uniform Step Length

Reconstructing Generalized Staircase Polygons with Uniform Step Length Jornal of Graph Algorithms and Applications http://jgaa.info/ ol. 22, no. 3, pp. 431 459 (2018) DOI: 10.7155/jgaa.00466 Reconstrcting Generalized Staircase Polygons with Uniform Step Length Nodari Sitchinaa

More information

arxiv: v1 [cs.cg] 1 Feb 2016

arxiv: v1 [cs.cg] 1 Feb 2016 The Price of Order Prosenjit Bose Pat Morin André van Renssen, arxiv:160.00399v1 [cs.cg] 1 Feb 016 Abstract We present tight bonds on the spanning ratio of a large family of ordered θ-graphs. A θ-graph

More information

On Bichromatic Triangle Game

On Bichromatic Triangle Game On Bichromatic Triangle Game Gordana Manić Daniel M. Martin Miloš Stojakoić Agst 16, 2012 Abstract We stdy a combinatorial game called Bichromatic Triangle Game, defined as follows. Two players R and B

More information

arxiv: v1 [cs.cg] 27 Nov 2015

arxiv: v1 [cs.cg] 27 Nov 2015 On Visibility Representations of Non-planar Graphs Therese Biedl 1, Giseppe Liotta 2, Fabrizio Montecchiani 2 David R. Cheriton School of Compter Science, University of Waterloo, Canada biedl@waterloo.ca

More information

Towards Tight Bounds on Theta-Graphs

Towards Tight Bounds on Theta-Graphs Toards Tight Bonds on Theta-Graphs arxiv:10.633v1 [cs.cg] Apr 01 Prosenjit Bose Jean-Lo De Carfel Pat Morin André van Renssen Sander Verdonschot Abstract We present improved pper and loer bonds on the

More information

Chapter 7 TOPOLOGY CONTROL

Chapter 7 TOPOLOGY CONTROL Chapter TOPOLOGY CONTROL Oeriew Topology Control Gabriel Graph et al. XTC Interference SINR & Schedling Complexity Distribted Compting Grop Mobile Compting Winter 00 / 00 Distribted Compting Grop MOBILE

More information

Lemma 1 Let the components of, Suppose. Trees. A tree is a graph which is. (a) Connected and. (b) has no cycles (acyclic). (b)

Lemma 1 Let the components of, Suppose. Trees. A tree is a graph which is. (a) Connected and. (b) has no cycles (acyclic). (b) Trees Lemma Let the components of ppose "! be (a) $&%('*)+ - )+ / A tree is a graph which is (b) 0 %(')+ - 3)+ / 6 (a) (a) Connected and (b) has no cycles (acyclic) (b) roof Eery path 8 in which is not

More information

Cutting Cycles of Rods in Space: Hardness and Approximation

Cutting Cycles of Rods in Space: Hardness and Approximation Ctting Cycles of Rods in Space: Hardness and pproximation oris rono ark de erg Chris Gray Elena mford bstract We stdy the problem of ctting a set of rods (line segments in R 3 ) into fragments, sing a

More information

Drawing Outer-Planar Graphs in O(n log n) Area

Drawing Outer-Planar Graphs in O(n log n) Area Draing Oter-Planar Graphs in O(n log n) Area Therese Biedl School of Compter Science, Uniersity of Waterloo, Waterloo, ON N2L 3G1, Canada, biedl@aterloo.ca Abstract. In this paper, e stdy draings of oter-planar

More information

Tri-Edge-Connectivity Augmentation for Planar Straight Line Graphs

Tri-Edge-Connectivity Augmentation for Planar Straight Line Graphs Tri-Edge-Connectivity Agmentation for Planar Straight Line Graphs Marwan Al-Jbeh 1, Mashhood Ishaqe 1, Kristóf Rédei 1, Diane L. Sovaine 1, and Csaba D. Tóth 1,2 1 Department of Compter Science, Tfts University,

More information

Fixed-Parameter Algorithms for Cluster Vertex Deletion

Fixed-Parameter Algorithms for Cluster Vertex Deletion Fixed-Parameter Algorithms for Clster Vertex Deletion Falk Hüffner Christian Komsieicz Hannes Moser Rolf Niedermeier Institt für Informatik, Friedrich-Schiller-Uniersität Jena, Ernst-Abbe-Platz 2, D-07743

More information

Augmenting the edge connectivity of planar straight line graphs to three

Augmenting the edge connectivity of planar straight line graphs to three Agmenting the edge connectivity of planar straight line graphs to three Marwan Al-Jbeh Mashhood Ishaqe Kristóf Rédei Diane L. Sovaine Csaba D. Tóth Pavel Valtr Abstract We characterize the planar straight

More information

Chapter 5. Plane Graphs and the DCEL

Chapter 5. Plane Graphs and the DCEL Chapter 5 Plane Graphs and the DCEL So far we hae been talking abot geometric strctres sch as trianglations of polygons and arrangements of line segments withot paying mch attention to how to represent

More information

h-vectors of PS ear-decomposable graphs

h-vectors of PS ear-decomposable graphs h-vectors of PS ear-decomposable graphs Nima Imani 2, Lee Johnson 1, Mckenzie Keeling-Garcia 1, Steven Klee 1 and Casey Pinckney 1 1 Seattle University Department of Mathematics, 901 12th Avene, Seattle,

More information

An Extended Fault-Tolerant Link-State Routing Protocol in the Internet

An Extended Fault-Tolerant Link-State Routing Protocol in the Internet An Extended Falt-Tolerant Link-State Roting Protocol in the Internet Jie W, Xiaola Lin, Jiannong Cao z, and Weijia Jia x Department of Compter Science and Engineering Florida Atlantic Uniersit Boca Raton,

More information

Localized Delaunay Triangulation with Application in Ad Hoc Wireless Networks

Localized Delaunay Triangulation with Application in Ad Hoc Wireless Networks 1 Localized Delanay Trianglation with Application in Ad Hoc Wireless Networks Xiang-Yang Li Gria Călinesc Peng-Jn Wan Y Wang Department of Compter Science, Illinois Institte of Technology, Chicago, IL

More information

Planarity-Preserving Clustering and Embedding for Large Planar Graphs

Planarity-Preserving Clustering and Embedding for Large Planar Graphs Planarity-Presering Clstering and Embedding for Large Planar Graphs Christian A. Dncan, Michael T. Goodrich, and Stephen G. Koboro Center for Geometric Compting The Johns Hopkins Uniersity Baltimore, MD

More information

Triangle Contact Representations

Triangle Contact Representations Triangle Contact Representations Stean Felsner elsner@math.t-berlin.de Technische Uniersität Berlin, Institt ür Mathematik Strasse des 7. Jni 36, 0623 Berlin, Germany Abstract. It is conjectred that eery

More information

Motivation: Art gallery problem. Polygon decomposition. Art gallery problem: upper bound. Art gallery problem: lower bound

Motivation: Art gallery problem. Polygon decomposition. Art gallery problem: upper bound. Art gallery problem: lower bound CG Lecture 3 Polygon decomposition 1. Polygon triangulation Triangulation theory Monotone polygon triangulation 2. Polygon decomposition into monotone pieces 3. Trapezoidal decomposition 4. Conex decomposition

More information

Vertex Guarding in Weak Visibility Polygons

Vertex Guarding in Weak Visibility Polygons Vertex Garding in Weak Visibility Polygons Pritam Bhattacharya, Sbir Kmar Ghosh*, Bodhayan Roy School of Technology and Compter Science Tata Institte of Fndamental Research Mmbai 400005, India arxi:1409.46212

More information

Coloring Eulerian triangulations of the Klein bottle

Coloring Eulerian triangulations of the Klein bottle Coloring Eulerian triangulations of the Klein bottle Daniel Král Bojan Mohar Atsuhiro Nakamoto Ondřej Pangrác Yusuke Suzuki Abstract We sho that an Eulerian triangulation of the Klein bottle has chromatic

More information

Mobility Control and Its Applications in Mobile Ad Hoc Networks

Mobility Control and Its Applications in Mobile Ad Hoc Networks Mobility Control and Its Applications in Mobile Ad Hoc Netorks Jie W and Fei Dai Department of Compter Science and Engineering Florida Atlantic Uniersity Boca Raton, FL 3331 Abstract Most existing localized

More information

On shortest-path all-optical networks without wavelength conversion requirements

On shortest-path all-optical networks without wavelength conversion requirements Research Collection Working Paper On shortest-path all-optical networks withot waelength conersion reqirements Athor(s): Erlebach, Thomas; Stefanakos, Stamatis Pblication Date: 2002 Permanent Link: https://doi.org/10.3929/ethz-a-004446054

More information

Maximal Cliques in Unit Disk Graphs: Polynomial Approximation

Maximal Cliques in Unit Disk Graphs: Polynomial Approximation Maximal Cliqes in Unit Disk Graphs: Polynomial Approximation Rajarshi Gpta, Jean Walrand, Oliier Goldschmidt 2 Department of Electrical Engineering and Compter Science Uniersity of California, Berkeley,

More information

Pushing squares around

Pushing squares around Pshing sqares arond Adrian Dmitresc János Pach Ý Abstract We stdy dynamic self-reconfigration of modlar metamorphic systems. We garantee the feasibility of motion planning in a rectanglar model consisting

More information

Alliances and Bisection Width for Planar Graphs

Alliances and Bisection Width for Planar Graphs Alliances and Bisection Width for Planar Graphs Martin Olsen 1 and Morten Revsbæk 1 AU Herning Aarhs University, Denmark. martino@hih.a.dk MADAGO, Department of Compter Science Aarhs University, Denmark.

More information

Henneberg Steps for Triangle Representations

Henneberg Steps for Triangle Representations Henneberg Steps or Triangle Representations Nieke Aerts and Stean Felsner {aerts,elsner}@math.t-berlin.de Technische Uniersität Berlin Institt ür Mathematik Strasse des 17. Jni 136 10623 Berlin, Germany

More information

arxiv: v2 [cs.cg] 5 Aug 2014

arxiv: v2 [cs.cg] 5 Aug 2014 The θ 5 -graph is a spanner Prosenjit Bose Pat Morin André van Renssen Sander Verdonschot November 5, 2018 arxiv:12120570v2 [cscg] 5 Ag 2014 Abstract Given a set of points in the plane, e sho that the

More information

A sufficient condition for spiral cone beam long object imaging via backprojection

A sufficient condition for spiral cone beam long object imaging via backprojection A sfficient condition for spiral cone beam long object imaging via backprojection K. C. Tam Siemens Corporate Research, Inc., Princeton, NJ, USA Abstract The response of a point object in cone beam spiral

More information

Today. B-splines. B-splines. B-splines. Computergrafik. Curves NURBS Surfaces. Bilinear patch Bicubic Bézier patch Advanced surface modeling

Today. B-splines. B-splines. B-splines. Computergrafik. Curves NURBS Surfaces. Bilinear patch Bicubic Bézier patch Advanced surface modeling Comptergrafik Matthias Zwicker Uniersität Bern Herbst 29 Cres Srfaces Parametric srfaces Bicbic Bézier patch Adanced srface modeling Piecewise Bézier cres Each segment spans for control points Each segment

More information

arxiv: v1 [cs.cg] 26 Sep 2018

arxiv: v1 [cs.cg] 26 Sep 2018 Convex partial transversals of planar regions arxiv:1809.10078v1 [cs.cg] 26 Sep 2018 Vahideh Keikha Department of Mathematics and Compter Science, University of Sistan and Balchestan, Zahedan, Iran va.keikha@gmail.com

More information

Math 365 Wednesday 4/10/ & 10.2 Graphs

Math 365 Wednesday 4/10/ & 10.2 Graphs Math 365 Wednesda 4/10/19 10.1 & 10.2 Graphs Eercise 44. (Relations and digraphs) For each the relations in Eercise 43(a), dra the corresponding directed graph here V = {0, 1, 2, 3} and a! b if a b. What

More information

Chapter 4: Network Layer

Chapter 4: Network Layer Chapter 4: Introdction (forarding and roting) Reie of qeeing theor Roting algorithms Link state, Distance Vector Roter design and operation IP: Internet Protocol IP4 (datagram format, addressing, ICMP,

More information

Point Location. The Slab Method. Optimal Schemes. The Slab Method. Preprocess a planar, polygonal subdivision for point location queries.

Point Location. The Slab Method. Optimal Schemes. The Slab Method. Preprocess a planar, polygonal subdivision for point location queries. Point Location The Slab Method Prerocess a lanar, olygonal sbdiision for oint location qeries. = (18, 11) raw a ertical line throgh each ertex. This decomoses the lane into slabs. In each slab, the ertical

More information

Triangle-Free Planar Graphs as Segments Intersection Graphs

Triangle-Free Planar Graphs as Segments Intersection Graphs Triangle-ree Planar Graphs as Segments Intersection Graphs N. de Castro 1,.J.Cobos 1, J.C. Dana 1,A.Márqez 1, and M. Noy 2 1 Departamento de Matemática Aplicada I Universidad de Sevilla, Spain {natalia,cobos,dana,almar}@cica.es

More information

Friend of My Friend: Network Formation with Two-Hop Benefit

Friend of My Friend: Network Formation with Two-Hop Benefit Friend of My Friend: Network Formation with Two-Hop Benefit Elliot Ansheleich, Onkar Bhardwaj, and Michael Usher Rensselaer Polytechnic Institte, Troy NY, USA Abstract. How and why people form ties is

More information

CS 557 Lecture IX. Drexel University Dept. of Computer Science

CS 557 Lecture IX. Drexel University Dept. of Computer Science CS 7 Lectre IX Dreel Uniersity Dept. of Compter Science Fall 00 Shortest Paths Finding the Shortest Paths in a graph arises in many different application: Transportation Problems: Finding the cheapest

More information

The Disciplined Flood Protocol in Sensor Networks

The Disciplined Flood Protocol in Sensor Networks The Disciplined Flood Protocol in Sensor Networks Yong-ri Choi and Mohamed G. Goda Department of Compter Sciences The University of Texas at Astin, U.S.A. fyrchoi, godag@cs.texas.ed Hssein M. Abdel-Wahab

More information

COMPOSITION OF STABLE SET POLYHEDRA

COMPOSITION OF STABLE SET POLYHEDRA COMPOSITION OF STABLE SET POLYHEDRA Benjamin McClosky and Illya V. Hicks Department of Comptational and Applied Mathematics Rice University November 30, 2007 Abstract Barahona and Mahjob fond a defining

More information

v e v 1 C 2 b) Completely assigned T v a) Partially assigned Tv e T v 2 p k

v e v 1 C 2 b) Completely assigned T v a) Partially assigned Tv e T v 2 p k Approximation Algorithms for a Capacitated Network Design Problem R. Hassin 1? and R. Rai 2?? and F. S. Salman 3??? 1 Department of Statistics and Operations Research, Tel-Ai Uniersity, Tel Ai 69978, Israel.

More information

arxiv: v1 [cs.cg] 12 Dec 2013

arxiv: v1 [cs.cg] 12 Dec 2013 Smooth Orthogonal Drawings of Planar Graphs Md. Jawaherl Alam, Michael A. Bekos, Michael Kafmann, Philipp Kindermann, Stephen G. Koboro, and Alexander Wolff arxi:.58 [cs.cg] Dec 0 Department of Compter

More information

Select-and-Protest-based Beaconless Georouting with Guaranteed Delivery in Wireless Sensor Networks

Select-and-Protest-based Beaconless Georouting with Guaranteed Delivery in Wireless Sensor Networks Select-and-Protest-based Beaconless Georoting ith Garanteed Deliery in Wireless Sensor Netorks Hanna Kalosha, Amiya Nayak, Stefan Rührp, Ian Stojmenoić School of Information Technology and Engineering

More information

Nonempty Intersection of Longest Paths in Series-Parallel Graphs

Nonempty Intersection of Longest Paths in Series-Parallel Graphs Nonempty Intersection of Longest aths in Series-arallel Graphs Jlia Ehrenmüller 1,, Cristina G. Fernandes 2,, and Carl Georg Heise 1,, 1 Institt für Mathematik, Technische Uniersität Hambrg-Harbrg, Germany,

More information

Tutte Embeddings of Planar Graphs

Tutte Embeddings of Planar Graphs Spectral Graph Theory and its Applications Lectre 21 Ttte Embeddings o Planar Graphs Lectrer: Daniel A. Spielman November 30, 2004 21.1 Ttte s Theorem We sally think o graphs as being speciied by vertices

More information

Queries. Inf 2B: Ranking Queries on the WWW. Suppose we have an Inverted Index for a set of webpages. Disclaimer. Kyriakos Kalorkoti

Queries. Inf 2B: Ranking Queries on the WWW. Suppose we have an Inverted Index for a set of webpages. Disclaimer. Kyriakos Kalorkoti Qeries Inf B: Ranking Qeries on the WWW Kyriakos Kalorkoti School of Informatics Uniersity of Edinbrgh Sppose e hae an Inerted Index for a set of ebpages. Disclaimer I Not really the scenario of Lectre.

More information

A Unified Energy-Efficient Topology for Unicast and Broadcast

A Unified Energy-Efficient Topology for Unicast and Broadcast A Unified Energy-Efficient Topology for Unicast and Broadcast Xiang-Yang Li Dept. of Compter Science Illinois Institte of Technology, Chicago, IL, USA xli@cs.iit.ed Wen-Zhan Song School of Eng. & Comp.

More information

Geometric Unique Set Cover on Unit Disks and Unit Squares

Geometric Unique Set Cover on Unit Disks and Unit Squares CCCG 2016, Vancouver, British Columbia, August 3 5, 2016 Geometric Unique Set Cover on Unit Disks and Unit Squares Saeed Mehrabi Abstract We study the Unique Set Cover problem on unit disks and unit squares.

More information

Multiple Source Shortest Paths in a Genus g Graph

Multiple Source Shortest Paths in a Genus g Graph Mltiple Sorce Shortest Paths in a Gens g Graph Sergio Cabello Erin W. Chambers Abstract We gie an O(g n log n) algorithm to represent the shortest path tree from all the ertices on a single specified face

More information

Reconstructing Orthogonal Polyhedra from Putative Vertex Sets

Reconstructing Orthogonal Polyhedra from Putative Vertex Sets Reconstructing Orthogonal Polyhedra from Putative Vertex Sets Therese Biedl 1 and Burkay Genc 1 David R. Cheriton School of Computer Science, University of Waterloo, Waterloo ON N2L 3G1, Canada biedl@uwaterloo.ca,

More information

Introduction to Computational Manifolds and Applications

Introduction to Computational Manifolds and Applications IMPA - Institto de Matemática Pra e Aplicada, Rio de Janeiro, RJ, Brazil Introdction to Comptational Manifolds and Applications Part 1 - Constrctions Prof. Marcelo Ferreira Siqeira mfsiqeira@dimap.frn.br

More information

Quadrilateral Meshes with Provable Angle Bounds

Quadrilateral Meshes with Provable Angle Bounds Quadrilateral Meshes with Proable Angle Bounds F. Betul Atalay Suneeta Ramaswami Dianna Xu March 3, 2011 Abstract In this paper, we present an algorithm that utilizes a quadtree data structure to construct

More information

Improving Network Connectivity Using Trusted Nodes and Edges

Improving Network Connectivity Using Trusted Nodes and Edges Improing Network Connectiity Using Trsted Nodes and Edges Waseem Abbas, Aron Laszka, Yegeniy Vorobeychik, and Xenofon Kotsokos Abstract Network connectiity is a primary attribte and a characteristic phenomenon

More information

Adaptive Influence Maximization in Microblog under the Competitive Independent Cascade Model

Adaptive Influence Maximization in Microblog under the Competitive Independent Cascade Model International Jornal of Knowledge Engineering, Vol. 1, No. 2, September 215 Adaptie Inflence Maximization in Microblog nder the Competitie Independent Cascade Model Zheng Ding, Kai Ni, and Zhiqiang He

More information

Flooding. Routing: Outlook. Flooding Algorithms. Spanning Tree. Flooding

Flooding. Routing: Outlook. Flooding Algorithms. Spanning Tree. Flooding Roting: Otlook Flooding Flooding Link-State: complete, global knoledge Distance-Vector: iteratie, distribted calclation Goal: To distribte a packet in the hole netork (i.e. to realie a netork-ide broadcast)

More information

KINEMATICS OF FLUID MOTION

KINEMATICS OF FLUID MOTION KINEMATICS OF FLUID MOTION The Velocity Field The representation of properties of flid parameters as fnction of the spatial coordinates is termed a field representation of the flo. One of the most important

More information

Stereopsis Raul Queiroz Feitosa

Stereopsis Raul Queiroz Feitosa Stereopsis Ral Qeiroz Feitosa 5/24/2017 Stereopsis 1 Objetie This chapter introdces the basic techniqes for a 3 dimensional scene reconstrction based on a set of projections of indiidal points on two calibrated

More information

Lecture 3: Art Gallery Problems and Polygon Triangulation

Lecture 3: Art Gallery Problems and Polygon Triangulation EECS 396/496: Computational Geometry Fall 2017 Lecture 3: Art Gallery Problems and Polygon Triangulation Lecturer: Huck Bennett In this lecture, we study the problem of guarding an art gallery (specified

More information

1-2 Geometric vectors

1-2 Geometric vectors 1-2 Geometric ectors We are going to start simple, by defining 2-dimensional ectors, the simplest ectors there are. Are these the ectors that can be defined by to numbers only? Yes, and here is a formal

More information

Mobility Control and Its Applications in Mobile Ad Hoc Networks

Mobility Control and Its Applications in Mobile Ad Hoc Networks Mobility Control and Its Applications in Mobile Ad Hoc Netorks Jie W and Fei Dai, Florida Atlantic Uniersity Abstract Most eisting localized protocols in mobile ad hoc netorks, sch as data commnication

More information

Fixed-Parameter Tractability Results for Full-Degree Spanning Tree and Its Dual

Fixed-Parameter Tractability Results for Full-Degree Spanning Tree and Its Dual Fixed-Parameter Tractability Results for Full-Degree Spanning Tree and Its Dual Jiong Guo, Rolf Niedermeier, and Sebastian Wernicke Institut für Informatik, Friedrich-Schiller-Uniersität Jena Ernst-Abbe-Platz

More information

arxiv: v1 [cs.cg] 31 Aug 2017

arxiv: v1 [cs.cg] 31 Aug 2017 Lombardi Drawings of Knots and Links Philipp Kindermann 1, Stephen Koboro 2, Maarten Löffler 3, Martin Nöllenbrg 4, André Schlz 1, and Birgit Vogtenhber 5 arxi:1708.098191 [cs.cg] 31 Ag 2017 1 FernUniersität

More information

On the complexity of Submap Isomorphism

On the complexity of Submap Isomorphism On the compleit of Sbmap Isomorphism Christine Solnon 1,2, Gillame Damiand 1,2, Colin de la Higera 3, and Jean-Christophe Janodet 4 1 INSA de Lon, LIRIS, UMR 5205 CNRS, 69621 Villerbanne, France 2 Université

More information

Complete Information Pursuit Evasion in Polygonal Environments

Complete Information Pursuit Evasion in Polygonal Environments Complete Information Prsit Easion in Polygonal Enironments Kyle Klein and Sbhash Sri Department of Compter Science Uniersity of California Santa Barbara, CA 9306 Abstract Sppose an npredictable eader is

More information

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un Dynamic Maintenance of Majority Information in Constant Time per Update? Gdmnd S. Frandsen and Sven Skym BRICS 1 Department of Compter Science, University of arhs, Ny Mnkegade, DK-8000 arhs C, Denmark

More information

POWER-OF-2 BOUNDARIES

POWER-OF-2 BOUNDARIES Warren.3.fm Page 5 Monday, Jne 17, 5:6 PM CHAPTER 3 POWER-OF- BOUNDARIES 3 1 Ronding Up/Down to a Mltiple of a Known Power of Ronding an nsigned integer down to, for eample, the net smaller mltiple of

More information

The Strong Colors of Flowers The Structure of Graphs with chordal Squares

The Strong Colors of Flowers The Structure of Graphs with chordal Squares Fakltät für Mathematik, Informatik nd Natrissenschaften der Rheinisch-Westfälischen Technischen Hochschle Aachen arxiv:1711.03464v1 [math.co] 9 Nov 2017 Master Thesis The Strong Colors of Floers The Strctre

More information

Topological Drawings of Complete Bipartite Graphs

Topological Drawings of Complete Bipartite Graphs Topological Drawings of Complete Bipartite Graphs Jean Cardinal Stefan Felsner y Febrary 017 Abstract Topological drawings are natral representations of graphs in the plane, where vertices are represented

More information

Authors. Tamilnadu, India 2.

Authors.   Tamilnadu, India 2. International Jornal of Emerging Trends in Science and Technology Impact Factor: 2.838 DOI: http://dx.doi.org/10.18535/ijetst/3i03.04 Irredndant Complete Domination Nmber of Graphs Athors A.Nellai Mrgan

More information

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES RICARDO G. DURÁN AND ARIEL L. LOMBARDI Abstract. We consider the nmerical approximation of a model convection-diffsion

More information

3-DIMENSIONAL RESPONSE CHARACTERISTICS OF CONTINUOUS VIADUCT NEAR A FAULT

3-DIMENSIONAL RESPONSE CHARACTERISTICS OF CONTINUOUS VIADUCT NEAR A FAULT 13 th World Conference on Earthqake Engineering Vancoer, B.C., Canada Agst 1-6, 24 Paper No. 367 3-DIMENSIONAL RESPONSE CHARACTERISTICS OF CONTINUOUS VIADUCT NEAR A FAULT Kotak OHO 1, Takanori HARADA 2

More information

Computing intersections in a set of line segments: the Bentley-Ottmann algorithm

Computing intersections in a set of line segments: the Bentley-Ottmann algorithm Computing intersections in a set of line segments: the Bentley-Ottmann algorithm Michiel Smid October 14, 2003 1 Introduction In these notes, we introduce a powerful technique for solving geometric problems.

More information

Evaluating Influence Diagrams

Evaluating Influence Diagrams Evalating Inflence Diagrams Where we ve been and where we re going Mark Crowley Department of Compter Science University of British Colmbia crowley@cs.bc.ca Agst 31, 2004 Abstract In this paper we will

More information

Colorability in Orthogonal Graph Drawing

Colorability in Orthogonal Graph Drawing Colorability in Orthogonal Graph Drawing Jan Štola Department of Applied Mathematics, Charles University Malostranské nám. 25, Prague, Czech Republic Jan.Stola@mff.cuni.cz Abstract. This paper studies

More information

Red-Black Trees Goodrich, Tamassia. Red-Black Trees 1

Red-Black Trees Goodrich, Tamassia. Red-Black Trees 1 Red-Black Trees 3 8 00 Goodrich, Tamassia Red-Black Trees 1 From (,) to Red-Black Trees A red-black tree is a representation of a (,) tree by means of a binary tree hose nodes are colored red or black

More information

5.0 Curve and Surface Theory

5.0 Curve and Surface Theory 5. Cre and Srface Theor 5.1 arametric Representation of Cres Consider the parametric representation of a cre as a ector t: t [t t t] 5.1 The deriatie of sch a ector ealated at t t is gien b t [ t t t ]

More information

The Geometry of Carpentry and Joinery

The Geometry of Carpentry and Joinery The Geometry of Carpentry and Joinery Pat Morin and Jason Morrison School of Computer Science, Carleton University, 115 Colonel By Drive Ottawa, Ontario, CANADA K1S 5B6 Abstract In this paper we propose

More information

Preferred directions for resolving the non-uniqueness of Delaunay triangulations

Preferred directions for resolving the non-uniqueness of Delaunay triangulations Preferred directions for resolving the non-uniqueness of Delaunay triangulations Christopher Dyken and Michael S. Floater Abstract: This note proposes a simple rule to determine a unique triangulation

More information

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET Mltiple-Choice Test Chapter 09.0 Golden Section Search Method Optimization COMPLETE SOLUTION SET. Which o the ollowing statements is incorrect regarding the Eqal Interval Search and Golden Section Search

More information

EECS 487: Interactive Computer Graphics f

EECS 487: Interactive Computer Graphics f Interpolating Key Vales EECS 487: Interactive Compter Graphics f Keys Lectre 33: Keyframe interpolation and splines Cbic splines The key vales of each variable may occr at different frames The interpolation

More information

UPWARD PLANAR DRAWING OF SINGLE SOURCE ACYCLIC DIGRAPHS. MICHAEL D. HUTTON y AND ANNA LUBIW z

UPWARD PLANAR DRAWING OF SINGLE SOURCE ACYCLIC DIGRAPHS. MICHAEL D. HUTTON y AND ANNA LUBIW z UPWARD PLANAR DRAWING OF SINGLE SOURCE ACYCLIC DIGRAPHS MICHAEL D. HUTTON y AND ANNA LUBIW z Abstract. An pward plane drawing of a directed acyclic graph is a plane drawing of the digraph in which each

More information

arxiv: v1 [cs.cg] 14 Apr 2014

arxiv: v1 [cs.cg] 14 Apr 2014 Complexity of Higher-Degree Orthogonal Graph Embedding in the Kandinsky Model arxi:1405.23001 [cs.cg] 14 Apr 2014 Thomas Bläsius Guido Brückner Ignaz Rutter Abstract We show that finding orthogonal grid-embeddings

More information

Worksheet And Programme Listing

Worksheet And Programme Listing GETTING STARTED WITH PYGAME ZERO ON THE RASPBERRY PI Worksheet And Programme Listing.technoisaledcation.co.k This resorce is copyright TechnoVisal Limited 2017 bt permission is gien to freely copy for

More information

Chapter 4: Network Layer. TDTS06 Computer networks. Chapter 4: Network Layer. Network layer. Two Key Network-Layer Functions

Chapter 4: Network Layer. TDTS06 Computer networks. Chapter 4: Network Layer. Network layer. Two Key Network-Layer Functions Chapter : Netork Laer TDTS06 Compter s Lectre : Netork laer II Roting algorithms Jose M. Peña, jospe@ida.li.se ID/DIT, LiU 009-09- Chapter goals: nderstand principles behind laer serices: laer serice models

More information

C Puzzles! Taken from old exams. Integers Sep 3, Encoding Integers Unsigned. Encoding Example (Cont.) The course that gives CMU its Zip!

C Puzzles! Taken from old exams. Integers Sep 3, Encoding Integers Unsigned. Encoding Example (Cont.) The course that gives CMU its Zip! 15-13 The corse that gies CMU its Zip! Topics class3.ppt Integers Sep 3,! Nmeric Encodings " Unsigned & Two s complement! Programming Implications " C promotion rles! Basic operations " Addition, negation,

More information

Approximation Algorithms for the Unit Disk Cover Problem in 2D and 3D

Approximation Algorithms for the Unit Disk Cover Problem in 2D and 3D Approximation Algorithms for the Unit Disk Cover Problem in 2D and 3D Ahmad Biniaz Paul Liu Anil Maheshwari Michiel Smid February 12, 2016 Abstract Given a set P of n points in the plane, we consider the

More information

23 Single-Slit Diffraction

23 Single-Slit Diffraction 23 Single-Slit Diffraction Single-slit diffraction is another interference phenomenon. If, instead of creating a mask ith to slits, e create a mask ith one slit, and then illuminate it, e find, under certain

More information

Polygon Partitioning. Lecture03

Polygon Partitioning. Lecture03 1 Polygon Partitioning Lecture03 2 History of Triangulation Algorithms 3 Outline Monotone polygon Triangulation of monotone polygon Trapezoidal decomposition Decomposition in monotone mountain Convex decomposition

More information

Inapproximability of the Perimeter Defense Problem

Inapproximability of the Perimeter Defense Problem Inapproximability of the Perimeter Defense Problem Evangelos Kranakis Danny Krizanc Lata Narayanan Kun Xu Abstract We model the problem of detecting intruders using a set of infrared beams by the perimeter

More information

Representing a Cubic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions

Representing a Cubic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions Representing a Cbic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions ABSTRACT Abhijin Adiga Network Dynamics and Simlation Science Laboratory Virginia Bioinformatics Institte,

More information

Fault Tolerance in Hypercubes

Fault Tolerance in Hypercubes Falt Tolerance in Hypercbes Shobana Balakrishnan, Füsn Özgüner, and Baback A. Izadi Department of Electrical Engineering, The Ohio State University, Colmbs, OH 40, USA Abstract: This paper describes different

More information

From (2,4) to Red-Black Trees

From (2,4) to Red-Black Trees Red-Black Trees 3/0/1 Presentation for use ith the textbook Data Structures and Algorithms in Jaa, th edition, by M. T. Goodrich, R. Tamassia, and M. H. Goldasser, Wiley, 01 Red-Black Trees 3 8 01 Goodrich,

More information

tpa, bq a b is a multiple of 5 u tp0, 0q, p0, 5q, p0, 5q,...,

tpa, bq a b is a multiple of 5 u tp0, 0q, p0, 5q, p0, 5q,..., A binar relation on a set A is a sbset of A ˆ A, hereelements pa, bq are ritten as a b. For eample, let A Z, so A ˆ A tpn, mq n, m P Z. Let be the binar relation gien b a b if and onl if a and b hae the

More information

Image Restoration Image Degradation and Restoration

Image Restoration Image Degradation and Restoration Image Degradation and Restoration hxy Image Degradation Model: Spatial domain representation can be modeled by: g x y h x y f x y x y Freqency domain representation can be modeled by: G F N Prepared By:

More information

Fast Ray Tetrahedron Intersection using Plücker Coordinates

Fast Ray Tetrahedron Intersection using Plücker Coordinates Fast Ray Tetrahedron Intersection sing Plücker Coordinates Nikos Platis and Theoharis Theoharis Department of Informatics & Telecommnications University of Athens Panepistemiopolis, GR 157 84 Ilissia,

More information