Thermal-aware job scheduling in data centers:an optimization approach

Data centers are becoming more and more vital for every day life: they are huge computational beasts that run google queries, keep facebook profiles, and store our data in the cloud. As a result, research has focused the last decade on making the computing halls that host data centers more energy efficient. This thesis focuses on thermal management and control techniques that balance the thermal load in the data center, using knowledge of the thermal flows and leakages among the server equipment. For maximal utility, the controllers are extended to allow operation at the operating boundary. The results are completed by simulating a combination of thermal-aware controllers designed in this thesis, and power-aware controllers designed elsewhere. It is shown that a smart combination of both techniques results in greater energy reductions than implementing a single-purpose controller. Finally this thesis provides a method for characterizing the thermal map of any data center. With this identification method, it is possible to apply the controllers designed in this thesis to any existing data center

Optimized Thermal-Aware Job Scheduling and Control of Data Centers

Analyzing data centers with thermal-aware optimization techniques is a viable approach to reduce energy consumption of data centers. By taking into account thermal consequences of job placements among the servers of a data center, it is possible to reduce the amount of cooling necessary to keep the servers below a given safe temperature threshold. We set up an optimization problem to analyze and characterize the optimal setpoints for the workload distribution and the supply temperature of the cooling equipment. Furthermore under mild assumptions we design and analyze controllers that drive the data center to the optimal state without knowledge of the current total workload to be handled by the data center. The response of our controller is validated by simulations and convergence to the optimal setpoints is achieved under varying workload conditions

Optimized Thermal-Aware Job Scheduling and Control of Data Centers

Analyzing data centers with thermal-aware optimization techniques is a viable approach to reduce energy consumption of data centers. By taking into account thermal consequences of job placements among the servers of a data center, it is possible to reduce the amount of cooling necessary to keep the servers below a given safe temperature threshold. We set up an optimization problem to analyze and characterize the optimal set points for the workload distribution and the supply temperature of the cooling equipment. Furthermore, under mild assumptions, we design and analyze controllers that regulate the system to the optimal state without knowledge of the current total workload to be handled by the data center. The response of our controller is validated by simulations and convergence to the optimal set points is achieved under varying workload conditions

cDNA cloning and functional expression of the α-d-galactose-binding lectin frutalin in escherichia coli

cDNA clones encoding frutalin, the α-d-galactose-binding lectin expressed in breadfruit seeds (Artocarpus incisa), were isolated and sequenced. The deduced amino acid sequences indicated that frutalin may be encoded by a family of genes. The NCBI database searches revealed that the frutalin sequence is highly homologous with jacalin and mornigaG sequences. Frutalin cDNA was re-amplified and cloned into the commercial expression vector pET-25b(+) for frutalin production in Escherichia coli. An experimental factorial design was employed to maximise the soluble expression of the recombinant lectin. The results indicated that temperature, time of induction, concentration of IPTG and the interaction between the concentration of IPTG and the time of induction had the most significant effects on the soluble expression level of recombinant frutalin. The optimal culture conditions were as follows: induction with 1 mM IPTG at 22°C for 20 h, yielding 16 mg/l of soluble recombinant frutalin. SDS-PAGE and Western blot analysis revealed that recombinant frutalin was successfully expressed by bacteria with the expected molecular weight (17 kDa). These analyses also showed that recombinant frutalin was mainly produced as insoluble protein. Recombinant frutalin produced by bacteria revealed agglutination properties and carbohydrate-binding specificity similar to the native breadfruit lectin.Fundação para a Ciência e a Tecnologia (FCT