Stellar turbulence : proceedings of colloquium 51 of the International Astronomical Union, held at the University of Western Ontario, London, Ontario, Canada, August 27-30, 1979 /

Stellar turbulence : proceedings of colloquium 51 of the International Astronomical Union, held at the University of Western Ontario, London, Ontario, Canada, August 27-30, 1979 /

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Bibliographic Details
Imprint:Berlin ; New York : Springer-Verlag, 1980.
Description:viii, 308 p. : ill. ; 24 cm.
Language:English
Series:Lecture notes in physics 114
Lecture notes in physics 114
Subject:
Stars -- Atmospheres -- Congresses.
Turbulence -- Congresses.
Stars -- Atmospheres.
Turbulence.
Conference papers and proceedings.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/347344
Hidden Bibliographic Details
Other authors / contributors:Gray, David F., 1938-
Linsky, J. L. (Jeffrey L.), 1941-
International Astronomical Union.
ISBN:0387097376
Notes:Includes bibliographies.
Table of Contents:
  • 1. Introduction
  • 1.1. Continuous-Rate Packet-Switched Networks
  • 1.2. Tiered-Service Networks
  • 1.3. Multi-Tiered Pricing Schemes
  • Part I. Theory
  • 2. The Directional p-Median Problem: Definition and Applications
  • 2.1. The p-Median Problem
  • 2.1.1. Continuous vs. Discrete Space
  • 2.2. A New Notion of Distance: The Directional Distance Metric
  • 2.3. Summary of Complexity Results
  • 2.4. Applications
  • 3. Bandwidth Tiered Service: Deterministic Demands
  • 3.1. Bandwidth Tiered Service as a DPM1 Problem
  • 3.2. A Linear Complexity Algorithm of DPM1
  • 3.2.1. Graph Representation of DPM1
  • 3.2.2. Monge Condition and Totally Monotone Matrices
  • 3.2.3. Efficient Dynamic Programming Algorithm for DPM1
  • 3.3. Impact of Tiered Service on Network Resources
  • 3.4. Joint Optimization of the Number and Magnitude of Service Tiers
  • 4. Bandwidth Tiered Service: TDM Emulation
  • 4.1. TDM Emulation As A Constrained DPM1 Problem
  • 4.1.1. Optimal Solution to TDM-DPM1 for Fixed
  • 4.1.2. The Behavior Of The TDM-DPM1 Objective Function
  • 4.1.3. An Exhaustive Search Algorithm for TDM-DPM1
  • 4.1.4. Optimization Heuristics
  • 4.2. Performance Evaluation
  • 4.2.1. Algorithm Comparison
  • 4.2.2. Impact on the Network Provider: Bandwidth Penalty Due to TDM Emulation
  • 4.2.3. Impact on Users: Blocking Probability
  • 5. Bandwidth Tiered Service: Stochastic Demands
  • 5.1. The Stochastic Directional p-Median Problem
  • 5.2. Optimal Solution Through Nonlinear Programming
  • 5.2.1. Example: Solution for the Uniform Demand Distribution
  • 5.2.2. Example: Solution for the Increasing Demand Distribution
  • 5.3. An Efficient Approximate Solution
  • 5.3.1. An Approximate Formulation of SDPM1
  • 5.3.2. Optimal Solution to Approximate-SDPM1
  • 5.3.3. Convergence of the Approximate Solution
  • 6. Tiered Structures for Multiple Services
  • 6.1. The Directional p-Median Problem on the Plane
  • 6.2. Heuristic Algorithms for Discrete-PM2
  • 6.2.1. Effect of Distance Properties on Computational Effort
  • 6.2.2. Teitz and Bart (TB) Vertex Substitution Heuristic
  • 6.2.3. The Global/Regional Interchange Algorithm (GRIA)
  • 6.2.4. Heuristic Concentration (HC)
  • 6.3. A Decomposition Heuristic for DPM2
  • 6.3.1. Evaluation of the Decomposition Heuristic
  • 6.4. The Class of Strictly Dominating Solutions for DPM2
  • Part II. Economics
  • 7. Economic Model for Bandwidth Tiered Service
  • 7.1. Pricing of Internet Services
  • 7.2. The Network Context
  • 7.3. Economic Model for Sizing of Service Tiers
  • 7.3.1. Maximization of Expected Surplus
  • 7.3.2. Solution Through Nonlinear Programming
  • 7.3.3. An Efficient Approximate Solution
  • 7.3.4. Optimizing the Number of Service Tiers
  • 7.4. Optimal Pricing Based on Nash Bargaining
  • 7.4.1. The Single Tier Case
  • 7.4.2. The Multiple Tier Case
  • 7.5. Performance Evaluation
  • 7.5.1. Convergence of the Approximate Solution
  • 7.5.2. Optimal Sizing of Service Tiers
  • 7.5.3. Optimal Pricing of Service Tiers
  • 7.5.4. Accounting for the Cost of Service Tiers
  • 8. Service Tiering As A Market Segmentation Strategy
  • 8.1. Economic Model of User Diversity
  • 8.2. The Single Tier Case
  • 8.3. The Multiple Tier Case: Market Segmentation
  • 8.3.1. The MAX-S Problem with Fixed Tiers
  • 8.3.2. Approximate Solution to the MAX-S Problem
  • 8.4. Performance Evaluation
  • 8.4.1. Convergence of the Approximate Solution
  • 8.4.2. Tier Structure Comparison
  • 9. Tiered Service Bundling Under Budget Constraints
  • 9.1. Economic Model of Service Bundling
  • 9.2. Approximate Solution to the MAX-ES-2D Problem
  • 9.2.1. The Fixed Tier Case
  • 9.2.2. Cost Minimization on an Indifference Curve
  • 9.2.3. Joint Optimization of Service Tiers and Prices
  • 9.3. Performance Evaluation
  • Part III. Quality of Service (QoS)
  • 10. Packet Scheduling
  • 10.1. Scheduling Objectives and Requirements
  • 10.2. Packet Scheduling Disciplines
  • 10.2.1. Timestamp-Based Schedulers
  • 10.2.2. Frame-Based Schedulers
  • 10.2.3. Hybrid Schedulers
  • 11. Tiered-Service Fair Queueing (TSFQ)
  • 11.1. Tiered-Service Fair Queueing (TSFQ)
  • 11.1.1. Logical Operation
  • 11.1.2. Virtual Time Computation
  • 11.2. Intra-Tier Scheduler: The Fixed-Size Packet Case
  • 11.2.1. Queue Structure and Operation
  • 11.3. Intra-Tier Scheduler: The Variable-Size Packet Case
  • 11.3.1. Queue Structure and Operations
  • 11.3.2. Packet Sorting Operations
  • 11.3.3. Elimination of Packet Sorting Operations
  • 11.4. Experimental Evaluation of TSFQ
  • 11.4.1. Testbed and Experimental Setup
  • 11.4.2. Performance Results
  • References
  • Index
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