
The anti-seismic support and hanger are firmly connected to the building structure and are anti-seismic support equipment with seismic force as the main load. Real-time and accurate acquisition of the service status of the seismic support and hanger to check and judge whether the seismic support and hanger are in a normal working state is of great significance for practical engineering applications. In this paper, based on distributed sensor technology, a set of intelligent monitoring systems for seismic support and hanger of buildings is established. The sensing equipment installed on the seismic support and hanger senses the signal, and then the data collection, storage and processing are used to accurately judge the seismic support and hanger. Service performance status. To effectively fuse multi-source data in distributed sensor environment, an improved method based on wavelet and neural network data fusion is proposed. Compared with the existing methods, the experimental results show that the proposed method has good robustness. Besides, it has better performance in building seismic multi-source monitoring data fusion and is less affected by the data overlap ratio.
Citation: Pingping Chen, Mingyang Qi, Long Chen. Distributed sensors and neural network driven building earthquake resistance mechanism[J]. AIMS Geosciences, 2022, 8(4): 718-730. doi: 10.3934/geosci.2022040
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The anti-seismic support and hanger are firmly connected to the building structure and are anti-seismic support equipment with seismic force as the main load. Real-time and accurate acquisition of the service status of the seismic support and hanger to check and judge whether the seismic support and hanger are in a normal working state is of great significance for practical engineering applications. In this paper, based on distributed sensor technology, a set of intelligent monitoring systems for seismic support and hanger of buildings is established. The sensing equipment installed on the seismic support and hanger senses the signal, and then the data collection, storage and processing are used to accurately judge the seismic support and hanger. Service performance status. To effectively fuse multi-source data in distributed sensor environment, an improved method based on wavelet and neural network data fusion is proposed. Compared with the existing methods, the experimental results show that the proposed method has good robustness. Besides, it has better performance in building seismic multi-source monitoring data fusion and is less affected by the data overlap ratio.
Throughout this paper, all graphs considered are finite, undirected, loopless and without multiple edges. We refer the reader to [3,18] for terminology and notation in graph theory.
Let G=(V,E) be a graph of order n with vertex set V(G) and edge set E(G). The open neighborhood of a vertex v in G is NG(v)=N(v)={u∈V(G)|uv∈E(G)}, and the closed neighborhood of v is NG[v]=N[v]=N(v)∪{v}. The degree of a vertex v in the graph G is dG(v)=d(v)=|N(v)|. Let δ(G)=δ and Δ(G)=Δ denote the minimum and maximum degree of a graph G, respectively. Denote by G[H] the induced subgraph of G induced by H with H⊂V(G). A vertex v in G is a leaf if d(v)=1. A vertex u is a support vertex if u has a leaf neighbor. Denote L(u)={v|uv∈E(G),d(v)=1}.
A subset M⊆E(G) is called a matching in G if no two elements are adjacent in G. A vertex v is said to be M-saturated if some edges of M are incident with v, otherwise, v is M-unsaturated. If every vertex of G is M-saturated, the matching M is perfect. M is a maximum matching if G has no matching M′ with |M′|>|M|. Let R be a subgraph of G, M be a matching of G, v∈V(R), uv∈M. We say the vertex v is RI (resp. RO) if u∈V(R) (resp. u∉V(R)).
A set VC of vertices in a graph G is a vertex cover of G if all the edges are touched by the vertices in VC. A vertex cover VC of G is minimal if no proper subset of it is a vertex cover of G. A minimal vertex cover of maximum cardinality is called a VC-set. In 2001, Mishra et al. [13] denote by MAX-MIN-VC the problem of finding a VC-set of G. Bazgan et al. [2] showed that MAX-MIN-VC is APX-complete for cubic graphs.
A set PD⊆V(G) in a graph G is a paired dominating set if every vertex v∉PD is adjacent to a vertex in PD and the subgraph induced by PD contains a perfect matching. Paired domination was proposed in 1996 [9] and was studied for example in [4,5,6,12,16,17]. A paired dominating set PD of G is minimal if there is no proper subset PD′⊂PD which is a paired dominating set of G. A minimal paired dominating set with maximum cardinality is called a Γpr(G)-set. The upper paired domination number of G is the cardinality of a Γpr(G)-set of G. Denote by Upper-PDS the problem of finding a Γpr(G)-set of G. Upper paired domination was introduced by Dorbec et al. in [7]. They investigated the relationship between the upper total domination and upper paired domination numbers of a graph. Later, they established bounds on upper paired domination number for connected claw-free graphs[10]. Denote Pr(v)={u|u∉PD,N(u)∩PD={v},uv∈E(G)}, where PD is a minimal paired dominating set of G.
Recently, Michael et al. showed that Upper-PDS is NP-hard for split graphs and bipartite graphs, and APX-completeness of Upper-PDS for bipartite graphs with Δ=4 in [11]. In order to improve the results in [11], we show that Upper-PDS is APX-complete for bipartite graphs with Δ=3.
The class APX is the set of NP-optimization problems that allow polynomial-time approximation algorithms with approximation ratio bounded by a constant.
First, we recall the notation of L-reduction [1,15]. Given two NP-optimization problems H and G and polynomial time transformation f from instances of H to instances of G, we say that f is an L-reduction if there are positive constants α and β such that for every instance x of H:
(i) optG(f(x))≤αoptH(x);
(ii) for every feasible solution y of f(x) with objective value mG(f(x),y)=a, we can find a solution y′ of x with mH(x,y′)=b in polynomial time such that |optH(x)−b|≤β|optG(f(x))−a|.
To show that a problem P∈APX is APX-complete, it's enough to show that there is an L-reduction from some APX-complete problems to P.
Denote by MAX-MIN-VC the problem of finding a maximum minimal vertex cover of G. Note that, Minimum Domination problem is APX-complete even for bipartite graphs with maximum degree 3 [14], and Minimum Independent Domination problem [8] is the complement problem of MAX-MIN-VC in a graph G. We can obtain an L-reduction from Minimum Domination problem to Minimum Independent Domination problem by replacing every edge uv with a path Puv=uabcv with α=7, β=1. It's clear that Minimum Independent Domination problem and MAX-MIN-VC are in APX. Thus, Minimum Independent Domination problem is APX-complete even for bipartite graphs with maximum degree 3, so is MAX-MIN-VC (by Theorem 7 in [2]).
In this section, we show Upper-PDS for bipartite graphs with maximum degree 3 is APX-complete by providing an L-reduction f from MAX-MIN-VC for bipartite graphs with maximum degree 3.
We formalize the optimization problems as follows.
Lemma 1. [11] Upper-PDS can be approximated with a factor of 2Δ for graphs without isolated vertices and with maximum degree Δ.
Therefore, Upper-PDS is in APX.
Let G=(V,E) be a bipartite graph with |E|=m, Δ(G)=3.
For each edge xy∈E(G), let Hxy be the graph which is shown in Figure 1. Let T1={ a,...,a5, b,...,b5, r,...,r6, s,...,s6, c,..,c3, u,u1,v,v1}, T2={p,...,p6, q,...,q6, d,...,d3,w,z}, T3={h,..,h5}, T4={t,...,t5}, V(Hxy)=V(T1)∪V(T2)∪V(T3)∪V(T4)∪{w1,z1,x,y}, |V(Hxy)|=70.
Construct G′ by replacing each edge xy∈E(G) with the graph Hxy.
It's clear, Δ(G′)=3 and G′ is a bipartite graph.
Let Sp={p,p1,...,p6}, Sq={q,q1,...,q6}, Sa={a,a1,...,a5}, Sb={b,b1,...,b5}, Sr={r,r1,...,r6}, Ss={s,s1,...,s6}, Sc={c,c1,c2,c3}, Sd={d,d1,d2,d3}.
Let xy=e∈E(G), H′e=H′xy=Hxy−{x,y}, |V(H′xy)|=68.
Let PD be a paired dominating set of G′, uv∈E(G). We say H′uv is [I,O] if u is HIuv and v is HOuv, or if v is HIuv and u is HOuv. We say H′uv is [I,0] if u is HIuv and v∉PD, or if u∉PD and v is HIuv. Analogously, H′uv could be [0,0] ([I,I] or [O,O] or [O,0]).
Note that
|T1∩PD|=|Sa∩PD|+|Sb∩PD|+|Sc∩PD|+|Sr∩PD|+|Ss∩PD|+|{u,u1,v,v1}∩PD|, | (2.1) |
|T2∩PD|=|Sp∩PD|+|Sq∩PD|+|Sd∩PD|+|{w,z}∩PD|, | (2.2) |
|V(H′xy)∩PD|=|T1∩PD|+|T2∩PD|+|T3∩PD|+|T4∩PD|+|{w1,z1}∩PD|. | (2.3) |
The following lemma is immediate.
Lemma 2. Let PD be a minimal paired dominating set of G, M be a perfect matching of G[PD]. If v,u are support vertices, uv∈E(G), x∈L(v), y∈L(u), then |{x,y}∩PD|≤1.
Lemma 3. Let PD be a minimal paired dominating set of G′, M be a perfect matching of G′[PD]. For each Hxy, we have
(a) |Sc∩PD|=4 if and only if r,s∉PD, Pr(c3)≠∅ or Pr(c)≠∅.
(b) |Sd∩PD|=4 if and only if p,q∉PD, Pr(d3)≠∅ or Pr(d)≠∅.
(c) |T3∩PD|≤4 with equality if and only if (i) or (ii) holds,
(i) Pr(h1)≠∅ if h∉PD,
(ii) N(h)∩PD={h1} or Pr(h)≠∅ if h∈PD.
And if h is G[T3]O, |T3∩PD|=3.
(d) |T4∩PD|≤4 with equality if and only if (i) or (ii) holds,
(i) Pr(t1)≠∅ if t∉PD,
(ii) N(t)∩PD={t1} or Pr(t)≠∅ if t∈PD.
And if t is G[T4]O, |T4∩PD|=3.
(e) |Sa∩PD|≤4 with equality if and only if (i) or (ii) holds,
(i) Pr(a1)≠∅ if a∉PD,
(ii) N(a)∩PD={a1} or Pr(a)≠∅ if a∈PD.
And if a is G[Sa]O, |Sa∩PD|=3.
(f) |Sb∩PD|≤4 with equality if and only if (i) or (ii) holds,
(i) Pr(b1)≠∅ if b∉PD,
(ii) N(b)∩PD={b1} or Pr(b)≠∅ if b∈PD.
And if b is G[Sb]O, |Sb∩PD|=3.
(g) 3≤|Sr∩PD|≤4. And if r∈PD and r is G[Sr]O, |Sr∩PD|=3.
(h) 3≤|Ss∩PD|≤4. And if s∈PD and s is G[Sr]O, |Ss∩PD|=3.
(i) 3≤|Sp∩PD|≤4. And if p∈PD and p is G[Sp]O, |Sp∩PD|=3.
(j) 3≤|Sq∩PD|≤4. And if q∈PD and q is G[Sq]O, |Sq∩PD|=3.
(k) |T2∩PD|≤13 with equality if and only if |{w,z}∩PD|=1.
(l) |T1∩PD|≤22 with equality if and only if {u,v}⊆PD.
(m) If {u,v}∩PD=∅, |T1∩PD|≤18.
Proof. (a) W.l.o.g. we consider r∈PD. If rc∈M, |Sc∩PD|≠4. Otherwise, c1c2,c3s∈M and let PD′=PD∖{c1,c2}, M′=M∖{c1c2}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If rc∉M, |Sc∩PD|≠4. Otherwise, cc1,c2c3∈M and let PD′=PD∖{c,c1}, M′=M∖{cc1}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.
If Pr(c3)=∅ and Pr(c)=∅, let PD′=PD∖{c,c3} and M′=M∖{cc1,c2c3}∪{c1c2}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.
(b) The proof is analogous to that of (a), and the proof is omitted.
(c) Clearly, |T3∩PD|≤4. If |T3∩PD|=4, {h1,h2,h3,h4}⊆PD or {h,h1,h2,h3}⊆PD. If {h1,h2,h3,h4}⊆PD, Pr(h1)≠∅. Otherwise, let PD′=PD∖{h4,h1}, M′=M∖{h3h4,h1h2}∪{h2h3}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If {h,h1,h2,h3}⊆PD, N(h)∩PD={h1} or Pr(h)≠∅. Otherwise, let PD′=PD∖{h,h1}, M′=M∖{hh1}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.
If h is G[T3]O, and since |T3∖{h}∩PD| is even, we have |T3∩PD|=3.
(d)–(f) We obtain the conclusions with a similar proof of (c).
(g) Clearly, 3≤|Sr∩PD|≠6. If |Sr∩PD|=5, we obtain Sr∩PD={r,r1,r2,r3,r4} or Sr∩PD={r,r2,r3,r4,r5} by Lemma 2. Therefore, PD is not a minimal paired dominating set, a contradiction. Thus, 3≤|Sr∩PD|≤4.
If r is G[Sr]O, and since |Sr∖{r}∩PD| is even, we have |Sr∩PD|=3.
(k) Since |Sd∩PD|≤4, |T2∩PD|≤14 by (i)–(j) and Eq (2.1).
If |{w,z}∩PD|=0, |T2∩PD|≤12.
If |{w,z}∩PD|=1, |T2∩PD|≤13.
Then we consider |{w,z}∩PD|=2. If w is G[T2]I or z is G[T2]I, we may assume w is G[T2]I. We obtain wp∈M, |Sp∩PD|=3 by (i), |Sd∩PD|≤3 by (b). Therefore, |T2∩PD|≤12 by Eq (2.1). If w,z are G[T2]O, |Sd∩PD|≤3 by (b). Since |T2∩PD| is even, |T2∩PD|≤12 by Eq (2.1).
Thus, |T2∩PD|≤13 with equality if and only if |{w,z}∩PD|=1, see Figure 2 (a).
(h)–(j) Using similar arguments of (g), the conclusions follow.
(l)–(m) We discuss the following cases.
Case 1. |{u,v}∩PD|=2.
In this case, we have |{u1,v1}∩PD|≥1, |Sa∩PD|≥3 and |Sc∩PD|≥3, otherwise, |T1∩PD|≤22 by (e)–(h) and Eq (2.2).
W.l.o.g. we assume u1∈PD.
First, we assume that |Sa∩PD|=4. We obtain aa1,uu1∈M, {r,c,r1}∩PD=∅ by (e). Thus, |Sc∩PD|≤3. Then, we consider |Sc∩PD|=3, that is, c3s∈M. By (h), we have |Ss∩PD|=3. Therefore, |T1∩PD|≤22 by Eq (2.2).
Then, we consider |Sa∩PD|=3. Therefore, v1∈PD, otherwise, |T1∩PD|≤22 by Eq (2.2).
We have |Sb∩PD|=4, otherwise, |T1∩PD|≤22 by Eq (2.2). By (f), {s,s1,c3}∩PD=∅. Thus, |Sc∩PD|≤3. Therefore, |T1∩PD|≤22 by Eq (2.2), see Figure 2 (b).
Case 2. |{u,v}∩PD|=1.
W.l.o.g. we assume u∈PD.
We have |{u1,v1}∩PD|≥1 and |Sa∩PD|≥3, otherwise, |T1∩PD|≤21 by Eq (2.2).
Case 2.1 u1∈PD.
If |Sa∩PD|=4, {r,r1,c}∩PD=∅ by (e). Then |Sc∩PD|≤3. If |Sc∩PD|=3, we have c3s∈M, |Ss∩PD|≤3 by (h). Therefore, |T1∩PD|≤21 by Eq (2.2). If |Sc∩PD|=2, |T1∩PD|≤21 by Eq (2.2).
Now we consider |Sa∩PD|=3. If v1∉PD, |T1∩PD|≤21 by Eq (2.2). Thus, v1∈PD, that is, v1b∈M. Therefore, |Sb∩PD|=3 by (f), |T1∩PD|≤21 by Eq (2.2).
Case 2.2 u1∉PD.
If v1∈PD, v1b∈M. Therefore, |Sb∩PD|=3 by (f), |T1∩PD|≤21 by Eq (2.2). Thus, v1∉PD, and |T1∩PD|≤21 by Eq (2.2).
Case 3. |{u,v}∩PD|=0.
In this case, |T1∩PD| is even.
Case 3.1 |{u1,v1}∩PD|≥1.
W.l.o.g. we assume u1∈PD. Then u1a∈M, |Sa∩PD|=3 by (e). If v1∉PD, b∈PD. By (a), |Sc∩PD|≤3. Therefore, |T1∩PD|≤19 by Eq (2.2). If v1∈PD, we obtain v1b∈M, |Sb∩PD|=3 by (f). |Sc∩PD|≤3 by (a). Therefore, |T1∩PD|≤19 by Eq (2.2).
Case 3.2 |{u1,v1}∩PD|=0.
In this case, a,b∈PD. By (a), |Sc∩PD|≤3. Therefore, |T1∩PD|≤19 by Eq (2.2).
Note that |T1∩PD| is even, so |T1∩PD|≤18, see Figure 2 (c).
Thus, (l) and (m) hold.
Lemma 4. Let PD be a minimal paired dominating set of G′.
(a) |V(H′xy)∩PD|≤43.
(b) If {xw1,yz1}⊂M, |V(H′xy)∩PD|≤42.
(c) If {xw1,yz1}∩M=∅ and {w1,z1}⊆PD, |V(H′xy)∩PD|≤42.
(d) If xw1∉M(G), w1∈PD and y∉PD, then |V(H′xy)∩PD|≤42.
Proof. (a) By Lemma 3 and Eq (2.3),
|V(H′xy)∩PD|=|T1∩PD|+|T2∩PD|+|T3∩PD|+|T4∩PD|+|{w1,z1}∩PD|≤22+13+4+4+2=45. |
We consider that {w1,z1}∩PD≠∅, |T4∩PD|≥3 and |T3∩PD|≥3, otherwise, |V(H′xy)∩PD|≤43. Then, w.l.o.g. we assume that w1∈PD.
If |T4∩PD|=4, {tt1,t2t3}⊆M or {t1t2,t3t4}⊆M.
If {tt1,t2t3}⊆M, Pr(t)≠∅ or N(t)∩PD={t1}. If Pr(t)≠∅, u∈Pr(t). By Lemma 3 (m), |V(H′xy)∩PD|≤43. If N(t)∩PD={t1}, we have u,w1∉PD, |T1∩PD|≤21 by Lemma 3 (l). Then we obtain z∈PD, otherwise, |V(H′xy)∩PD|≤43 by Lemma 3 (k) and Eq (2.3). If |T3∩PD|=4, we have v∉PD, therefore, |V(H′xy)∩PD|≤43 by Eq (2.3). If |T3∩PD|=3, |V(H′xy)∩PD|≤43 by Eq (2.3).
If {t1t2,t3t4}⊆M, {w,u}∩PD=∅. By Lemma 3 (l), |T1∩PD|≤21, and v∈PD. If z∉PD, |V(H′xy)∩PD|≤43 by Lemma 3 (k) and Eq (2.3). If z∈PD, |T3∩PD|≤3 by Lemma 3 (c). Therefore, |V(H′xy)∩PD|≤43 by Eq (2.3).
If |T4∩PD|=3, we consider |T1∩PD|=22, and {u,v,z1}∈PD. We have |T3∩PD|≠4 by Lemma 3 (c). Therefore, |V(H′xy)∩PD|≤43 by Eq (2.3).
(b)–(d) Since |V(H′xy)∩PD|≤43, and, |V(H′xy)∩PD| is even in those cases, so |V(H′xy)∩PD|≤42.
Lemma 5. Let PD be a minimal paired dominating set of G′, M be a perfect matching of G′[PD].
(a) If {x,w1,y,z1}⊂PD, xw1∈M(G) and yz1∉M, we have |V(H′xy)∩PD|≤41.
(b) If {x,y}∩PD=∅, |V(H′xy)∩PD|≤40.
Proof. (a) In this case, we have z∈PD and zz1∈M.
Since |V(H′xy)∩PD| is odd, it's sufficient to show |V(H′xy)∩PD|≤42. We only consider {u,v}∩PD≠∅ by Lemma 3 (m).
Case 1. |T4∩PD|=4.
In this case, we have {t1t2,t3t4}⊆M or {tt1,t2t3}⊆M. If {t1t2,t3t4}⊆M (or {tt1,t2t3}⊆M), we obtain u,w∉PD, v∈PD. Since z,v∈PD, |T3∩PD|≤3 by Lemma 3 (c). If |T3∩PD|=2, |V(H′xy)∩PD|≤42 by Eq (2.3). If |T3∩PD|=3, hv∈M. Thus, {q,q1,d3}∩PD=∅, otherwise, let PD′=PD∖{z,z1}, M′=M∖{zz1}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. Since zz1∈M, we obtain that |T2∩PD| is odd. So |T1∩PD|≤12. Therefore, |V(H′xy)∩PD|≤42 by Eq (2.3), see Figure 3 (a).
Case 2. |T4∩PD|=3.
If tw∈M, u∉PD or {p,p1,d}∩PD=∅. Otherwise, let PD′=PD∖{t,w}, M′=M∖{tw}. Then, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If {p,p1,d}∩PD=∅, |Sd∩PD|≤3. W have |Sd∩PD|=3, d3q∈M, otherwise, |V(H′xy)∩PD|≤42 by Eq (2.3). Thus |Sq∩PD|≤3 by Lemma 3 (j) and Eq (2.3), and |V(H′xy)∩PD|≤42. If u∉PD, v∈PD. Thus, |T3∩PD|≤3 by Lemma 3 (c) and Eq (2.3), and |V(H′xy)∩PD|≤42.
If tu∈M, |T3∩PD|≤3 by Lemma 3 (c). We have |T3∩PD|=3, hv∈M, otherwise, |V(H′xy)∩PD|≤42 by Eq (2.3). Let PD′=PD∖{t,h}, M′=M∖{tu,hv}∪{uv}. Therefore, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.
Case 3. |T4∩PD|=2.
Now we only consider |T1∩PD|=22, and {u,v}⊂PD. By Lemma 3 (c) and Eq (2.3), |V(H′xy)∩PD|≤42.
(b) Since |V(H′xy)∩PD| is even, it's sufficient to show |V(H′xy)∩PD|≤41.
Case 1. |{z1,w1}∩PD|=0.
We obtain {z,w}⊆PD, |T2∩PD|≤12 by Lemma 3 (k). If |T4∩PD|≤3, |V(H′xy)∩PD|≤41 by Eq (2.3), see Figure 3 (b). If |T4∩PD|=4, t∈PD and Pr(t)≠∅ by Lemma 3(d). So, {u,v,u1}∩PD=∅. By Lemma 3 (m) and Eq (2.3), |V(H′xy)∩PD|≤40.
Case 2. |{z1,w1}∩PD|=1.
W.l.o.g. we assume w1∈PD. Thus, ww1∈M, z∈PD, |T2∩PD|≤12 by Lemma 3 (k). If |T4∩PD|=2, |V(H′xy)∩PD|≤41 by Eq (2.3). If |T4∩PD|=4, we obtain Pr(t)={u} for t∈PD, {u,u1,v}∩PD=∅. By Lemma 3 (m) and Eq (2.3), |V(H′xy)∩PD|≤40. If |T4∩PD|=3, tu∈M. And v∈PD, otherwise |T1∩PD|≤21 by Lemma 3 (l), |V(H′xy)∩PD|≤41 by Eq (2.3). Thus, |T4∩PD|≠4 by Lemma 3 (d). Afterwards, |V(H′xy)∩PD|≤41 by Eq (2.3).
Case 3. |{z1,w1}∩PD|=2.
Thus, ww1∈M, zz1∈M, |T2∩PD|≤12 by Lemma 3 (k).
If |T4∩PD|=4, t∈PD and {u,u1,v}∩PD=∅. By Lemma 3 (m) and Eq (2.3), we have |V(H′xy)∩PD|≤40.
If |T4∩PD|=3, we have tu∈M, and |T3∩PD|≤3 by Lemma 3 (c). If |T3∩PD|=2, |V(H′xy)∩PD|≤41 by Eq (2.3). If |T3∩PD|=3, hv∈M. Let PD′=PD∖{t,h}, M′=M∖{tu,hv}∪{uv}. Therefore, PD′ is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.
If |T4∩PD|=2, we only consider |T1∩PD|=22. Thus, u,v∈PD. By Lemma 3 (c), |T3∩PD|≤3. Therefore, |V(H′xy)∩PD|≤41 by Eq (2.3).
Corollary 6. Let PD be a minimal paired dominating set of G′. If |V(H′uv)∩PD|=43 if and only if |{u,v}∩PD|=1, and, u or v is HIuv.
Lemma 7. If VC1 is a minimal vertex cover of G, there exists a minimal paired dominating set PD1 of G′ with |PD1|=42m+2|VC|.
Proof. A minimal paired dominating set PD1 can be constructed by the following manner:
For each vertex x∈VC1, we have |N(x)∩VC1|<d(x)≤3. So there exists at least one edge xx1 with x1∉VC1 in G, and maybe exist edges xx2 or xx3.
Therefore, for the edge xx1, put i into PD′ for i∈{x,w1, p2,p3,p4,p5, d,d1,d2,d3, q2,q3,q4,q5, z,z1, h,h2,h3, v, b1,b2,b3,b4, s2,s3,s4,s5, c,c1,c2,c3, r2,r3,r4,r5, a,a1,a2,a3, t1,t2,t3,t4}. Put j into M for j∈{xw1, p5p4,p3p2,dd1,d2d3, q2q3,q4q5, zz1, hv, h2h3, b1b2,b3b4, s2s3,s4s5, cc1,c2c3, r2r3,r4r5, aa1,a2a3, t1t2,t3t4}. See Figure 4 (a).
For edges xx2,xx3, put i into PD′ for i∈{x, p2,p3,p4,p5, d,d1,d2,d3, q2,q3,q4,q5, z,z1, u,v, h2,h3, b1,b2,b3,b4, s2,s3,s4,s5, c,c1,c2,c3, r2,r3,r4,r5, a1,a2,a3,a4, t1,t2,t3,t4}. Put j into M for j∈{ p5p4,p3p2,dd1,d2d3, q2q3,q4q5, zz1, h2h3, uv, b1b2,b3b4, s2s3,s4s5, cc1,c2c3, r2r3,r4r5, a1a2,a3a4, tt1,t2t3}. See Figure 4 (b).
Let PD1=PD′∪VC1. Since vertex x is M-saturated in PD1. Therefore, PD1 is a paired dominating set of G′.
Since N(w)∩PD1={w1}, then PD1∖{w1} is not a dominating set of G′. So PD1 is a minimal paired dominating set of G′. And |PD1|=|VC1|+|VC1|×43+(m−|VC1|)×42. Therefore, |PD1|=2|VC1|+42m.
Let PD be a minimal paired dominating set of G′. Algorithm 1 is to obtain a minimal vertex cover VC of G, and it terminates in polynomial time.
Algorithm 1 CONST-VC(G′,PD) |
Input: A graph G′ with a minimal paired dominating set PD Output: A graph G with a minimal vertex cover VC 1: VC=PD 2: for every Hxy⊆G′ do 3: Delete vertices in H′xy 4: Add an edge between x and y {obtained the graph G} 5: VC=VC∖V(H′xy) 6: end for 7: VC′=VC 8: De=∅ {Mo is the set of vertex which is removed from VC.} 9: In=∅ {In is the set of vertex which is added into VC.} 10: Mo=∅ {De is the set of vertex which is added into VC at first, then removed from VC.} 11: while |N[v]∩VC|=d(v)+1 do 12: VC=VC∖{v},Mo=Mo∪{v} 13: end while 14: while uv∈E(G) and u,v∉VC do 15: VC=VC∪{u},In=In∪{u} 16: for w∈N(u) do 17: if |N[w]∩VC|=d(w)+1 then 18: VC=VC∖{w},De=De∪{w} 19: end if 20: end for 21: end while 22: return VC |
Lemma 8. If PD is a minimal paired dominating set of G′ and VC is a minimal vertex cover of G obtained by Algorithm 1, |VC|≥|PD|−42m−|VC|.
Proof. Let M be the perfect matching of G[PD], me=V(H′xy)∩PD where e=xy∈E(G), Me=⋃e∈E(G)me, Le=V(G)∖(Mo∪In∪De).
In Algorithm 1, we have:
Claim 9. (a) If v is put into Mo by the while loop (lines 11 to 13) or De (line 18), v will not be put into In later.
(b) For every vertex v∈V(G), v will be put into Mo (or De or In) at most once.
(c) Mo∩De=∅, Mo∩In=∅.
(d) If v∈De, there exists a vertex w∈N(v)∩In.
(e) If vertex v∈De∩In, we have v∉VC′, that is, v is put into In at first and then into De.
(f) If u,v∈De∪Mo, N(v)∩N(u)∩Mo∩De=∅.
(g) If v∈De∖In, there exists a vertex u∈N(v)∩(In∖De), u∉VC′. And |N(u)∩De|≤2. What's more, there exists a vertex w∈N(u)∖VC′. If w∈In∖De, |(N(u)∪N(w))∩(De∖In)|≤3.
Proof. (a) After v is put into De (or Mo), every w∈N(v) has a neighbor v which does not belong to VC, so w will not be put into De. Therefore, v will not be put into In later.
(b)–(d) By (a), it is immediate.
(e) By (a) and (c), it is immediate.
(f) Suppose v is put into De∪Mo. By (a), w∈N(v) will not be put into De∪Mo.
(g) For vertex v∈De∖In, by (d) and (f), let u∈N(v)∩(In∖De), and u∉VC′, |N(u)∩De|≤2.
Since u∈In∖De, there exists a vertex w∈N(u)∖VC′.
Since 1≤|N(u)∩(De∖In)|≤2, |N(w)∩(De∖In)|≤2. If w∈In∖De, we may assume u is put into In at first. Then N(u)∩(De∖In)|≤1, otherwise, w will not be put into In later. Therefore, |(N(u)∪N(w))∩(De∖In)|≤3.
Thus,
|VC|=|PD|−|Me|−|Mo|−|De|+|In|. | (2.4) |
To show that |Me|+|Mo|+|De|−|In|≤42m+|VC|, we use the following strategy.
Discharging procedure:
In the graph G′, we set the initial charge of every vertex v to be s(v)=1 for v∈Mo∪Me∪(De∖In), s(v)=−1 for v∈In∖De, s(v)=0 otherwise, s(H′uv)=∑x∈V(H′uv)s(x), s(G′)=∑v∈V(G′)s(v).
Obviously,
∑v∈V(G′)s(v)=|Me|+|Mo|+|De|−|In|. | (2.5) |
We use the discharging procedure, leading to a final charge s′, defined by applying the following rules:
Rule 1: For the vertex v∈Mo, v is M-saturated. Therefore, v is HIuv for u. If u is HIuv, s(v) transmits 1 charge to s(u). If u is HOuv, s(v) transmits 1 charge to s(H′uv) which is [I,O].
Rule 2: For each s(H′uv)=43, by Corollary 6, s(H′uv) transmits 1 charge to u∈VC′.
Rule 3: For the vertex v∈De∖In, by Claim 9 (g), there exists a vertex u∈N(v)∩(In∖De), and a vertex w∈N(u)∖VC′ and |N(u)∩De|≤2. If |N(u)∩De|=2, s(v) transmits 1 charge to s(u) and transmits 1 charge to s(H′uw) which is [0,0]. If |N(u)∩De|=1, s(v) transmits 2 charge to s(u).
After discharging, we have:
Claim 10. (a) s′(v)≤0 for v∈Mo∪(De∖In)∪(Le∖VC)∪(In∩De).
(b) For each H′xy, s′(H′xy)≤42.
(c) s′(v)≤1 for v∈(In∖De)∪(Le∩VC).
Proof. (a) If v∈Mo, by Claim 9 (f), v will not receive any charge by Rules 1 and 3. Since N[v]∩VC′=N[v]. By Lemmas 4 and 5, v will not receive any charge by Rule 2. Therefore, s′(v)=0.
If v∈De∖In, v∈VC′. By Claim 9 (f), N(v)∩Mo=∅. Thus, v will not receive any charge by Rules 1 and 3. Since v is HIuv for u. By Lemmas 4 and 5, if u∈VC′, v will not receive any charge by Rule 2. If u∉VC′, v will receive 1 charge at most by Rule 2. Afterwards, by Rule 3, v will transmit 2 charge to others, so s′(v)≤0.
If v∈Le∖VC, v will not receive any charge by Rules 1, 2 and 3.
If v∈In∩De, v∉VC′ by Claim 9 (e). Thus, v will not receive any charge by Rules 1 and 2. By Claim 9 (f), v∈De, N(v)∩De=∅. Thus, v will not receive any charge by Rule 3.
(b) If H′uw is [I,I] or [O,O] or [I,0] or [O,0], s(H′uw) will not receive any charge by Rules 1, 2 and 3. If H′uw is [0,0], s(H′uw) will not receive any charge by Rules 1 and 2.
If H′uw is [0,0], by Claim 9 (g), |(N(u)∪N(w))∩(De∖In)|≤3. Thus, s(H′uw) will receive 2 charge at most from s(x) where x∈N(v)∖{w} by Rule 3.
And if s(H′uw)=43, by Corollary 6, there exists a vertex u∈VC′ and u is HIuw. Therefore, s′(H′uw)=42 by Rule 2.
Thus, by Lemmas 4 and 5, s′(H′uw)≤42.
(c) If v∈In∖De, v∉VC′, v will receive any charge by Rules 1 and 2. And there exists a vertex w∈N(v) w∉VC′ and w∉De∖In. So v will receive 2 charge at most by Rule 3, s′(v)≤−1+2=1.
If v∈Le∩VC, v will receive any charge by Rule 3. By Lemmas 4, 5 and Corollary 6, H′uv is [I,0] if s(H′uv)=43. Since v can be M-saturated once, v will receive 1 charge at most by Rules 1 and 2. Thus, s′(v)≤0+1=1.
By Claim 10,
|Me|+|Mo|+|De|−|In|=∑uv∈E(G)s(H′uv)+∑v∈Mos(v)+∑v∈De∖Ins(v)−∑v∈In∖Des(v)=∑uv∈E(G)s′(H′uv)+∑v∈Mos′(v)+∑v∈De∖Ins′(v)+∑v∈In∖Des′(v)+∑v∈In∩Des′(v)+∑v∈Le∖VCs′(v)∑v∈Le∩VCs′(v)≤42m+|In∖De|+|Le∩VC|≤42m+|VC|. |
Thus, by Eq (2.4),
|VC|=|PD|−|Me|−|Mo|−|De|+|In|≥|PD|−42m−|VC|. |
Let PD∗ be a Γpr(G′)-set of G′, and be the Input of Algorithm 1. Then we obtain the Output VC by Algorithm 1.
Since
|VC∗|≥mΔ=m3. |
By Lemma 8,
|VC|≥|PD∗|−42m−|VC|≥|PD∗|−42×3|VC|−|VC||VC|≥|PD∗|−127|VC| |
Let VC∗ be a VC-set of G. Since |VC|≤|VC∗|,
|PD∗|≤128|VC|≤128|VC∗| | (2.6) |
By Lemma 7, |PD∗|≥|PD1|=42m+2|VC∗|. By Lemma 8,
|PD|−|VC|≤|VC|+42m≤|VC∗|+42m≤|PD∗|−|VC∗|. |
Thus,
|VC∗|−|VC|≤|PD∗|−|PD| | (2.7) |
Therefore, by Eq (2.6) and Eq (2.7), f is an L-reduction with α=128, β=1.
Upper-PDS for bipartite graphs is proved to be APX-complete with maximum degree 4 and still open with maximum degree 3. In this paper, we show that Upper-PDS for bipartite graphs with maximum degree 3 is APX-complete by providing an L-reduction f from MAX-MIN-VC for bipartite graphs to it.
This work was supported by the National Key R & D Program of China (No. 2018YFB1005100), the Guangzhou Academician and Expert Workstation (No. 20200115-9) and the Innovation Ability Training Program for Doctoral student of Guangzhou University (No. 2019GDJC-D01).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Algorithm 1 CONST-VC(G′,PD) |
Input: A graph G′ with a minimal paired dominating set PD Output: A graph G with a minimal vertex cover VC 1: VC=PD 2: for every Hxy⊆G′ do 3: Delete vertices in H′xy 4: Add an edge between x and y {obtained the graph G} 5: VC=VC∖V(H′xy) 6: end for 7: VC′=VC 8: De=∅ {Mo is the set of vertex which is removed from VC.} 9: In=∅ {In is the set of vertex which is added into VC.} 10: Mo=∅ {De is the set of vertex which is added into VC at first, then removed from VC.} 11: while |N[v]∩VC|=d(v)+1 do 12: VC=VC∖{v},Mo=Mo∪{v} 13: end while 14: while uv∈E(G) and u,v∉VC do 15: VC=VC∪{u},In=In∪{u} 16: for w∈N(u) do 17: if |N[w]∩VC|=d(w)+1 then 18: VC=VC∖{w},De=De∪{w} 19: end if 20: end for 21: end while 22: return VC |
Algorithm 1 CONST-VC(G′,PD) |
Input: A graph G′ with a minimal paired dominating set PD Output: A graph G with a minimal vertex cover VC 1: VC=PD 2: for every Hxy⊆G′ do 3: Delete vertices in H′xy 4: Add an edge between x and y {obtained the graph G} 5: VC=VC∖V(H′xy) 6: end for 7: VC′=VC 8: De=∅ {Mo is the set of vertex which is removed from VC.} 9: In=∅ {In is the set of vertex which is added into VC.} 10: Mo=∅ {De is the set of vertex which is added into VC at first, then removed from VC.} 11: while |N[v]∩VC|=d(v)+1 do 12: VC=VC∖{v},Mo=Mo∪{v} 13: end while 14: while uv∈E(G) and u,v∉VC do 15: VC=VC∪{u},In=In∪{u} 16: for w∈N(u) do 17: if |N[w]∩VC|=d(w)+1 then 18: VC=VC∖{w},De=De∪{w} 19: end if 20: end for 21: end while 22: return VC |