On the Energy Efficiency of Sleeping and Rate Adaptation for Network Devices

Best Paper AwardInternational audienceThe ever-growing appetite of Internet applications for network resources has led to an unprecedented electricity bill for these telecommunication infrastructures. Several techniques have been developed to improve the energy consumption of network devices. As their utilization highly varies over time, the two main techniques for saving energy, namely sleeping and rate adaptation, exploits the lower work-load periods to either put to sleep some hardware elements or adapt the network rate to the actual traffic level. In this paper, we compare two emblematic approaches of these energy-efficient techniques: Low Power Idle and Adaptive Link Rate. Our simulation-based study quantifies the reachable energy savings of these two approaches depending on the traffic characteristics. We show that, with little impact on the Quality of Service and consequent energy savings, Low Power Idle has a clear advantage. On the contrary, ALR is almost always consuming more than LPI and can reach unacceptable QoS levels. We also show that they can be combined to achieve better energy-efficiency, but at the cost of important QoS degradation

Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina)

International audienceTrichoderma reesei is the main industrial source of cellulases and hemicellulases used to depolymerize biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethanol. We assembled 89 scaffolds (sets of ordered and oriented contigs) to generate 34 Mbp of nearly contiguous T. reesei genome sequence comprising 9,129 predicted gene models. Unexpectedly, considering the industrial utility and effectiveness of the carbohydrate-active enzymes of T. reesei, its genome encodes fewer cellulases and hemicellulases than any other sequenced fungus able to hydrolyze plant cell wall polysaccharides. Many T. reesei genes encoding carbohydrate-active enzymes are distributed nonrandomly in clusters that lie between regions of synteny with other Sordariomycetes. Numerous genes encoding biosynthetic pathways for secondary metabolites may promote survival of T. reesei in its competitive soil habitat, but genome analysis provided little mechanistic insight into its extraordinary capacity for protein secretion. Our analysis, coupled with the genome sequence data, provides a roadmap for constructing enhanced T. reesei strains for industrial applications such as biofuel production