Contention-based congestion management in large-scale networks

Abstract

Global adaptive routing exploits non-minimal paths to improve performance on adversarial traffic patterns and load-balance network channels in large-scale networks. However, most prior work on global adaptive routing have assumed admissible traffic pattern where no endpoint node is oversubscribed. In the presence of a greedy flow or hotspot traffic, we show how exploiting path diversity with global adaptive routing can spread network congestion and degrade performance. When global adaptive routing is combined with congestion management, the two types of congestion - network congestion that occurs within the interconnection network channels and endpoint congestion that occurs from oversubscribed endpoint nodes - are not properly differentiated. As a result, previously proposed congestion management mechanisms that are effective in addressing endpoint congestion are not necessarily effective when global adaptive routing is also used in the network. Thus, we propose a novel, low-cost contention-based congestion management (CBCM) to identify endpoint congestion based on the contention within the intermediate routers and at the endpoint nodes. While contention also occurs for network congestion, the endpoint nodes or the destination determines whether the congestion is endpoint congestion or network congestion. If it is only network congestion, CBCM ignores the network congestion and adaptive routing is allowed to minimize network congestion. However, if endpoint congestion occurs, CBCM throttles the hotspot senders and minimally route the traffic through a separate VC. Our evaluation across different traffic patterns and network sizes demonstrates that our approach is more robust in identifying endpoint congestion in the network while complementing global adaptive routing to avoid network congestion.