We consider the problem of approximating the longest path in undirected graphs. In an attempt to pin down the best achievable
performance ratio of an approximation algorithm for this problem, we present both positive and negative results. First, a
simple greedy algorithm is shown to find long paths in dense graphs. We then consider the problem of finding paths in graphs
that are guaranteed to have extremely long paths. We devise an algorithm that finds paths of a logarithmic length in Hamiltonian
graphs. This algorithm works for a much larger class of graphs (weakly Hamiltonian), where the result is the best possible.
Since the hard case appears to be that of sparse graphs, we also consider sparse random graphs. Here we show that a relatively
long path can be obtained, thereby partially answering an open problem of Broderet al.
To explain the difficulty of obtaining better approximations, we also prove hardness results. We show that, for any ε<1, the
problem of finding a path of lengthn-nε in ann-vertex Hamiltonian graph isNP-hard. We then show that no polynomial-time algorithm can find a constant factor approximation to the longest-path problem
unlessP=NP. We conjecture that the result can be strengthened to say that, for some constant δ>0, finding an approximation of rationδ is alsoNP-hard. As evidence toward this conjecture, we show that if any polynomial-time algorithm can approximate the longest path
to a ratio of
, for any ε>0, thenNP has a quasi-polynomial deterministic time simulation. The hardness results apply even to the special case where the input
consists of bounded degree graphs.
D. Karger was supported by an NSF Graduate Fellowship, NSF Grant CCR-9010517, and grants from the Mitsubishi Corporation and
OTL. R. Motwani was supported by an Alfred P. Sloan Research Fellowship, an IBM Faculty Development Award, grants from Mitsubishi
and OTL, NSF Grant CCR-9010517, and NSF Young Investigator Award CCR-9357849, with matching funds from IBM, the Schlumberger
Foundation, the Shell Foundation, and the Xerox Corporation, G. D. S. Ramkumar was supported by a grant from the Toshiba Corporation.
Communicated by M. X. Goemans. 相似文献
Due to recent advances in network, storage and data compression technologies, video-on-demand (VOD) service has become economically
feasible. It is a challenging task to design a video storage server that can efficiently service a large number of concurrent
requests on demand. One approach to accomplishing this task is to reduce the I/O demand to the VOD server through data- and
resource-sharing techniques. One form of data sharing is the stream-merging approach proposed in [5]. In this paper, we formalize a static version of the stream-merging problem, derive an upper bound on the
I/O demand of static stream merging, and propose efficient heuristic algorithms for both static and dynamic versions of the
stream-merging problem. 相似文献
The watershed transformation is a mid-level operation used in morphological image segmentation. Techniques applied on large images, which must often complete fast, are usually computationally expensive and complex entailing efficient parallel algorithms. Two distributed approaches of the watershed transformation are introduced in this paper. The algorithms survey in a Single Program Multiple Data (SPMD) model both local and global connectivity properties of the morphological gradient of a gray-scale image to label connected components. The sequentiality of the serial algorithm is broken in the parallel versions by exploiting the ordering relation between two neighboring pixels successively incorporated in the same region. Thus, a path is traced, for every unlabeled pixel, down to its region of inclusion (whose label is then propagated backwards); in the second algorithm, regions grow independently around their seeds. In both cases only pixels which satisfy the ordering relation are incorporated in any region. This way, not only different regions are explored in a parallel fashion, but also different parts of the same region, when the latter extends to neighboring subdomains, are treated likewise. Running time and relative speedup evaluated on a Cray T3D parallel computer are used to appreciate the performance of both algorithms. 相似文献
LetP andQ be two convex polygons withm andn vertices, respectively, which are specified by their cartesian coordinates in order. A simpleO(m+n) algorithm is presented for computing the intersection ofP andQ. Unlike previous algorithms, the new algorithm consists of a two-step combination of two simple algorithms for finding convex hulls and triangulations of polygons. 相似文献
Parallel algorithms for solving the satisfaction problem of non-trivial functional and multivalued data dependencies (FDs and MVDs) in a relation of N tuples by M processors are developed in this paper. Algorithms performing, in a parallel manner, batch or interactive checking of these data dependencies are also discussed. The M processors are organized as a linear systolic array. The time complexities of the first two algorithms for solving the FD satisfaction problem under MN are both O(N), and that of Algorithm (3) or (4) for solving the FD or MVD satisfaction problem under NM is O(N2/M). The latter complexity reduced to O(N) if N = M and is at least not worse than O(N log N) if N = M (N/log N). 相似文献
We develop anO(n) algorithm to construct a rectangular dual of ann-vertex planar triangulated graph.This research was supported in part by the National Science Foundation under Grant MCS-83-05567. 相似文献
An algorithm for sorting on a mesh by alternately transforming the rows and columns is presented. The algorithm runs in a constant number of row- and column-transformation phases (sixteen phases), an improvement over the previous best upper bound ofO(log logm) phases,m being the number of rows in the mesh. A corresponding lower bound of five phases is also shown.This research was supported by the National Science Foundation under Grant DCR-84-51396, and by IBM Corporation under Grant D8400622. 相似文献
This paper describes an efficient algorithm for the parallel solution of systems of linear equations with a block tridiagonal coefficient matrix. The algorithm comprises a multilevel LU-factorization based on block cyclic reduction and a corresponding solution algorithm.
The paper includes a general presentation of the parallel multilevel LU-factorization and solution algorithms, but the main emphasis is on implementation principles for a message passing computer with hypercube topology. Problem partitioning, processor allocation and communication requirement are discussed for the general block tridiagonal algorithm.
Band matrices can be cast into block tridiagonal form, and this special but important problem is dealt with in detail. It is demonstrated how the efficiency of the general block tridiagonal multilevel algorithm can be improved by introducing the equivalent of two-way Gaussian elimination for the first and the last partitioning and by carefully balancing the load of the processors. The presentation of the multilevel band solver is accompanied by detailed complexity analyses.
The properties of the parallel band solver were evaluated by implementing the algorithm on an Intel iPSC hypercube parallel computer and solving a larger number of banded linear equations using 2 to 32 processors. The results of the evaluation include speed-up over a sequential processor, and the measure values are in good agreement with the theoretical values resulting from complexity analysis. It is found that the maximum asymptotic speed-up of the multilevel LU-factorization using p processors and load balancing is approximated well by the expression (p +6)/4.
Finally, the multilevel parallel solver is compared with solvers based on row and column interleaved organization. 相似文献