DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling

The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches.Comment: Submitted to Springer Computin

On the relation between SMMR 37-GHz polarization difference and the rainfall over Africa and Australia

A major difficulty in interpreting coarse resolution satellite data in terms of land surface characteristics is unavailability of spatially and temporally representative ground observations. Under certain conditions rainfall has been found to provide a proxy measure for surface characteristics, and thus a relation between satellite observations and rainfall might provide an indirect approach for relating satellite data to these characteristics. Relationship between rainfall over Africa and Australia and 7-year average (1979-1985) polarization difference (PD) at 37 GHz from scanning multichannel microwave radiometer (SMMR) on board the Nimbus-7 satellite is studied in this paper. Quantitative methods have been used to screen (accept or reject) PD data considering antenna pattern, geolocation uncertainty, water contamination, surface roughness, and adverse effect of drought on the relation between rainfall and surface characteristics. The rainfall data used in the present analysis are climatologic averages and also 1979-1985 averages, and no screening has been applied to this data. The PD data has been screened considering only the location of rainfall stations, without any regard to rainfall amounts. The present analysis confirms a non-linear relation between rainfall and PD published previously

Comparing continuous and intermittent exercise. An "isoeffort" and "isotime" approach

The present study proposes an alternative way of comparing performance and acute physiological responses to continuous exercise with those of intermittent exercise, ensuring similar between-protocol overall effort (isoeffort) and the same total duration of exercise (isotime). This approach was expected to overcome some drawbacks of traditional methods of comparison. Fourteen competitive cyclists (20±3 yrs) performed a preliminary incremental test and four experimental 30-min self-paced protocols, i.e. one continuous and three passive-recovery intermittent exercise protocols with different workto- rest ratios (2 = 40:20s, 1 = 30:30s and 0.5 = 20:40s). A "maximal session effort" prescription was adopted for this experimental design. As expected, a robust perceived exertion template was observed irrespective of exercise protocol. Similar between-protocol pacing strategies further support the use of the proposed approach in competitive cyclists. Total work, oxygen uptake and heart rate mean values were significantly higher (P<0.05) in the continuous compared to intermittent protocols, while lactate values were lower. Manipulating the work-to-rest ratio in intermittent exercise, total work, oxygen uptake and heart rate mean values decreased with the decrease in the work-to-rest ratio, while lactate values increased. Despite this complex physiological picture, all protocols showed similar ventilatory responses and a nearly perfect relationship between respiratory frequency and perceived exertion. In conclusion, our data indicate that overall effort and total duration of exercise are two critical parameters that should both be controlled when comparing continuous with intermittent exercise. On an isoeffort and isotime basis, the work-to-rest ratio manipulation affects physiological responses in a different way from what has been reported in literature with traditional methods of comparison. Finally, our data suggest that during intermittent exercise respiratory frequency reflects physiological strain better than oxygen uptake, heart rate and blood lactate

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea ice extents and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea ice extents is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea ice areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea ice extents is 0.0304% +/- 0.4880%, and the mean difference in sea ice areas is 0.1550% +/- 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available