Exact and Approximate Algorithms for Assignment Problems in Distributed Systems

Exact and Approximate Algorithms for Assignment Problems in Distributed Systems
Author: David Fernandez-Baca
Publisher:
Total Pages: 22
Release: 1992
Genre: Distributed parameter systems
ISBN:

Abstract: "We present exact dynamic programming algorithms for two variants of the task assignment problem on distributed systems: (1) finding a minimum-cost assignment when one of the processors has limited memory and (2) finding an assignment that minimizes the maximum processor load. These procedures lead to approximation schemes for the case where the communication graph is a partial k-tree. In contrast to these results, we show that, for arbitrary graphs, no fully polynomial time approximation schemes exist unless P = NP. Finally, we discuss implementation details for our algorithms and summarize our experimental results."

Approximation Algorithms for Certain Assignment Problems in Distributed Systems

Approximation Algorithms for Certain Assignment Problems in Distributed Systems
Author: Iowa State University. Dept. of Computer Science
Publisher:
Total Pages: 44
Release: 1991
Genre: Distributed parameter systems
ISBN:

Abstract: "We consider two variants of the task assignment problem for distributed systems. The first is the problem of finding a minimum cost assignment when one of the processors has a limited memory. The second is the problem of finding an assignment that minimizes the maximum processor load. Both problems are NP-hard, even if the communication graph is a tree. We present exact algorithms and approximation schemes for these problems for the case where the communication graph is a partial k-tree. Faster algorithms are presented for the case of trees with uniform costs. We also show that, if the communication graph is unrestricted, there is no fully polynomial-time approximation scheme for the memory-constrained problem unless P = NP."

Iterative Methods in Combinatorial Optimization

Iterative Methods in Combinatorial Optimization
Author: Lap Chi Lau
Publisher: Cambridge University Press
Total Pages: 255
Release: 2011-04-18
Genre: Computers
ISBN: 1139499394

With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.

Distributed Algorithms

Distributed Algorithms
Author: Wan Fokkink
Publisher: MIT Press
Total Pages: 242
Release: 2013-12-06
Genre: Computers
ISBN: 0262318954

A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation. This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. An appendix offers pseudocode descriptions of many algorithms. Distributed algorithms are performed by a collection of computers that send messages to each other or by multiple software threads that use the same shared memory. The algorithms presented in the book are for the most part “classics,” selected because they shed light on the algorithmic design of distributed systems or on key issues in distributed computing and concurrent programming. Distributed Algorithms can be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field.