Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants
At the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements....
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/9/1/136 |
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| author | Valerio Frascolla Cristina K. Dominicini Marcia H. M. Paiva Gilles Caporossi Marcelo Antonio Marotta Moises R. N. Ribeiro Marcelo E. V. Segatto Magnos Martinello Maxwell E. Monteiro Cristiano Bonato Both |
| author_facet | Valerio Frascolla Cristina K. Dominicini Marcia H. M. Paiva Gilles Caporossi Marcelo Antonio Marotta Moises R. N. Ribeiro Marcelo E. V. Segatto Magnos Martinello Maxwell E. Monteiro Cristiano Bonato Both |
| author_sort | Valerio Frascolla |
| collection | DOAJ |
| description | At the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements. These developments put increasing pressure on network backhaul and drive the need for a re-examination of traditional backhaul topologies. Challenges of impending networks cannot be tackled by star and ring approaches due to their lack of intrinsic survivability and resilience properties, respectively. In support of this re-examination, we propose a backhaul topology design method that formulates the topology optimization as a graph optimization problem by capturing both the objective and constraints of optimization in graph invariants. Our graph theoretic approach leverages well studied mathematical techniques to provide a more systematic alternative to traditional approaches to backhaul design. Specifically, herein, we optimize over some known graph invariants, such as maximum node degree, topology diameter, average distance, and edge betweenness, as well as over a new invariant called node Wiener impact, to achieve baseline backhaul topologies that match the needs for resilient future wireless and optical networks. |
| first_indexed | 2024-04-12T19:51:04Z |
| format | Article |
| id | doaj.art-691aba005fe14c0287cd36648443c548 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-12T19:51:04Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-691aba005fe14c0287cd36648443c5482022-12-22T03:18:50ZengMDPI AGApplied Sciences2076-34172019-01-019113610.3390/app9010136app9010136Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph InvariantsValerio Frascolla0Cristina K. Dominicini1Marcia H. M. Paiva2Gilles Caporossi3Marcelo Antonio Marotta4Moises R. N. Ribeiro5Marcelo E. V. Segatto6Magnos Martinello7Maxwell E. Monteiro8Cristiano Bonato Both9Intel Communication and Devices Group, Intel Deutschland GmbH, Am Campeon 10-12, 85579 Neubiberg, GermanySoftware Defined Networks Research Group, Department of Informatics, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilLabTel (Laboratory of Telecommunications), Department of Electrical Engineering, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilGERAD & HEC Montréal, 3000, Chemin de la Côte-Sainte-Claire, Montréal, QC H3T 2A7, CanadaInstitute of Informatics—Federal University of Rio Grande do Sul, Av. Bento Gonçalves 9500, Porto Alegre 91501-970, Rio Grande do Sul, BrazilLabTel (Laboratory of Telecommunications), Department of Electrical Engineering, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilLabTel (Laboratory of Telecommunications), Department of Electrical Engineering, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilSoftware Defined Networks Research Group, Department of Informatics, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilLabTel (Laboratory of Telecommunications), Department of Electrical Engineering, Federal University of Espírito Santo—UFES, Av. Fernando Ferrari, 514, Vitória 29075-910, Espírito Santo, BrazilExact and Applied Social Sciences Department (DECESA), Federal University of Health Sciences of Porto Alegre, Av. Independência, 2293, Santa Cruz do Sul 96815-900, Rio Grande do Sul, BrasilAt the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements. These developments put increasing pressure on network backhaul and drive the need for a re-examination of traditional backhaul topologies. Challenges of impending networks cannot be tackled by star and ring approaches due to their lack of intrinsic survivability and resilience properties, respectively. In support of this re-examination, we propose a backhaul topology design method that formulates the topology optimization as a graph optimization problem by capturing both the objective and constraints of optimization in graph invariants. Our graph theoretic approach leverages well studied mathematical techniques to provide a more systematic alternative to traditional approaches to backhaul design. Specifically, herein, we optimize over some known graph invariants, such as maximum node degree, topology diameter, average distance, and edge betweenness, as well as over a new invariant called node Wiener impact, to achieve baseline backhaul topologies that match the needs for resilient future wireless and optical networks.http://www.mdpi.com/2076-3417/9/1/136cloud-radio access networkssurvivabilityresiliencegraph theorygraph invariantstopology optimizationnode wiener impact |
| spellingShingle | Valerio Frascolla Cristina K. Dominicini Marcia H. M. Paiva Gilles Caporossi Marcelo Antonio Marotta Moises R. N. Ribeiro Marcelo E. V. Segatto Magnos Martinello Maxwell E. Monteiro Cristiano Bonato Both Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants Applied Sciences cloud-radio access networks survivability resilience graph theory graph invariants topology optimization node wiener impact |
| title | Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants |
| title_full | Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants |
| title_fullStr | Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants |
| title_full_unstemmed | Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants |
| title_short | Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants |
| title_sort | optimizing c ran backhaul topologies a resilience oriented approach using graph invariants |
| topic | cloud-radio access networks survivability resilience graph theory graph invariants topology optimization node wiener impact |
| url | http://www.mdpi.com/2076-3417/9/1/136 |
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