The Computer Journal - recent issues

Combinatorial Optimization on Graphs of Bounded Treewidth

Bodlaender, H. L., Koster, A. M. C. A. — 2008-04-29

There are many graph problems that can be solved in linear or polynomial time with a dynamic programming algorithm when the input graph has bounded treewidth. For combinatorial optimization problems, this is a useful approach for obtaining fixed-parameter tractable algorithms. Starting from trees and series-parallel graphs, we introduce the concepts of treewidth and tree decompositions, and illustrate the technique with the Weighted Independent Set problem as an example. The paper surveys some of the latest developments, putting an emphasis on applicability, on algorithms that exploit tree decompositions, and on algorithms that determine or approximate treewidth and find tree decompositions with optimal or close to optimal treewidth. Directions for further research and suggestions for further reading are also given.

Parameterized Complexity and Biopolymer Sequence Comparison

Cai, L., Huang, X., Liu, C., Rosamond, F., Song, Y. — 2008-04-29

The paper surveys parameterized algorithms and complexities for computational tasks on biopolymer sequences, including the problems of longest common subsequence, shortest common supersequence, pairwise sequence alignment, multiple sequencing alignment, structure–sequence alignment and structure–structure alignment. Algorithm techniques, built on the structural-unit level as well as on the residue level, are discussed.

The Bidimensionality Theory and Its Algorithmic Applications

Demaine, E. D., Hajiaghayi, M. — 2008-04-29

This paper surveys the theory of bidimensionality. This theory characterizes a broad range of graph problems (‘bidimensional’) that admit efficient approximate or fixed-parameter solutions in a broad range of graphs. These graph classes include planar graphs, map graphs, bounded-genus graphs and graphs excluding any fixed minor. In particular, bidimensionality theory builds on the Graph Minor Theory of Robertson and Seymour by extending the mathematical results and building new algorithmic tools. Here, we summarize the known combinatorial and algorithmic results of bidimensionality theory with the high-level ideas involved in their proof; we describe the previous work on which the theory is based and/or extends; and we mention several remaining open problems.

Fixed-Parameter Algorithms For Artificial Intelligence, Constraint Satisfaction and Database Problems

Gottlob, G., Szeider, S. — 2008-04-29

We survey the parameterized complexity of problems that arise in artificial intelligence, database theory and automated reasoning. In particular, we consider various parameterizations of the constraint satisfaction problem, the evaluation problem of Boolean conjunctive database queries and the propositional satisfiability problem. Furthermore, we survey parameterized algorithms for problems arising in the context of the stable model semantics of logic programs, for a number of other problems of non-monotonic reasoning, and for the computation of cores in data exchange.

Width Parameters Beyond Tree-width and their Applications

Hlineny, P., Oum, S.-i., Seese, D., Gottlob, G. — 2008-04-29

Besides the very successful concept of tree-width (see [Bodlaender, H. and Koster, A. (2007) Combinatorial optimisation on graphs of bounded treewidth. These are special issues on Parameterized Complexity]), many concepts and parameters measuring the similarity or dissimilarity of structures compared to trees have been born and studied over the past years. These concepts and parameters have proved to be useful tools in many applications, especially in the design of efficient algorithms. Our presented novel look at the contemporary developments of these ‘width’ parameters in combinatorial structures delivers—besides traditional tree-width and derived dynamic programming schemes—also a number of other useful parameters like branch-width, rank-width (clique-width) or hypertree-width. In this contribution, we demonstrate how ‘width’ parameters of graphs and generalized structures (such as matroids or hypergraphs), can be used to improve the design of parameterized algorithms and the structural analysis in other applications on an abstract level.

Some Parameterized Problems On Digraphs

Gutin, G., Yeo, A. — 2008-04-29

We survey results and open questions on complexity of parameterized problems on digraphs. The problems include the feedback vertex and arc set problems, induced subdigraph problems and directed k-leaf problems. We also prove some new results on the topic. Most of these new results are on parameterizations of the backward paired comparison problem.

Parameterized Complexity of Geometric Problems

Giannopoulos, P., Knauer, C., Whitesides, S. — 2008-04-29

This paper surveys parameterized complexity results for hard geometric algorithmic problems. It includes fixed-parameter tractable problems in graph drawing, geometric graphs, geometric covering and several other areas, together with an overview of the algorithmic techniques used. Fixed-parameter intractability results are surveyed as well. Finally, we give some directions for future research.

Parameterized Complexity in Cognitive Modeling: Foundations, Applications and Opportunities

van Rooij, I., Wareham, T. — 2008-04-29

In cognitive science, natural cognitive processes are generally conceptualized as computational processes: they serve to transform sensory and mental inputs into mental and action outputs. At the highest level of abstraction, computational models of cognitive processes aim at specifying the computational problem computed by the process under study. Because computational problems are realistic cognitive models only insofar as they can plausibly be computed by the human brain given its limited resources for computation, computational tractability provides a useful constraint on cognitive models. In this paper, we consider the particular benefits of the parameterized complexity framework for identifying sources of intractability in cognitive models. We review existing applications of the parameterized framework to this end in the domains of perception, action and higher cognition. We further identify important opportunities and challenges for future research. These include the development of new methods for complexity analyses specifically tailored to the reverse engineering perspective underlying cognitive science.

Capsule Reviews

Kamareddine, F. — 2008-02-27

The Capsule Reviews are intended to provide a short succinct review of each paper in the issue in order to bring the content to a wider readership. The Capsule Reviews were compiled by Fairouz Kamareddine. Professor Kamareddine is an Associate Editor of The Computer Journal and is based in the Department of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh, UK.

Information-Dynamics-Conscious Development of Routing Software: A Case of Routing Software that Improves Link-State Routing Based on Future Link-Delay-Information Estimation

Eom, H. — 2008-02-27

In link-state routing, routes are determined based on the estimates of the current delays on the links, i.e. without considering the dynamics of the link-delay information. Ideally, a data packet should be routed based on the delays it will encounter at each link of the path at the time the packet gets to the link. To address this issue, we have designed a new routing software that improves link-state routing by estimating and using the future link delays encountered by data packets. In link-state routing, link-delay estimates are periodically flooded throughout the network. This flooding of link-delay estimates is done without considering the relevance of these estimates to routing quality, i.e. without taking into account the usefulness of the link-delay information. Our routing-software design also improves link-state routing by broadcasting these estimates only to the extent that they are relevant. In the design of routing software, we consider the temporal change of the link-delay information and its usefulness given the information at a time; we call this an information-dynamics-conscious approach. Simulation studies suggest that this design can lead to significant reductions in routing traffic with noticeable improvements of routing quality in high-load conditions, demonstrating the effectiveness of information-dynamics-conscious development of routing software.

On Distributed Rating Systems for Peer-to-Peer Networks

Tian, Y., Wu, D., Ng, K.-W. — 2008-02-27

In recent years, many distributed rating systems have been proposed against the increasing misbehaviors of peers in peer-to-peer (P2P) networks. However, the low accuracy, long-response time and vulnerabilities under the adversary attacks of P2P rating systems have long been criticized and hindering the practical deployment of such a mechanism. There is also a lack of systematic analysis and evaluation for understanding the systems. In this paper, we first present a framework of stochastic analytical model for evaluating P2P rating systems. The performances of two representative designs, namely the unstructured self-managing rating (UMR) system and the structured supervising rating (SSR) system, are then studied with our model. We identify the positive features as well as the negative ones of the two designs with different design choices and under various network environments and adversary attacks. We also propose a configurable loosely supervising rating system, and show that this system works inexpensively, and could make trade-off between the false rating attack resistance of the UMR system and the accuracy, responsiveness, whitewashing attack resistance as well as a failure resilience of the SSR system, thus providing a better overall performance according to the application context.

On the Behavioral Equivalence Between k-data Structures

Martins, M. A. — 2008-02-27

Throughout this paper we consider data structures as sorted algebras endowed with a designated subset of their visible part, which represents the set of truth values. The originality of our approach is the application of the standard abstract algebraic logic theory of deductive systems to the hidden heterogeneous case. We generalize the well-known equivalence relation between finite automata, which relies on the Nerode equivalence relation between states, to k-data structures. This is obtained via the Leibniz congruence, which can be viewed as a generalization of the Nerode equivalence in automata theory.

Accurate and Efficient Cache Warmup for Sampled Processor Simulation Through NSL-BLRL

Van Ertvelde, L., Hellebaut, F., Eeckhout, L. — 2008-02-27

Architectural simulation is extremely time-consuming given the huge number of instructions that need to be simulated for contemporary benchmarks. Sampled simulation that selects a number of samples from the complete benchmark execution yields substantial speedups. However, there is one major issue that needs to be dealt with in order to minimize non-sampling bias, namely the hardware state at the beginning of each sample. This is well known in the literature as the cold-start problem. The hardware structures that suffer the most from the cold–start problem are cache hierarchies. In this paper, we propose NSL–BLRL, which combines two previously proposed cache hierarchy warmup approaches, namely: no-state-loss (NSL) and boundary line reuse latency (BLRL). The idea of NSL–BLRL is to warmup the cache hierarchy using a hardware state checkpoint that stores a truncated NSL stream. The NSL stream is a least-recently used stream of (unique) memory references in the pre-sample. This NSL stream is then truncated to form the NSL–BLRL warmup checkpoint; this is done by inspecting the sample for determining how far in the pre-sample one needs to go back to accurately warmup the hardware state for the given sample. We show using SPEC CPU2000 benchmarks that NSL–BLRL is (i) nearly as accurate as BLRL and NSL for sampled processor simulation, (ii) yields simulation time speedups of several orders of magnitude compared to BLRL and (iii) is more space-efficient than NSL. As such, we conclude that NSL–BLRL is a highly efficient and accurate cache warmup strategy for sampled processor simulation.

Bi-Directional Synthesis of 4-Bit Reversible Circuits

Yang, G., Song, X., Hung, W. N. N., Perkowski, M. A. — 2008-02-27

Reversible circuits play an important role in quantum computing, which is one of the most promising emerging technologies. In this paper, we investigate the problem of optimally synthesizing 4-bit reversible circuits. We present an enhanced bi-directional synthesis approach. Owing to the exponential nature of the memory and run-time complexity, all existing methods can only perform four steps for the Controlled-Not gate NOT gate, and Peres gate library. Our novel method can achieve 12 steps. As a result, we augment the number of circuits that can optimally be synthesized by over 5 x 10⁶ times. We synthesized 1000 random 4-bit reversible circuits. The statistical analysis result supports our estimation. The quantum cost of our result is also better than the quantum cost of other approaches. The promising experimental results demonstrate the effectiveness of our approach.

Average-Case Performance Analysis Of Online Non-Clairvoyant Scheduling Of Parallel Tasks With Precedence Constraints

Li, K. — 2008-02-27

We evaluate the average-case performance of three approximation algorithms for online non-clairvoyant scheduling of parallel tasks with precedence constraints. We show that for a class of wide task graphs, when task sizes are uniformly distributed in the range [1...C], the online non-clairvoyant scheduling algorithm LL-SIMPLE has an asymptotic average-case performance bound of M/(M – (3 – (1 + 1/C)^C+1)C – 1), where M is the number of processors. For uniform probability distributions of task sizes, we present numerical and simulation data to demonstrate the accuracy of our general asymptotic average-case performance bound. We also report extensive experimental results on the average-case performance of online non-clairvoyant scheduling algorithms LL-GREEDY and LS. Algorithm LL-GREEDY has better performance than LL-SIMPLE using an improved algorithm to schedule independent tasks in the same level. Algorithm LS produces even better schedules due to a break of boundaries among levels.

Reducing Power Consumption in Wireless Sensor Networks Using a Novel Approach to Data Aggregation

Croce, S., Marcelloni, F., Vecchio, M. — 2008-02-27

Saving energy is a very critical issue in wireless sensor networks (WSNs) since sensor nodes are typically powered by batteries with a limited capacity. Since the radio is the main cause of power consumption in a sensor node, transmission/reception of data should be limited as much as possible. To this aim, we propose a novel distributed approach to data aggregation based on fuzzy numbers and weighted average operators to reduce data communication in WSNs when we are interested in the estimation of an aggregated value such as maximum or minimum temperature measured in the network. The basic point of our approach is that each node maintains an estimate of the aggregated value. Based on this estimate, the node decides whether a new value measured by the sensor on board the node or received through a message has to be propagated along the network. We show how the lifetime of the network can be estimated through the datasheet of the sensor node and the number of received and transmitted messages. We discuss and evaluate the application of our approach to the monitoring of the maximum temperature in a 100-node simulated WSN and a 12-node real WSN. Finally, we compute the estimates of the lifetimes for both the networks.

Similarity of XML-Schema Elements: A Structural and Information Content Approach

Formica, A. — 2008-02-27

EXtensible Markup Language (XML)-Schemas are the emerging standards for describing and validating semi-structured documents across the Internet, due to the rich set of modeling constructors, types and constraints they provide. Semantic similarity is growing in importance in different settings, such as digital libraries, heterogeneous databases and, in particular, the Semantic Web. The focus of this paper is the definition of a method for determining semantic similarity of XML-Schema elements in the presence of type hierarchies. Such a method has been defined by combining and revisiting: (i) the information content approach, and (ii) a method for comparing the structural components of type declarations, inspired by the maximum weighted matching problem in bipartite graphs.

The Wilkes Best Paper Award in Volume 49 (2006)

2008-01-09

The Computer Journal Special Issue on Parameterized Complexity: Foreword by the Guest Editors

Downey, R. G., Fellows, M. R., Langston, M. A. — 2008-01-09

Techniques for Practical Fixed-Parameter Algorithms

Huffner, F., Niedermeier, R., Wernicke, S. — 2008-01-09

The fixed-parameter approach is an algorithm design technique for solving combinatorially hard (mostly NP-hard) problems. For some of these problems, it can lead to algorithms that are both efficient and yet at the same time guaranteed to find optimal solutions. Focusing on their application to solving NP-hard problems in practice, we survey three main techniques to develop fixed-parameter algorithms, namely: kernelization (data reduction with provable performance guarantee), depth-bounded search trees and a new technique called iterative compression. Our discussion is circumstantiated by several concrete case studies and provides pointers to various current challenges in the field.

Innovative Computational Methods for Transcriptomic Data Analysis: A Case Study in the Use of FPT for Practical Algorithm Design and Implementation

Langston, M. A., Perkins, A. D., Saxton, A. M., Scharff, J. A., Voy, B. H. — 2008-01-09

Tools of molecular biology and the evolving tools of genomics can now be exploited to study the genetic regulatory mechanisms that control cellular responses to a wide variety of stimuli. These responses are highly complex, and involve many genes and gene products. The main objectives of this paper are to describe a novel research program centered on understanding these responses by

developing powerful graph algorithms that exploit the innovative principles of fixed parameter tractability in order to generate distilled gene sets;

producing scalable, high performance parallel and distributed implementations of these algorithms utilizing cutting-edge computing platforms and auxiliary resources;

employing these implementations to identify gene sets suggestive of co-regulation; and

performing sequence analysis and genomic data mining to examine, winnow and highlight the most promising gene sets for more detailed investigation.

As a case study, we describe our work aimed at elucidating genetic regulatory mechanisms that control cellular responses to low-dose ionizing radiation (IR). A low-dose exposure, as defined here, is an exposure of at most 10 cGy (rads). While the consequences of high doses of radiation are well known, the net outcome of low-dose exposures continues to be debated, with support in the literature for both detrimental and beneficial effects. We use genome-scale gene expression data collected in response to low-dose IR exposure in vivo to identify the pathways that are activated or repressed as a tissue responds to the radiation insult. The driving motivation is that knowledge of these pathways will help clarify and interpret physiological responses to IR, which will advance our understanding of the health consequences of low-dose radiation exposures.

On Parameterized Intractability: Hardness and Completeness

Chen, J., Meng, J. — 2008-01-09

We study the theory and techniques developed in the research of parameterized intractability, emphasizing on parameterized hardness and completeness that imply (stronger) computational lower bounds for natural computational problems. Moreover, the fundamentals of the structural properties in parameterized complexity theory, relationships to classical complexity theory and more recent developments in the area are also introduced.

Parameterized Complexity and Approximation Algorithms

Marx, D. — 2008-01-09

Approximation algorithms and parameterized complexity are usually considered to be two separate ways of dealing with hard algorithmic problems. In this paper, our aim is to investigate how these two fields can be combined to achieve better algorithms than what any of the two theories could offer. We discuss the different ways parameterized complexity can be extended to approximation algorithms, survey results of this type and propose directions for future research.

Fixed-Parameter Algorithms in Phylogenetics

Gramm, J., Nickelsen, A., Tantau, T. — 2008-01-09

We survey the use of fixed-parameter algorithms in the field of phylogenetics, which is the study of evolutionary relationships. The central problem in phylogenetics is the reconstruction of the evolutionary history of biological species, but its methods also apply to linguistics, philology or architecture. A basic computational problem is the reconstruction of a likely phylogeny (genealogical tree) for a set of species based on observed differences in the phenotype like color or form of limbs, based on differences in the genotype like mutated nucleotide positions in the DNA sequence, or based on given partial phylogenies. Ideally, one would like to construct socalled perfect phylogenies, which arise from a very simple evolutionary model, but in practice one must often be content with phylogenies whose ‘distance from perfection’ is as small as possible. The computation of phylogenies has applications in seemingly unrelated areas such as genomic sequencing and finding and understanding genes. The numerous computational problems arising in phylogenetics often are NP-complete, but for many natural parametrizations they can be solved using fixed-parameter algorithms.

Parameterized Complexity of Cardinality Constrained Optimization Problems

Cai, L. — 2008-01-09

We study the parameterized complexity of cardinality constrained optimization problems, i.e. optimization problems that require their solutions to contain specified numbers of elements to optimize solution values. For this purpose, we consider around 20 such optimization problems, as well as their parametric duals, that deal with various fundamental relations among vertices and edges in graphs. We have almost completely settled their parameterized complexity by giving either FPT algorithms or W[1]-hardness proofs. Furthermore, we obtain faster exact algorithms for several cardinality constrained optimization problems by transforming them into problems of finding maximum (minimum) weight triangles in weighted graphs.

An Overview of Techniques for Designing Parameterized Algorithms

Sloper, C., Telle, J. A. — 2008-01-09

A survey of the most important and general techniques in parameterized algorithm design is given. Each technique is explained with a meta-algorithm, its use is illustrated by examples, and it is placed in a taxonomy under the four main headings of branching, kernelization, induction and win/win.

Invitation to Fixed-Parameter Algorithms * Parameterized Complexity Theory * Parameterized Algorithmics: Theory, Practice and Prospects

Gasarch, W., Kin, K. M. — 2008-01-09