GMonE: A complete approach to cloud monitoring

The inherent complexity of modern cloud infrastructures has created the need for innovative monitoring approaches, as state-of-the-art solutions used for other large-scale environments do not address specific cloud features. Although cloud monitoring is nowadays an active research field, a comprehensive study covering all its aspects has not been presented yet. This paper provides a deep insight into cloud monitoring. It proposes a unified cloud monitoring taxonomy, based on which it defines a layered cloud monitoring architecture. To illustrate it, we have implemented GMonE, a general-purpose cloud monitoring tool which covers all aspects of cloud monitoring by specifically addressing the needs of modern cloud infrastructures. Furthermore, we have evaluated the performance, scalability and overhead of GMonE with Yahoo Cloud Serving Benchmark (YCSB), by using the OpenNebula cloud middleware on the Grid’5000 experimental testbed. The results of this evaluation demonstrate the benefits of our approach, surpassing the monitoring performance and capabilities of cloud monitoring alternatives such as those present in state-of-the-art systems such as Amazon EC2 and OpenNebula.     

Efficient lower bounds and heuristics for the variable cost and size bin packing problem

We consider the variable cost and size bin packing problem, a generalization of the well-known bin packing problem, where a set of items must be packed into a set of heterogeneous bins characterized by possibly different volumes and fixed selection costs. The objective of the problem is to select bins to pack all items at minimum total bin-selection cost. The paper introduces lower bounds and heuristics for the problem, the latter integrating lower and upper bound techniques. Extensive numerical tests conducted on instances with up to 1000 items show the effectiveness of these methods in terms of computational effort and solution quality. We also provide a systematic numerical analysis of the impact on solution quality of the bin selection costs and the correlations between these and the bin volumes. The results show that these correlations matter and that solution methods that are un-biased toward particular correlation values perform better.     

Parallel hierarchical radiosity on hybrid platforms

Achieving an efficient realistic illumination is an important aim of research in computer graphics. In this paper a new parallel global illumination method for hybrid systems based on the hierarchical radiosity method is presented. Our solution allows the exploitation of systems that combine independent nodes with multiple cores per node. Thus, multiple nodes work in parallel in the computation of the global illumination for the same scene. Within each node, all the available computational cores are used through a shared-memory multithreading approach. The good results obtained in terms of speedup on several distributed-memory and shared-memory configurations show the versatility of our hybrid proposal.     

Precision flight control for a multi-vehicle quadrotor helicopter testbed

Quadrotor helicopters continue to grow in popularity for unmanned aerial vehicle applications. However, accurate dynamic models for deriving controllers for moderate to high speeds have been lacking. This work presents theoretical models of quadrotor aerodynamics with non-zero free-stream velocities based on helicopter momentum and blade element theory, validated with static tests and flight data. Controllers are derived using these models and implemented on the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC), demonstrating significant improvements over existing methods. The design of the STARMAC platform is described, and flight results are presented demonstrating improved accuracy over commercially available quadrotors.     

Low-complexity heterogeneous architecture for H.264/HEVC video transcoding

High efficiency video coding (HEVC) was developed by the Joint Collaborative Team on video coding to replace the current H.264/AVC standard, which has been widely adopted over the last few years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient conversion to HEVC is needed. This paper presents a hybrid transcoding algorithm which makes use of soft computing techniques as well as parallel processing. On the one hand, a fast quadtree level decision algorithm tries to exploit the information gathered at the H.264/AVC decoder to make faster decisions on coding unit splitting in HEVC using a Naïve–Bayes probabilistic classifier that is determined by a supervised data mining process. On the other hand, a parallel HEVC-encoding algorithm makes use of a heterogeneous platform composed of a multi-core central processing unit plus a graphics processing unit (GPU). In this way, from a coarse point of view, groups of frames or rows of a frame (both options are possible) are divided into threads to be executed on each core (each of which executes one of the aforementioned classifiers) and, from a finer point of view, all these threads work in a collaborative way on a single GPU to perform the motion estimation process on the co-processor. Experimental results show that the proposed transcoder can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder.     

A miniaturized flow reaction chamber for use in combination with QCM-D sensing

A miniaturized flow chamber for quartz crystal microbalance with dissipation monitoring (QCM-D) has been developed. The main purpose was to reduce the total liquid sample consumption during an experiment, but also to gain advantages with respect to kinetics and mass transport by reducing the boundary diffusion layer. The bottom of the flow chamber is a QCM-D sensor surface, on which a polydimethylsiloxane spacer ring, fabricated onto a poly(methyl methacrylate) lid, is placed symmetrically around the QCM-D electrode (diameter ~10 mm). The spacer ring defines the inner chamber height (typically 40–50 μm) and provides sealing. Through the lid, there are inlet and outlet channels. The typical chamber volume is in the range of 2.5–3.5 μl (with a 10 μl dead volume). In flow mode, we have operated the cell at flow rates of 6–50 μl/min, i.e., volume turnovers of 2–17 per min. As a model system, to test the microcell, the formation of supported phospholipid bilayers on a SiO₂ surface was studied. For comparison, the same process was studied in a commercially available QCM-D equipment with significantly larger total volume (by a factor of 20). The decrease in effective sample consumption to produce a bilayer on the sensor surface in the chamber was approximately proportional to the decrease in chamber volume. Smaller volume also reduced the liquid exchange time. Potential improvements of the chamber include further optimization of the flow profile and, in addition, further miniaturization by decreasing the chamber height and the sensor radius.     

Effect of ultrasonic shot peening on microstructure and properties of 301SS

Ultrasonic shot peening (USP) is an efficient way to improve the mechanical behavior of 301 stainless steel by inducing severe plastic deformation on its surface. However, this surface treatment induces complex microstructural evolutions, such as grain refinement and phase transformation. Therefore, a better understanding of those evolution mechanisms is critical to optimize the USP treatment. In this work, we rely on various electron microscope observations to compare a specimen before and after a 5-min shot peening treatment. We found an affected layer of ~450?µm with a significant increase in hardness on the top surface by a factor of 2.7 times. Inside this layer, we noticed a nanoscale grain layer of ~130?µm, the most strengthened layer, containing nanoscale grain of α′, with few γ and a large amount of low angle grain boundaries on the topmost. Afterward, we observed coarse grains with deformation twins, which seem to be a preferential site for martensite nucleation, especially at their intersection, and a high density of dislocation. We also conducted experiments to determine a possible scenario for the microstructural evolution, based on those observations.     

On the benefits of a stress criterion for the simulation of cup drawing process

Experimental and numerical cup drawing process has been investigated on 0.65 mm zinc sheets. The cup exhibits anisotropic earrings due to the material microstructure. The material formability is studied through elliptical bulge tests in the rolling, diagonal and transverse direction. High anisotropy of the formability is observed. The numerical simulation of cup drawing is then made and demonstrates the correct fitting with experimental results. A stress formability criterion developed by Jansen et al. [14] is then implemented into a finite element method software and applied to predict the material rupture observed for some process conditions. The risk zone of the cup is subjected to some strain path changes according to the simulation whereas the strain value does not explain the rupture according to the experimental formability measured by the bulge tests. It has been shown that the rupture is due to some critical stresses, which are reached in the risk zone of the cup. The use of the stress criterion and its non-dependence on the strain path change allows the fracture prediction. Finally, the numerical fracture propagation by the “kill element method”, as briefly discussed by Bouchard et al. [4], is used and shows a good similarity with the experience.