The elasticity promised by cloud computing does not come for free. Providers need to reserve resources to allow users to scale on demand, and cope with workload variations, which results in low utilization. The current response to this low utilization is to re-sell unused resources with no Service Level Objectives (SLOs) for availability. In this paper, we show how to make some of these reclaimable resources more valuable by providing strong, long-term availability SLOs for them. These SLOs are based on forecasts of how many resources will remain unused during multi-month periods, so users can do capacity planning for their long-running services. By using confidence levels for the predictions, we give service providers control over the risk of violating the availability SLOs, and allow them trade increased risk for more resources to make available. We evaluated our approach using 45 months of workload data from 6 production clusters at Google, and show that 6-17% of the resources can be reoffered with a long-term availability of 98.9% or better. A conservative analysis shows that doing so may increase the profitability of selling reclaimed resources by 22-60%.

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The genus Capsicum comprises a wide variety of peppers and peppers, with different sizes, colors and flavors. The present work had the objective to characterize and evaluate the genetic divergence among eight accessions of pepper (Capsicum annuum). The experiment was developed at the Federal University of Paraíba, Areia - PB. Eight accessions of pepper belonging to the germplasm bank of the CCA-UFPB were used. The experimental design was completely randomized. Data were submitted to analysis of variance by the F test at a level of 5% and 1% significance and the means were grouped by the Scott Knott test at 5% and 1% significance. For the analysis of genetic divergence, the Tocher grouping method and canonical variables were used. The treatment effects were significant, by the F test, at a level of 1% for all the characteristics evaluated, except for crown width and stem diameter, which were significant at 5% probability. According to the results obtained in the Scott & Knott test at 5% and 1% probability, the accessions were differentiated into two to six different classes. According to Tocher’s methodology the accessions were grouped into two groups. In the analysis of the canonical variables, the first three variables explained 94.18% of the total variance, and four different groups were formed according to the graphical dispersion.

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Priority-based scheduling policies are commonly used to guarantee that requests submitted to the different service classes offered by cloud providers achieve the desired Quality of Service (QoS). However, the QoS delivered during resource contention periods may be unfair on certain requests. In particular, lower priority requests may have their resources preempted to accommodate resources associated with higher priority ones, even if the actual QoS delivered to the latter is above the desired level, while the former is underserved. Also, competing requests with the same priority may experience quite different QoS, since some of them may have their resources preempted, while others do not. In this paper we present a new scheduling policy that is driven by the QoS promised to individual requests. Benefits of using the QoS-driven policy are twofold: it maintains the QoS of each request as high as possible, considering their QoS targets and available resources; and it minimizes the variance of the QoS delivered to requests of the same class, promoting fairness. We used simulation experiments fed with traces from a production system to compare the QoS-driven policy with a state-of-the-practice priority-based one. In general, the QoS-driven policy delivers a better service than the priority-based one. Moreover, the equity of the QoS delivered to requests of the same class is much higher when the QoS-driven policy is used, particularly when not all requests get the promised QoS, which is the most important scenario. Finally, based on the current practice of large public cloud providers, our results show that penalties incurred by the priority-based scheduler in the scenarios studied can be, on average, as much as 193% higher than those incurred by the QoS-driven one.

A computational grid is a large scale federated infrastructure where users execute several types of applications with different submission rates. On the evaluation of solutions for grids, there are not much effort on using realistic workloads for experiments, and most of the time users' activities and applications are not well represented. In this work, we propose a user-based grid workload model which is based on clustering users according to their behaviour in the system and their applications. The results show that according to a new metric proposed, the model quality increases when using clustering and extracting models for the group of users with similar behaviour. Moreover, we compare our user-based modelling with a state-of-the-art system-based modelling approach. We show that by using our user-based model the system load can be easily changed by varying the number of users in the grid, creating different evaluation scenarios without affecting individual users' behaviour. On the other hand, varying the number of users in the system-based model does not affect the system load and change the way individual user's behave on the system, which can result in unrealistic users' activities.

Pepper has considerable genetic diversity and versatility. Knowledge of the genetic control of traits in peppers is of great importance for breeding programs given the large variety of types, sizes, colors and flavors. To this end, we examined the inheritance of seedling and plant traits in ornamental pepper (Capsicum annuum). The experiment was conducted in a greenhouse in Areia, Paraíba, Brazil. Seven ornamental pepper accessions (C. annuum) belonging to the Federal University of Paraiba's Germplasm Bank were investigated: UFPB001, UFPB004, UFPB77.3, UFPB099, UFPB134, UFPB137 and UFPB390. Morphoagronomic characterization was performed based on Capsicum descriptors, and 12 quantitative traits were evaluated in seedlings and plants. The data were subjected to variance analysis and subsequent diallel analysis performed according to Hayman's method. The t statistic was used to test the adequacy of the additive-dominance model. The traits seedling height, hypocotyl diameter, cotyledon leaf length, plant height, bifurcation height, leaf length and width and chlorophyll a and b are in agreement with the additive-dominant model. Correlations were positive and significant for seedling height (0.470) and hypocotyl diameter (0.885). Cotyledonary leaf length and width showed negative and significant values of-0.088 and-0.669, respectively. The correlations were positive for the following traits: plant height, stem diameter, first bifurcation height, canopy diameter, leaf length and chlorophyll b, with values ranging from 0.094 to 0.965. Leaf width and ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (1): gmr18120 A.M.S. Pessoa et al. 2 chlorophyll a exhibited negative r correlation values. In the genetic parameters estimate, the positive r correlation for most of the traits indicates that the recessive alleles were generally responsible for the increase in these traits. Genetic gains for plant traits in ornamental peppers are possible using breeding programs. The parents UFPB001 and UFPB134 exhibited the highest concentration of favorable alleles for size traits and are indicated for selection for continued improvement programs.