Mapping Algorithms provided for ESCAPE
This orchestration algorithm maps service graphs (consisting of (virtual) network functions and logical connections) to resource graphs (consisting of virtualized node and network resources) in a greedy backtracking manner, based on heuristics and customizable preference value calculations.
- Python 2.7.6+
- NFFG 1.0
- NetworkX 1.11+
Files required to run the algorithm:
* MappingAlgorithms.py ---> function MAP() is the entry point * Alg1_Core.py * GraphPreprocessor.py * Alg1_Helper.py * BacktrackHandler.py * UnifyExceptionTypes.py
Other files (appropriate PYTHONPATH setting maybe required, see StressTest-small.py):
* StressTest-small.py * CarrierTopoBuilder.py * MIPBaseline.py * milp_solution_in_nffg.py
Utilities (can be outdated):
* BatchTest-params.py * ParameterSearch.py * SimulatedAnnealing.py * StressTest.py * StressTest-agressive.py * StressTest-decent.py * StressTest-gwin.py * StressTest-normal.py * StressTest-sc8decent.py * StressTest-sharing.py * calc_mapping_times.py * calc_res_util_metrics.py * count_bt_successes.py * count_milp_successes.py * night_test.py
The parameters of the algorithm are:
* ``enable_shortest_path_cache`` -- saves the calculated shortest paths for the resource graph into a file for later usage. * ``bw_factor``, ``res_factor``, ``lat_factor`` -- the coefficients of bandwidth, node resources and latency respectively, during network function placement preference value. Their sum is suggested to be 3.0. * ``bt_limit`` -- Backtracking depth limit of the algorithm. * ``bt_branching_factor`` -- The number of the top preferred placement options to remember. * ``mode`` -- Mapping operation mode: _NFFG.MODE_REMAP_ -- All network function and every reservation attribute of the resource graph are ignored. _NFFG.MODE_ADD_ -- The stored VNF information in the substrate graph is interpreted as reservation state. Their resource requirements are subtracted from the available. If an ID is present in both the substrate and request graphs, the resource requirements (and the whole instance) will be updated. _NFFG.MODE_DEL_ -- All the elements of the request will be deleted from the resource graph which has all of its connected components speficied in the service graph. * (``shortest_paths`` -- The shortest path matrix can be added as an input Python object.) * (``return_dist`` -- The MAP function returns a tuple of the mapped NFFG and the shortest path Python object)
An example invocation of the orchestration algorithm for mapping a service graph to a resource graph both given by an NFFG file, can be found in the main of MappingAlgorithms.py.
The documentation for the input structure formats can be found in nffg-doc.pdf.
For more details on the context and design of the algorithm is (will be) available in the paper published in
IEEE NFV-SDN -- 2nd Workshop for Orchestration for Software Defined Infrastructure (O4SDI), 07th November 2016, Palo Alto, CA, USA. title: Efficient Service Graph Embedding: A Practical Approach authors: Balázs Németh, Balázs Sonkoly (Budapest University of Technology and Economics), Matthias Rost (Technische Universität Berlin), Stefan Schmid (Aalborg University)
Licensed under the Apache License, Version 2.0; see LICENSE file.
Copyright (C) 2017 by Balazs Nemeth <firstname.lastname@example.org>