In this project, we develop the first to our knowledge REpulsive-BAsed Traffic Engineering (REBATE) approach for dynamic scale-free networks. REBATE is built upon dual principles of the demand-aware TE and fundamentals properties of hyperbolic spaces. Using trace-driven numerical simulations from this repository, we show how REBATE can reduce the maximum link utilization up to 25% when compared to a common geometric routing-based traffic steering. However, REBATE can be still subject to practically large optimality gaps compared to both demands-aware and oblivious TE. Thus, our work should pave the way for more efficient TE in the nextgeneration dynamic scale-free networks.
2019 VIMAN laboratory, Computer Science Department, University of Missouri-Columbia.
Updated January 12, 2019 by Dmitrii Chemodanov
All feedback appreciated to dycbt4@mail.missouri.edu
This project is licensed under the GNU General Public License - see the LICENSE file for details
The source code of the REBATE numerical simulations. Java simulation is used to evaluate our novel REBATE algorithm with alternative geometric hyperbolic routing solutions in dynamic scale-free networks using Tier-1 core network topology.
The distribution tree contains:
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README
- this file
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LICENSE
- GNU license file
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build.xml (build file for ant)
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lib/ (java library dependencies)
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results/ (folder to store simulation results of experiments in a form of txt files)
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src/ (java source files)
``` edu/mu/vimanlab/chemodanov/rebate/main/Main (java sim main file) ```
Compiling and run of this software requires Ant, Java 1.8 and IBM ILOG CPLEX Optimization Studio (v.12.7 or higher) installed. These can be downloaded respectively from:
http://jakarta.apache.org/ant/index.html
http://java.sun.com/j2se/
http://www.ibm.com/products/ilog-cplex-optimization-studio
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Specify path to cplex in build.xml file
<property name="cplex_path" location="/Users/user1/Applications/IBM/ILOG/CPLEX_Studio127/cplex/bin/x86-64_osx"/> -
clean
ant clean -
compile
ant -
run any of 4 experiments (0: the general experiment comparing optimal, geometric hyperbolic routing and rebate in terms of their optimization; experiment 1: a cold-down propery evaluation experiment; 2: a TTL experiment to access the rebate dynamic packet header size; 3: an experiment with network dynamics/failures)
ant -Dexperiment=(from 0 to 3) run