Enhanced Lagrange Decomposition for multi-objective scalable TE in SDN
Autor: | Piotr Cholda, Piotr Borylo, Andrzej Szymanski, Piotr Jaglarz |
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Rok vydání: | 2020 |
Předmět: |
Optimization problem
Computer Networks and Communications business.industry Computer science Distributed computing 020206 networking & telecommunications 02 engineering and technology Energy consumption Traffic engineering Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Decomposition method (constraint satisfaction) business Heuristics Software-defined networking Integer programming |
Zdroj: | Computer Networks. 167:106992 |
ISSN: | 1389-1286 |
DOI: | 10.1016/j.comnet.2019.106992 |
Popis: | The paradigm of Software Defined Networking opens attractive perspectives for network operators in terms of traffic engineering (TE) mechanisms. Thanks to programmability of a logically centralized network controller, static optimization techniques became applicable to optimization of resource utilization. Such an approach, combined with accurate traffic prediction, enabled deployment of globally scoped, efficient solutions. However, such an approach might pose some scalability issues which must be carefully considered. The challenge is to propose a solution able to solve multi-objective problems with non-linear constraints in large-scale networks. Networks, that are comprised of numerous nodes handling millions of flows of dynamic nature. Our work is aimed at addressing these issues. A novel, energy-aware, multi-objective, mixed integer linear programming problem is formulated, and solved using the Lagrange Decomposition method. The method is enhanced by novel adoption of ergodic sequences in order to improve quality of a primal solution recovered from a dual one. The proposed heuristics is carefully assessed regarding its time-efficiency, applicability to multi-objective optimization problems and problems with constraints of non-linear nature, such as energy consumption. The presented method is of significant practical value, and as such is a direct response to traffic engineering scalability challenges in Software Defined Networks. |
Databáze: | OpenAIRE |
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