Adapting Parallel Algorithms to the W Stream Model with Applications to Graph Problems 1st Edition by Camil Demetrescu, Bruno Escoffier, Gabriel Moruz, Andrea Ribichini ISBN 9783540744566

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ISBN 10: 
ISBN 13: 9783540744566
Author: Camil Demetrescu, Bruno Escoffier, Gabriel Moruz, Andrea Ribichini

In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for several classical combinatorial problems in the W − Stream . In this model, at each pass one input stream is read and one output stream is written; streams are pipelined in such a way that the output stream produced at pass i is given as input stream at pass i + 1. Our techniques give new insights on developing streaming algorithms and yield optimal algorithms (up to polylog factors) for several classical problems in this model including sorting, connectivity, minimum spanning tree, biconnected components, and maximal independent set.

Adapting Parallel Algorithms to the W-Stream Model, with Applications to Graph Problems 1st Table of contents:

• Introduction
  1.1 Motivation and Background
  1.2 The W-Stream Model
  1.3 Objectives and Contributions
  1.4 Organization of the Paper

• Preliminaries
  2.1 Parallel Algorithms
  2.2 The W-Stream Model: Definition and Features
  2.3 Graph Problems: Key Concepts
  2.4 Previous Work on Streaming Models and Graph Algorithms

• W-Stream Model: A Detailed Overview
  3.1 The W-Stream Model Architecture
  3.2 Comparison with Other Streaming Models
  3.3 Algorithmic Challenges in W-Stream
  3.4 Data Structure Requirements in W-Stream

• Parallel Algorithm Design
  4.1 General Framework for Parallel Algorithms
  4.2 Adapting Parallel Algorithms to the W-Stream Model
  4.3 Optimization Techniques for Streaming Algorithms
  4.4 Handling Large Data in W-Stream

• Applications to Graph Problems
  5.1 Graph Representation in Streaming Models
  5.2 Subgraph Detection in W-Stream
  5.3 Connectivity and Shortest Path Problems
  5.4 Graph Coloring and Other NP-Hard Problems in W-Stream
  5.5 Applications to Dynamic Graphs

• Algorithmic Results and Complexity Analysis
  6.1 Time Complexity of Adapted Algorithms
  6.2 Space Complexity and Streaming Efficiency
  6.3 Approximation Ratios for Graph Problems
  6.4 Comparison with Traditional Parallel Algorithms

• Experimental Results
  7.1 Experimental Setup and Benchmarks
  7.2 Performance Evaluation of Graph Algorithms in W-Stream
  7.3 Scalability and Efficiency Analysis
  7.4 Comparison with Existing Streaming and Parallel Approaches

• Discussion and Future Directions
  8.1 Insights Gained from Adapting Parallel Algorithms
  8.2 Challenges in Scaling Graph Algorithms on W-Stream
  8.3 Open Problems and Potential Extensions
  8.4 Future Research Directions

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