Fault-Tolerant Embedding of Pairwise Independent Hamiltonian Paths on a Faulty Hypercube with Edge Faults

A Hamiltonian path in G is a path which contains every vertex of G exactly once. Two Hamiltonian paths P ₁=〈u ₁,u ₂,…,u _n 〉 and P ₂=〈v ₁,v ₂,…,v _n 〉 of G are said to be independent if u ₁=v ₁, u _n =v _n , and u _i ≠v _i for all 1<i<n; and both are full-independent if u _i ≠v _i for all 1≤i≤n. Moreover, P ₁ and P ₂ are independent starting at u ₁, if u ₁=v ₁ and u _i ≠v _i for all 1<i≤n. A set of Hamiltonian paths {P ₁,P ₂,…,P _k } of G are pairwise independent (respectively, pairwise full-independent, pairwise independent starting at u ₁) if any two different Hamiltonian paths in the set are independent (respectively, full-independent, independent starting at u ₁). A bipartite graph G is Hamiltonian-laceable if there exists a Hamiltonian path between any two vertices from different partite sets. It is well known that an n-dimensional hypercube Q _n is bipartite with two partite sets of equal size. Let F be the set of faulty edges of Q _n . In this paper, we show the following results:

Panconnectivity of Cartesian product graphs

A graph G of order n (≥2) is said to be panconnected if for each pair (x,y) of vertices of G there exists an xy-path of length ℓ for each ℓ such that d _G (x,y)≤ℓ≤n−1, where d _G (x,y) denotes the length of a shortest xy-path in G. In this paper, we consider the panconnectivity of Cartesian product graphs. As a consequence of our results, we prove that the n-dimensional generalized hypercube Q _n (k ₁,k ₂,…,k _n ) is panconnected if and only if k _i ≥3 (i=1,…,n), which generalizes a result of Hsieh et al. that the 3-ary n-cube Q³_nQ^{3}_{n} is panconnected.     

The construction of mutually independent Hamiltonian cycles in bubble-sort graphs

A Hamiltonian cycle C=? u ₁, u ₂, …, u _n(G), u ₁ ? with n(G)=number of vertices of G, is a cycle C(u ₁; G), where u ₁ is the beginning and ending vertex and u _i is the ith vertex in C and u _i ≠u _j for any i≠j, 1≤i, j≤n(G). A set of Hamiltonian cycles {C ₁, C ₂, …, C _k } of G is mutually independent if any two different Hamiltonian cycles are independent. For a hamiltonian graph G, the mutually independent Hamiltonianicity number of G, denoted by h(G), is the maximum integer k such that for any vertex u of G there exist k-mutually independent Hamiltonian cycles of G starting at u. In this paper, we prove that h(B _n )=n?1 if n≥4, where B _n is the n-dimensional bubble-sort graph.     

Bounded dilation maps of hypercubes into Cayley graphs on the symmetric group

LetG andH be graphs with |V(G)≤ |V(H)|. Iff:V(G) →V(H) is a one-to-one map, we letdilation(f) be the maximum of dist _H (f x),f(y)) over all edgesxy inG where dist _H denotes distance inH. The construction of maps fromG toH of small dilation is motivated by the problem of designing small slowdown simulations onH of algorithms that were originally designed for the networkG. LetS(n), thestar network of dimension n, be the graph whose vertices are the elements of the symmetric group of degreen, two verticesx andy being adjacent ifx o (1,i) =y for somei. That is,xy is an edge ifx andy are related by a transposition involving some fixed symbol (which we take to be 1). Also letP(n), thepancake network of dimension n, be the graph whose vertices are the elements of the symmetric group of degreen, two verticesx andy being adjacent if one can be obtained from the other by reversing some prefix. That is,xy is an edge ifx andy are related byx o (1,i(2,i-1) ⋯ ([i/2], [i/2]) =y. The star network (introduced in [AHK]) has nice symmetry properties, and its degree and diameter are sublogarithmic as functions of the number of vertices, making it compare favorably with the hypercube network. These advantages ofS(n) motivate the study of how well it can simulate other parallel computation networks, in particular, the hypercube. The concern of this paper is to construct low dilation maps of hypercube networks into star or pancake networks. Typically in such problems, there is a tradeoff between keeping the dilationsmall and simulating alarge hypercube. Our main result shows that at the cost ofO (1) dilation asn→ ∞, one can embed a hypercube of near optimum dimension into the star or pancake networksS(n) orP(n). More precisely, lettingQ (d) be the hypercube of dimensiond, our main theorem is stated below. For simplicity, we state it only in the special case when the star network dimension is a power of 2. A more general result (applying to star networks of arbitrary dimension) is obtained by a simple interpolation. This author's research was done during the Spring Semester 1991, as a visiting professor in the Department of Mathematics and Statistics at Miami University.     

A Primal-Dual Approximation Algorithm for Partial Vertex Cover: Making Educated Guesses

We study the partial vertex cover problem. Given a graph G=(V,E), a weight function w:V→R ⁺, and an integer s, our goal is to cover all but s edges, by picking a set of vertices with minimum weight. The problem is clearly NP-hard as it generalizes the well-known vertex cover problem. We provide a primal-dual 2-approximation algorithm which runs in O(nlog n+m) time. This represents an improvement in running time from the previously known fastest algorithm. Our technique can also be used to get a 2-approximation for a more general version of the problem. In the partial capacitated vertex cover problem each vertex u comes with a capacity k _u . A solution consists of a function x:V→ℕ₀ and an orientation of all but s edges, such that the number of edges oriented toward vertex u is at most x _u k _u . Our objective is to find a cover that minimizes ∑ _v∈V x _v w _v . This is the first 2-approximation for the problem and also runs in O(nlog n+m) time. Research supported by NSF Awards CCR 0113192 and CCF 0430650, and the University of Maryland Dean’s Dissertation Fellowship.     

Multicolorings of Series-Parallel Graphs

Let G be a graph, and let each vertex v of G have a positive integer weight ω(v). A multicoloring of G is to assign each vertex v a set of ω(v) colors so that any pair of adjacent vertices receive disjoint sets of colors. This paper presents an algorithm to find a multicoloring of a given series-parallel graph G with the minimum number of colors in time O(n W), where n is the number of vertices and W is the maximum weight of vertices in G.     

On Word Equations in One Variable

For a word equation E of length n in one variable x occurring # _x times in E a resolution algorithm of O(n+# _x log n) time complexity is presented here. This is the best result known and for the equations that feature #_x < \fracnlogn\#_{x}<\frac{n}{\log n} it yields time complexity of O(n) which is optimal. Additionally it is proven here that the set of solutions of any one-variable word equation is either of the form F or of the form F∪(uv)⁺ u where F is a set of O(log n) words and u, v are some words such that uv is a primitive word.     

Reduced constants for simple cycle graph separation

 If G is an n vertex maximal planar graph and δ≤1 3, then the vertex set of G can be partitioned into three sets A, B, C such that neither A nor B contains more than (1−δ)n vertices, no edge from G connects a vertex in A to a vertex in B, and C is a cycle in G containing no more than (√2δ+√2−2δ)√n+O(1) vertices. Specifically, when δ=1 3, the separator C is of size (√2/3+√4/3)√n+O(1), which is roughly 1.97√n. The constant 1.97 is an improvement over the best known so far result of Miller 2√2≈2.82. If non-negative weights adding to at most 1 are associated with the vertices of G, then the vertex set of G can be partitioned into three sets A, B, C such that neither A nor B has weight exceeding 1−δ, no edge from G connects a vertex in A to a vertex in B, and C is a simple cycle with no more than 2√n+O(1) vertices. Received: 8 September 1993/11 December 1995     

Efficient algorithms for constructing (1+∊,β)-spanners in the distributed and streaming models

For an unweighted undirected graph G = (V,E), and a pair of positive integers α ≥ 1, β ≥ 0, a subgraph G′ = (V,H), H ⊂eqE, is called an (α,β)-spanner of G if for every pair of vertices u,v ∊ V, dist_G′(u,v) ≤ α ⋅ dist_G(u,v) + β. It was shown in [21] that for any ∊ > 0, κ = 1,2,…, there exists an integer β = β(∊,κ) such that for every n-vertex graph G there exists a (1+∊,β)-spanner G′ with O(n^1+1/κ) edges. An efficient distributed protocol for constructing (1+∊,β)-spanners was devised in [19]. The running time and the communication complexity of that protocol are O(n^1+ρ) and O(|E|n^ρ), respectively, where ρ is an additional control parameter of the protocol that affects only the additive term β. In this paper we devise a protocol with a drastically improved running time (O(n^ρ) as opposed to O(n^1+ρ)) for constructing (1+∊,β)-spanners. Our protocol has the same communication complexity as the protocol of [19], and it constructs spanners with essentially the same properties as the spanners that are constructed by the protocol of [19]. The protocol can be easily extended to a parallel implementation which runs in O(log n + (|E|⋅ n^ρlog n)/p) time using p processors in the EREW PRAM model. In particular, when the number of processors, p, is at least |E|⋅ n^ρ, the running time of the algorithm is O(log n). We also show that our protocol for constructing (1+∊,β)-spanners can be adapted to the streaming model, and devise a streaming algorithm that uses a constant number of passes and O(n^1+1/κ⋅ {log} n) bits of space for computing all-pairs-almost-shortest-paths of length at most by a multiplicative factor (1+∊) and an additive term of β greater than the shortest paths. Our algorithm processes each edge in time O(n^ρ), for an arbitrarily small ρ > 0. The only previously known algorithm for the problem [23] constructs paths of length κ times greater than the shortest paths, has the same space requirements as our algorithm, but requires O(n^1+1/κ) time for processing each edge of the input graph. However, the algorithm of [23] uses just one pass over the input, as opposed to the constant number of passes in our algorithm. We also show that any streaming algorithm for o(n)-approximate distance computation requires Ω(n) bits of space. This work was Supported by the DoD University Research Initiative (URI) administered by the Office of Naval Research under Grant N00014-01-1-0795. Michael Elkin was supported by ONR grant N00014-01-1-0795. Jian Zhang was supported by ONR grant N00014-01-1-0795 and NSF grants CCR-0105337 and ITR-0331548. Preliminary version of this paper was published in PODC’04, see [22]. After the preliminary version of our paper [22] appeared on PODC’04, Feigenbaum et al. [24] came up with a new streaming algorithm for the problem that is far more efficient than [23] in terms of time-per-edge processing. However, our algorithm is still the only existing streaming algorithm that provides an almost additive approximation of distances.     

On the locatic number of graphs

A vertex v of a connected graph G distinguishes a pair u, w of vertices of G if d(v, u)≠d(v, w), where d(·,·) denotes the length of a shortest path between two vertices in G. A k-partition Π={S ₁, S ₂, …, S _k } of the vertex set of G is said to be a locatic partition if for every pair of distinct vertices v and w of G, there exists a vertex s∈S _i for all 1≤i≤k that distinguishes v and w. The cardinality of a largest locatic partition is called the locatic number of G. In this paper, we study the locatic number of paths, cycles and characterize all the connected graphs of order n having locatic number n, n?1 and n?2. Some realizable results are also given in this paper.     

Adaptive robust control of nonholonomic systems with stochastic disturbances

Based on the Brockett’s necessary condition for feedback asymptotic stabilization[1], nonholonomic systems fail to be stabilized at the origin by any static continuous state feedback though they are open loop controllable. There are two novel approaches …     

On estimation of the probability of absence of collisions of some random mappings

Let X and Y be finite sets and φ: (X,Y) →Y be a mapping. Consider a random mapping i → φ(x_i,y_i), where x_i are arbitrarily chosen from the set X, whereas (y_i) is a random sample from Y without replacement. A two-sided bound is derived for the probability of absence of collisions of this mapping. A case of mapping, defined as φ(x, y)=x+ y modulo n, is considered in particular. The results may be used in the selection of identification codes. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 132–137, January–February, 2000.     

On edge connectivity of direct products of graphs

Let λ(G) be the edge connectivity of G. The direct product of graphs G and H is the graph with vertex set V(G×H)=V(G)×V(H), where two vertices (u₁,v₁) and (u₂,v₂) are adjacent in G×H if u₁u₂∈E(G) and v₁v₂∈E(H). We prove that λ(G×Kn)=min{n(n−1)λ(G),(n−1)δ(G)} for every nontrivial graph G and n?3. We also prove that for almost every pair of graphs G and H with n vertices and edge probability p, G×H is k-connected, where k=O(²(n/logn)).     

On selecting thek largest with median tests

LetW _itk(n) be the minimax complexity of selecting thek largest elements ofn numbersx ₁,x ₂,...,x _n by pairwise comparisonsx _i :x _j . It is well known thatW ₂(n) =n–2+ [lgn], andW _k (n) = n + (k–1)lg n +O(1) for all fixed k 3. In this paper we studyW _k (n), the minimax complexity of selecting thek largest, when tests of the form Isx _i the median of {x _i ,x _j ,x _t }? are also allowed. It is proved thatW₂(n) =n–2+ [lgn], andW _k (n) =n + (k–1)lg₂ n +O(1) for all fixedk3.This research was supported in part by the National Science Foundation under Grant No. DCR-8308109.     

Fast Algorithms for the Density Finding Problem

We study the problem of finding a specific density subsequence of a sequence arising from the analysis of biomolecular sequences. Given a sequence A=(a ₁,w ₁),(a ₂,w ₂),…,(a _n ,w _n ) of n ordered pairs (a _i ,w _i ) of numbers a _i and width w _i >0 for each 1≤i≤n, two nonnegative numbers ℓ, u with ℓ≤u and a number δ, the Density Finding Problem is to find the consecutive subsequence A(i ^*,j ^*) over all O(n ²) consecutive subsequences A(i,j) with width constraint satisfying ℓ≤w(i,j)=∑ _r=i ^j w _r ≤u such that its density is closest to δ. The extensively studied Maximum-Density Segment Problem is a special case of the Density Finding Problem with δ=∞. We show that the Density Finding Problem has a lower bound Ω(nlog n) in the algebraic decision tree model of computation. We give an algorithm for the Density Finding Problem that runs in optimal O(nlog n) time and O(nlog n) space for the case when there is no upper bound on the width of the sequence, i.e., u=w(1,n). For the general case, we give an algorithm that runs in O(nlog ² m) time and O(n+mlog m) space, where and w _min=min  _r=1 ⁿ w _r . As a byproduct, we give another O(n) time and space algorithm for the Maximum-Density Segment Problem. Grants NSC95-2221-E-001-016-MY3, NSC-94-2422-H-001-0001, and NSC-95-2752-E-002-005-PAE, and by the Taiwan Information Security Center (TWISC) under the Grants NSC NSC95-2218-E-001-001, NSC95-3114-P-001-002-Y, NSC94-3114-P-001-003-Y and NSC 94-3114-P-011-001.     

The super spanning connectivity and super spanning laceability of the enhanced hypercubes

A k -container C(u,v) of a graph G is a set of k disjoint paths between u and v. A k-container C(u,v) of G is a k ^* -container if it contains all vertices of G. A graph G is k ^* -connected if there exists a k ^*-container between any two distinct vertices of G. Therefore, a graph is 1^*-connected (respectively, 2^*-connected) if and only if it is Hamiltonian connected (respectively, Hamiltonian). A graph G is super spanning connected if there exists a k ^*-container between any two distinct vertices of G for every k with 1≤k≤κ(G) where κ(G) is the connectivity of G. A bipartite graph G is k ^* -laceable if there exists a k ^*-container between any two vertices from different partite set of G. A bipartite graph G is super spanning laceable if there exists a k ^*-container between any two vertices from different partite set of G for every k with 1≤k≤κ(G). In this paper, we prove that the enhanced hypercube Q _n,m is super spanning laceable if m is an odd integer and super spanning connected if otherwise.

A Quadratic Algorithm for Finding Next-to-Shortest Paths in Graphs

Given an edge-weighted undirected graph G and two prescribed vertices u and v, a next-to-shortest (u,v)-path is a shortest (u,v)-path amongst all (u,v)-paths having length strictly greater than the length of a shortest (u,v)-path. In this paper, we deal with the problem of computing a next-to-shortest (u,v)-path. We propose an O(n²){\mathcal{O}}(n^{2}) time algorithm for solving this problem, which significantly improves the bound of a previous one in O(n³){\mathcal{O}}(n^{3}) time where n is the number of vertices in G.     

The Hub Number of Sierpiński-Like Graphs

A set Q⊆V is a hub set of a graph G=(V,E) if, for every pair of vertices u,v∈V∖Q, there exists a path from u to v such that all intermediate vertices are in Q. The hub number of G is the minimum size of a hub set in G. This paper derives the hub numbers of Sierpiński-like graphs including: Sierpiński graphs, extended Sierpiński graphs, and Sierpiński gasket graphs. Meanwhile, the corresponding minimum hub sets are also obtained.     

Approximation Algorithms for Requirement Cut on Graphs

In this paper, we unify several graph partitioning problems including multicut, multiway cut, and k-cut, into a single problem. The input to the requirement cut problem is an undirected edge-weighted graph G=(V,E), and g groups of vertices X ₁,…,X _g ⊆V, with each group X _i having a requirement r _i between 0 and |X _i |. The goal is to find a minimum cost set of edges whose removal separates each group X _i into at least r _i disconnected components. We give an O(log n⋅log (gR)) approximation algorithm for the requirement cut problem, where n is the total number of vertices, g is the number of groups, and R is the maximum requirement. We also show that the integrality gap of a natural LP relaxation for this problem is bounded by O(log n⋅log (gR)). On trees, we obtain an improved guarantee of O(log (gR)). There is an Ω(log g) hardness of approximation for the requirement cut problem, even on trees.     

All-Pairs Bottleneck Paths in Vertex Weighted Graphs

Let G=(V,E,w) be a directed graph, where w:V→ℝ is a weight function defined on its vertices. The bottleneck weight, or the capacity, of a path is the smallest weight of a vertex on the path. For two vertices u,v the capacity from u to v, denoted by c(u,v), is the maximum bottleneck weight of a path from u to v. In the All-Pairs Bottleneck Paths (APBP) problem the task is to find the capacities for all ordered pairs of vertices. Our main result is an O(n ^2.575) time algorithm for APBP. The exponent is derived from the exponent of fast matrix multiplication.