23

In-Advance Bandwidth Scheduling in e-Science Networks

Yan Li, Eunsung Jung, Sanjay Ranka, Nageswara S. Rao, and Sartaj Sahni

Contents

23.1 Introduction
23.2 Temporal Network Model
23.2.1 Slotted Time
23.2.2 Continuous Time
23.3 Single-Path Scheduling
23.3.1 Problem Definitions
23.3.2 Path Computation Algorithms
23.3.2.1 Fixed Slot
23.3.2.2 Maximum Bandwidth in a Slot
23.3.2.3 Maximum Duration
23.3.2.4 First Slot
23.3.2.5 All Slots
23.3.2.6 All Pairs, All Slots
23.3.3 Performance Metrics
23.3.3.1 Space Complexity
23.3.3.2 Time Complexity
23.3.3.3 Effectiveness
23.3.4 Experiments
23.4 Multiple-Path Scheduling
23.4.1 Problem Definition
23.4.1.1 Data Structures
23.4.2 Optimal Solution and N-Batch Heuristics
23.4.2.1 N-Batch Heuristics
23.4.3 Online Scheduling Algorithms
23.4.3.1 Greedy Algorithm
23.4.3.2 Greedy Scheduling with Finish Time Extension (GOS-E)
23.4.3.3 K-Path Algorithms
23.4.4 Experimental Evaluation
23.4.4.1 Experimental Framework
23.4.4.2 Single Start Time Scheduling (SSTS)
23.4.4.3 Multiple Start Time Scheduling (MSTS)
23.4.4.4 GOS vs. GOS-E
23.5 Conclusion
Acknowledgment
References

23.1 Introduction

Many large-scale scientific and commercial applications produce large amounts of data, of the order of terabytes to petabytes, which must be transferred across wide-area networks. For example, for an e-Science application, data sets produced on a supercomputer in Los Angeles may need to be streamed to a remote storage center in Houston for analysis. The results are ...

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