5089320
Better approximation guarantees for job-shop scheduling
Job-shop scheduling is a classical NP-hard problem. Shmoys, Stein, and Wein presented the first polynomial-time approximation algorithm for this problem that has a good (polylogarithmic) approximation guarantee. We improve the approximation guarantee of their work and present further improvements for some important NP-hard special cases of this problem (e.g., in the preemptive case where machines can suspend work on operations and later resume). We also present NC algorithms with improved approximation guarantees for some NP-hard special cases.
12370019
New algorithmic aspects of the Local Lemma with applications to routing and partitioning
The Lovasz local lemma (LLL)is a powerful tool that is increasingly playing a valuable role in computer science. The original lemma was nonconstructive; a breakthrough of Beck and its generalizations (due to Alon and Molloy and Reed)have led to constructive versions. However, these methods do not capture some classes of applications of the LLL. We make progress on this by providing algorithmic approaches to two families of applications of the LLL. The first provides constructive versions of certain applications of an extension of the LLL (modeling, e.g., hypergraph-partitioning and low-congestion routing problems); the second provides new algorithmic results on constructing disjoint paths in graphs. Our results can also be seen as constructive upper bounds on the integrality gap of certain packing problems. One common theme of our work is a "gradual rounding" approach.
8959226
Low-Discrepancy Sets For High-Dimensional Rectangles: A Survey
A sub-area of discrepancy theory that has received much attention in computer science recently, is that of explicit constructions of low-discrepancy point sets for various types of rectangle families in high dimension. This research has led to interesting applications in error-control coding, distributed protocols, Web document filtering, derandomization, and other areas. We give a short survey of this area here.
8868988
Contention resolution with constant expected delay
We study contention resolution in a multiple-access channel such as the Ethernet channel. In the model that we consider, n users generate messages for the channel according to a probability distribution. Raghavan and Upfal have given a protocol in which the expected delay (time to get serviced) of every message is O(log n) when messages are generated according to a Bernoulli distribution with generation rate up to about 1/10. Our main results are the following protocols: (a) one in which the expected average message delay is O(1) when messages are generated according to a Bernoulli distribution with a generation rate smaller than 1/e, and (b) one in which the expected delay of any message is O(1) for an analogous model in which users are synchronized (i.e., they agree about the time), there are potentially an infinite number of users, and messages are generated according to a Poisson distribution with generation rate up to 1/e. (Each message constitutes a new user.)
To achieve (a), we first show how to simulate (b) using n synchronized users, and then show how to build the synchronization into the protocol.
39527744
Efficient Algorithms for the Minimum Weighted Dominating Clique Problem on Permutation Graphs
Given a graph G=(V, E) with real weights assigned to its vertices, a clique of G that also dominates its vertex set V, is called a dominating clique (DC) of G. Given a permutation graph G with all its vertices having nonnegative weights, and its permutation representation, the problem addressed in this paper is that of finding any minimum weight DC of G. We improve the existing O(|V|2) algorithm for this problem to O(|V|log|V|). The space complexity of our algorithm is O(|V|). We also present a |V| processor, O(log|V|) time, O(|V|log|V|) space parallel EREW PRAM algorithm for this problem.
23028632
Mechanism design for intellectual property rights protection
Estimates for the annual size of software piracy are in the region of $15 billion. The problem is also manifest in other forms of intellectual property. The explosive growth of the Internet and other communications networks has accentuated this problem. The new infrastructure has facilitated piracy by effectively reducing the cost of copying to negligible levels. (Recently, the FBI launched an operation called “Cyber Strike,” with the objective of curbing illegal copying and distribution of software over computer networks.) A naive suggestion has been that intellectual property rights (IPR) violation is actually beneficial from the social point of view, since it decreases the monopoly power of the provider. However, the flip side of this argument is that the IPR violations decrease the incentive for innovation because they lead to lower profits. In this paper, several mechanisms for IPR protection are designed. The mechanisms involve two tools: the level of enforcement (i.e., the probability that an IPR violator will be apprehended) and the penalty to be levied on an apprehended IPR violator. These tools are analyzed by considering the tradeoff between social welfare and the provider’s profit. The paper considers a provider who wants to maximize his profit and a policy maker who wants to maximize “net” social welfare (defined as welfare less any costs of enforcement), subject to a target profit for the provider. The consumers choose from among three options: buy, copy, or stay out of the market. A game-theoretic framework is adopted, where the policy maker, the provider, and the consumers get to move in that order. Among the results, the research shows that
2075186
An assessment of submissions made to the Predictive Toxicology Evaluation Challenge
Constructing "good" models for chemical carcinogenesis was identified in IJCAI-97 as providing a substantial challenge to "knowledge discovery" programs. Attention was drawn to a comparative exercise which called for predictions on the outcome of 30 rodent carcinogenicity bioassays. This-the Predictive Toxicology Evaluation (or PTE) Challenge - was seen to provide AI programs with an opportunity to participate in an enterprise of scientific merit, and a yardstick for comparison against strong competition. Here we provide an assessment of the machine learning (ML) submissions made. Models submitted are assessed on: (1) their accuracy, in comparison to models developed with expert collaboration; and (2) their explanatory value for toxicology. The principal findings were: (a) using structural information available from a standard modelling package, layman-devised features, and outcomes of established biological tests, results from MLderived models were at least as good as those with expert-derived techniques. This was surprising; (b) the combined use of structural and biological features by ML-derived models was unusual, and suggested new avenues for toxicology modelling. This was also unexpected; and (c) significant effort was required to interpret the output of even the most "symbolic" of ML-derived models. Much of this could have been alleviated with measures for converting the results into a more "toxicology-friendly" form. As it stands, their absence is sufficient to prevent a whole-hearted acceptance of these promising methods by toxicologists. This suggests that ML techniques have been able to respond -not fully, but nevertheless substantially -to the PTE Challenge.
16314241
End-to-end packet-scheduling in wireless ad-hoc networks
Packet-scheduling is a particular challenge in wireless networks due to interference from nearby transmissions. A distance-2 interference model serves as a useful abstraction here, and we study packet routing and scheduling under this model. The main focus of our work is the development of fully-distributed (decentralized) protocols. We present polylogarithmic/constant factor approximation algorithms for various families of disk graphs (which capture the geometric nature of wireless-signal propagation), as well as near-optimal approximation algorithms for general graphs. The packet-scheduling work by L eighton, Maggs and Rao (Combinatorica, 1994) and a basic distributed coloring procedure, originally due to Luby (J. Computer and System Sciences, 1993), underlie many of our algorithms. Experimental work of Finocchi, Panconesi, and Silvestri (SODA 2002) showed that a natural modification of Luby's algorithm leads to improved performance, and a rigorous explanation of this was left as an open question; we prove that the modified algorithm is provably better in the worst-case. Finally, using simulations, we study the impact of the routing strategy and the choice of parameters on the performance of our distributed algorithm for unit disk graphs.
37521671
Latency tolerance through parallelization of time in scientific applications
Emerging computing environments, such as the Grid, promise enormous raw computational power. However, effective use of such platforms is often difficult, because conventional spatial decomposition leads to fine granularity, resulting in high communication overhead. We introduce the concept of guided simulations to parallelize along the time domain. Here, we use the fact that typically results of other simulations of closely related problems are available. In this approach, we automatically and dynamically determine a relationship between old simulations and the one being performed, and use this to parallelize along the time domain. We demonstrate the validity of this approach by applying the technique to an important application involving molecular dynamics simulation of nanomaterials. In this application, spatial decomposition is not effective due to the small size of the physical system. However, time parallelization is effective, since the granularity is much coarser. We also mention how this approach can be extended to make it inherently fault tolerant.
6168494
Approximation algorithms for scheduling on multiple machines
We develop a single rounding algorithm for scheduling on unrelated parallel machines; this algorithm works well with the known linear programming, quadratic programming, and convex programming-relaxations for scheduling to minimize completion time, makespan, and other well-studied objective functions. We obtain the following applications for the general setting of unrelated parallel machines: (i) a bicriteria algorithm for a schedule whose weighted completion-time and makespan simultaneously exhibit the current-best individual approximations for these criteria (3/2 and 2, respectively); (ii) better-than-two approximation guarantees for scheduling under the L/sub p/ norm for all 1 < p < /spl infin/, improving on the 2-approximation algorithms of Azar & Epstein; and (iii) the first constant-factor multicriteria approximation algorithms that handle the weighted completion-time and any given collection of integer L/sub p/ norms. Our algorithm yields a common generalization of rounding theorems due to Karp et al and Shmoys & Tardos; among other applications, this yields an improved approximation for scheduling with resource-dependent processing times studied by Grigoriev et al.
15947258
Domain Decomposition for Particle Methods on the Sphere
We present an algorithm for efficient parallelization of particle methods when the domain is the surface of a sphere. Such applications typically arise when dealing with directional data. We propose a domain decomposition scheme based on geometric partitioning that provides domains suitable for practical implementation. This algorithm has the advantage of being fast enough to be applied dynamically, and at the same time provides good partitions, comparable in quality to those produced by spectral graph partitioning schemes.