Network unfairness in dragonfly topologies

Dragonfly networks arrange network routers in a two-level hierarchy, providing a competitive cost-performance solution for large systems. Non-minimal adaptive routing (adaptive misrouting) is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns...

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Detalles Bibliográficos
Autores: Fuentes, Pablo, Vallejo, Enrique, Camarero, Cristóbal, Beivide Palacio, Ramon, Valero Cortés, Mateo|||0000-0003-2917-2482
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/97185
Acceso en línea:https://hdl.handle.net/2117/97185
https://dx.doi.org/10.1007/s11227-016-1758-z
Access Level:acceso abierto
Palabra clave:Routing (Computer network management)
Telecommunication -- Traffic -- Management
Dragonfly
Fairness
Networking
Encaminadors (Xarxes d'ordinadors)
Telecomunicació -- Tràfic -- Gestió
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Descripción
Sumario:Dragonfly networks arrange network routers in a two-level hierarchy, providing a competitive cost-performance solution for large systems. Non-minimal adaptive routing (adaptive misrouting) is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Network fairness issues arise in the dragonfly for several combinations of traffic pattern, global misrouting and traffic prioritization policy. Such unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. This paper reviews the main causes behind network unfairness in dragonflies, including a new adversarial traffic pattern which can easily occur in actual systems and congests all the global output links of a single router. A solution for the observed unfairness is evaluated using age-based arbitration. Results show that age-based arbitration mitigates fairness issues, especially when using in-transit adaptive routing. However, when using source adaptive routing, the saturation of the new traffic pattern interferes with the mechanisms employed to detect remote congestion, and the problem grows with the network size. This makes source adaptive routing in dragonflies based on remote notifications prone to reduced performance, even when using age-based arbitration.