Joint optimal scheduling and routing for maximum network throughput

In this paper we consider packet networks loaded by admissible traffic patterns, i.e. by traffic patterns that, if optimally routed, do not overload network resources. In these conditions, we study the combined behavior of distributed dynamic routing and scheduling algorithms based upon link state information, with no knowledge of the average traffic pattern, and we prove that simple schemes can achieve the same network throughput as optimal centralized routing and scheduling algorithms with complete information on the traffic pattern. Our study is based on a flow-level abstract model of the network, and considers elastic traffic, i.e., we assume that flows can adapt their transmission rates to network conditions. As a result, our model captures some of the main features of Internet traffic and of quality-of-service routing approaches being currently proposed for IP networks. We show that efficient dynamic routing and scheduling algorithms can be implemented in a distributed way, and we prove that maximum throughput is achieved also in case of temporary mismatches between the actual link metrics and those used by the routing algorithm. This is a particularly relevant aspect, since any distributed implementation of a routing algorithm requires a periodic exchange of link state information among nodes, and this implies delays, and thus time periods in which the actual link state is not known.

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