The authors would like to thank the two anonymous reviewers for their insightful and constructive comments that improved the quality of our work as well as the Ministry of Economic Affairs and Climate Policy of the Netherlands for its financial support enabling the research behind this publication.
SynopsisWe examined foods ingested by American brook lamprey larvae from Minnesota streams during spring and summer seasons. The diet was dominated numerically by diatoms, but organic detritus comprised the bulk (>85%) of ingested materials. The organic contents of ingested foods did not differ among streams or between seasons, averaging approximately 70%. Feeding rates based on gut fullness were highest, but most variable, during spring. Assimilation efficiency of the organic fraction of the diet averaged >65% across streams and seasons. Larval American brook lamprey depend on organic detritus to meet most of their nutritional needs and are very efficient at digesting and assimilating these detrital foods. Survival of American brook lamprey populations may be affected by human activities that alter the production and availability of detritus within streams.
Abstract-This paper presents a scheme in which a dedicated backup network is designed to provide protection from random link failures. Upon a link failure in the primary network, traffic is rerouted through a preplanned path in the backup network. We introduce a novel approach for dealing with random link failures, in which probabilistic survivability guarantees are provided to limit capacity over-provisioning. We show that the optimal backup routing strategy in this respect depends on the reliability of the primary network. Specifically, as primary links become less likely to fail, the optimal backup networks employ more resource sharing amongst backup paths. We apply results from the field of robust optimization to formulate an ILP for the design and capacity provisioning of these backup networks. We then propose a simulated annealing heuristic to solve this problem for largescale networks, and present simulation results that verify our analysis and approach.
The performance of wireless scheduling algorithms directly depends on the availability and accuracy of channel state information (CSI) at the scheduler. As CSI updates must propagate across the network, they are delayed as they arrive at the controller. In this paper, we analyze the effect that delayed CSI has on the throughput performance of scheduling in wireless networks. By accounting for the delays in CSI as they relate to the network topology, we revisit the comparison between centralized and distributed scheduling, which is analyzed as a trade-off between using delayed CSI and making imperfect scheduling decisions. In particular, we prove that there exist conditions under which distributed scheduling outperforms the optimal centralized scheduling policy. We characterize the point at which distributed scheduling outperforms centralized scheduling for tree networks, illustrating the impact of topology on throughput.
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