Optimal strategy for graceful network upgrade
Download
1 / 22

Optimal Strategy For Graceful Network Upgrade - PowerPoint PPT Presentation


  • 68 Views
  • Uploaded on

Optimal Strategy For Graceful Network Upgrade. Ram Keralapura, UC-Davis Chen-Nee Chuah, UC-Davis Yueyue Fan, UC-Davis. Outline. Introduction: Graceful Network Upgrade Problem Two-Phase Framework Phase-1: Finding Optimal End-State Phase-2: Multistage Node Addition

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Optimal Strategy For Graceful Network Upgrade' - yardley-hanson


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Optimal strategy for graceful network upgrade

Optimal Strategy For Graceful Network Upgrade

Ram Keralapura, UC-Davis

Chen-Nee Chuah, UC-Davis

Yueyue Fan, UC-Davis


Outline
Outline

  • Introduction:

    Graceful Network Upgrade Problem

  • Two-Phase Framework

    • Phase-1: Finding Optimal End-State

    • Phase-2: Multistage Node Addition

  • Numerical Example and Results

  • Conclusions and Future Directions

University of California, Davis


Introduction
Introduction

  • Network Upgrade

    • Adding new nodes and links into an existing operational network

    • Does not refer to upgrading individual network components

  • “Graceful” Network Upgrade

    • Network performance deterioration from the perspective of existing customers should be minimized during upgrade process

University of California, Davis


Introduction cont d
Introduction (cont’d)

  • Steps for Graceful Network Upgrade

    • Identifying set of potential locations where new nodes can be added

    • Determining a subset of potential locations where nodes should added and how they should be connected to the rest of the network

    • Determining an ideal sequence for adding nodes and links into the network

University of California, Davis


Scenario
Scenario

  • Tier-1 ISP backbone networks

    • Nodes  Points of Presence (PoPs)

    • Links  Inter-POP links

  • Assumptions:

    • ISPs can reliably determine the future traffic demands when new nodes are added

    • ISPs can reliably estimate the revenue associated with the addition of every new node

      • Revenues resulting from different node additions are independent of each other

University of California, Davis


Network performance customers view
Network Performance: Customers’ View

  • Link failures are the primary reason for performance deterioration in tier-1 ISP backbone networks

  • Impact of link failures: Service Disruption (SD) Time and Traffic Disruption (TD)

    • Depends on the operational network conditions like shortest paths between nodes, exit points for prefixes, traffic demands, etc.

  • Adding new nodes and links can change the above operational network conditions

University of California, Davis


Graceful network upgrade
Graceful Network Upgrade

  • Given a budget constraint:

    • Find where to add new nodes and how they should be connected to the rest of the network

    • Determine optimal sequence for this upgrade

  • Two-Phase Framework

    • Phase-1: Finding Optimal End State

      • Formulated as an optimization problem

    • Phase-2: Multistage Node Addition Strategy

      • Formulated as a multistage dynamic programming (DP) problem

University of California, Davis


Phase 1 finding optimal end state
Phase-1: Finding Optimal End State

Revenue

  • Objective Function:

    Subject to:

    • Budget constraint:

    • Node degree constraint

Link installation cost

Node installation cost

Budget

University of California, Davis


Phase 1 finding optimal end state cont d
Phase-1: Finding Optimal End State (Cont’d)

  • SD Time constraint

  • TD constraint

  • Link utilization constraint

  • Can be solved by non-linear programming techniques – tabu search, genetic algorithms

  • University of California, Davis


    Phase 2 multistage node addition
    Phase-2: Multistage Node Addition

    • Assumptions:

      • Already have the solution from Phase-1

      • ISP wants to add one node and its associated links into the network at every stage

        • Hard to debug if all nodes are added simultaneously

        • Node/link construction delays

        • Sequential budget allocation

      • Time period between every stage could range from several months to few years

    University of California, Davis


    Phase 2 multistage node addition1

    Cost instead of constraints to ensure we

    find feasible solutions

    Phase-2: Multistage Node Addition

    • Multistage dynamic programming problem with costs for performance degradation

      • Maximize (revenue – cost)

    • Cost considered:

      • Node degree

      • Link utilization

      • SD Time

      • TD Time

    University of California, Davis


    Numerical example

    Potential Node Locations

    Original Nodes

    Numerical Example

    1

    Chicago

    Seattle

    C

    New York

    D

    A

    San Jose

    B

    2

    3

    Phoenix

    Atlanta

    Dallas

    4

    Miami

    University of California, Davis


    Numerical example phase 1 solution

    New Links

    New Nodes

    Original Nodes

    Original Links

    1

    Chicago

    Seattle

    C

    New York

    D

    A

    San Jose

    B

    2

    3

    Phoenix

    Atlanta

    Dallas

    4

    Miami

    Solution from Phase-1

    Numerical Example – Phase-1 Solution

    University of California, Davis


    Numerical example result
    Numerical Example – Result

    University of California, Davis


    Numerical example phase 2 solution

    New Links

    New Nodes

    Original Nodes

    Original Links

    Numerical Example – Phase-2 Solution

    1

    Chicago

    Seattle

    C

    New York

    D

    A

    San Jose

    B

    2

    3

    Phoenix

    Atlanta

    Dallas

    4

    Miami

    Solution from Phase-1

    University of California, Davis


    Numerical example phase 2 solution1
    Numerical Example – Phase-2 Solution

    • Ignoring SD time and TD in Phase-2 results in significant performance deterioration for customers

    University of California, Davis


    Conclusions
    Conclusions

    • We propose a two phase framework for graceful upgrade of operational network

      • Important to consider performance from users’ perspective (service/traffic disruptions)

    • We illustrated the feasibility of our approach using a simple numerical example

    • The framework is flexible and can be easily adapted to include other constraints or scenario-specific requirements

    University of California, Davis


    Future work
    Future Work

    • Need to relax simplifying assumptions

      • Revenue and traffic demands in the network after node additions could dynamically change because of endogenous and exogenous effects

        • Adaptive and stochastic dynamic programming

      • Revenue generated by adding one node is usually not independent of other node additions

      • Uncertainty in predicting traffic demands

    • Applications of this framework in different environments

      • Wireless networks (WiFi, WiMax, celllular)

    University of California, Davis


    Questions
    Questions?

    • http://www.ece.ucdavis.edu/rubinet/

    University of California, Davis


    Phase 2 multistage node addition2
    Phase-2: Multistage Node Addition

    • Multistage dynamic programming problem with costs for performance degradation

    • Cost of node degree:

    • Cost of link utilization:

    University of California, Davis


    Phase 2 multistage node addition3
    Phase-2: Multistage Node Addition

    • Cost of SD Time:

    • Cost of TD:

    University of California, Davis


    Phase 2 multistage node addition4
    Phase-2: Multistage Node Addition

    • Functional equation:

    University of California, Davis