Power spectra of self-organized critical sandpiles

We analyze the power spectra of avalanches in two classes of self-organized critical sandpile models, the Bak-Tang-Wiesenfeld model and the Manna model. We show that these decay with a $1/f^\alpha$ power law, where the exponent value $\alpha$ is significantly smaller than 2 and equals the scaling exponent relating the avalanche size to its duration. We discuss the basic ingredients behind this result, such as the scaling of the average avalanche shape.Comment: 7 pages, 3 figures, submitted to JSTA

Facilitating self-adaptable inter-cloud management

Cloud Computing infrastructures have been developed as individual islands, and mostly proprietary solutions so far. However, as more and more infrastructure providers apply the technology, users face the inevitable question of using multiple infrastructures in parallel. Federated cloud management systems offer a simplified use of these infrastructures by hiding their proprietary solutions. As the infrastructure becomes more complex underneath these systems, the situations (like system failures, handling of load peaks and slopes) that users cannot easily handle, occur more and more frequently. Therefore, federations need to manage these situations autonomously without user interactions. This paper introduces a methodology to autonomously operate cloud federations by controlling their behavior with the help of knowledge management systems. Such systems do not only suggest reactive actions to comply with established Service Level Agreements (SLA) between provider and consumer, but they also find a balance between the fulfillment of established SLAs and resource consumption. The paper adopts rule-based techniques as its knowledge management solution and provides an extensible rule set for federated clouds built on top of multiple infrastructures. © 2012 IEEE

LAYSI: A layered approach for SLA-violation propagation in self-manageable cloud infrastructures

Cloud computing represents a promising comput ing paradigm where computing resources have to be allocated to software for their execution. Self-manageable Cloud in frastructures are required to achieve that level of flexibility on one hand, and to comply to users' requirements speci fied by means of Service Level Agreements (SLAs) on the other. Such infrastructures should automatically respond to changing component, workload, and environmental conditions minimizing user interactions with the system and preventing violations of agreed SLAs. However, identification of sources responsible for the possible SLA violation and the decision about the reactive actions necessary to prevent SLA violation is far from trivial. First, in this paper we present a novel approach for mapping low-level resource metrics to SLA parameters necessary for the identification of failure sources. Second, we devise a layered Cloud architecture for the bottom-up propagation of failures to the layer, which can react to sensed SLA violation threats. Moreover, we present a communication model for the propagation of SLA violation threats to the appropriate layer of the Cloud infrastructure, which includes negotiators, brokers, and automatic service deployer. © 2010 IEEE

Probability distribution of residence-times of grains in sandpile models

We show that the probability distribution of the residence-times of sand grains in sandpile models, in the scaling limit, can be expressed in terms of the survival probability of a single diffusing particle in a medium with absorbing boundaries and space-dependent jump rates. The scaling function for the probability distribution of residence times is non-universal, and depends on the probability distribution according to which grains are added at different sites. We determine this function exactly for the 1-dimensional sandpile when grains are added randomly only at the ends. For sandpiles with grains are added everywhere with equal probability, in any dimension and of arbitrary shape, we prove that, in the scaling limit, the probability that the residence time greater than t is exp(-t/M), where M is the average mass of the pile in the steady state. We also study finite-size corrections to this function.Comment: 8 pages, 5 figures, extra file delete

Vasodilator effect of glucagon: receptorial crosstalk among glucagon, GLP-1, and receptor for glucagon and GLP-1

Glucagon is known for its insulin-antagonist effect in the blood glucose homeostasis, while it also reduces vascular resistance. The mechanism of the vasoactive effect of glucagon has not been studied before; thereby we aimed to investigate the mediators involved in the vasodilatation induced by glucagon. The vasoactive effect of glucagon, insulin, and glucagon-like peptide-1 was studied on isolated rat thoracic aortic rings using a wire myograph. To investigate the mechanism of the vasodilatation caused by glucagon, we determined the role of the receptor for glucagon and the receptor for GLP-1, and studied also the effect of various inhibitors of gasotransmitters, inhibitors of reactive oxygen species formation, NADPH oxidase, prostaglandin synthesis, protein kinases, potassium channels, and an inhibitor of the Na(+)/Ca(2+)-exchanger. Glucagon causes dose-dependent relaxation in the rat thoracic aorta, which is as potent as that of insulin but greater than that of GLP-1 (7-36) amide. Vasodilatation by GLP-1 is partially mediated by the glucagon receptor. The vasodilatation due to glucagon evokes via the glucagon-receptor, but also via the receptor for GLP-1, and it is endothelium-independent. Contribution of gasotransmitters, prostaglandins, the NADPH oxidase enzyme, free radicals, potassium channels, and the Na(+)/Ca(2+)-exchanger is also significant. Glucagon causes dose-dependent relaxation of rat thoracic aorta in vitro, via the receptor for glucagon and the receptor for GLP-1, while the vasodilatation evoked by GLP-1 also evolves partially via the receptor for glucagon, thereby, a possible crosstalk between the 2 hormones and receptors could occur

Mounding Instability and Incoherent Surface Kinetics

Mounding instability in a conserved growth from vapor is analysed within the framework of adatom kinetics on the growing surface. The analysis shows that depending on the local structure on the surface, kinetics of adatoms may vary, leading to disjoint regions in the sense of a continuum description. This is manifested particularly under the conditions of instability. Mounds grow on these disjoint regions and their lateral growth is governed by the flux of adatoms hopping across the steps in the downward direction. Asymptotically ln(t) dependence is expected in 1+1- dimensions. Simulation results confirm the prediction. Growth in 2+1- dimensions is also discussed.Comment: 4 pages, 4 figure

Distributed Environment for Efficient Virtual Machine Image Management in Federated Cloud Architectures

The use of Virtual Machines (VM) in Cloud computing provides various benefits in the overall software engineering lifecycle. These include efficient elasticity mechanisms resulting in higher resource utilization and lower operational costs. VM as software artifacts are created using provider-specific templates, called VM images (VMI), and are stored in proprietary or public repositories for further use. However, some technology specific choices can limit the interoperability among various Cloud providers and bundle the VMIs with nonessential or redundant software packages, leading to increased storage size, prolonged VMI delivery, stagnant VMI instantiation and ultimately vendor lock-in. To address these challenges, we present a set of novel functionalities and design approaches for efficient operation of distributed VMI repositories, specifically tailored for enabling: (i) simplified creation of lightweight and size optimized VMIs tuned for specific application requirements; (ii) multi-objective VMI repository optimization; and (iii) efficient reasoning mechanism to help optimizing complex VMI operations. The evaluation results confirm that the presented approaches can enable VMI size reduction by up to 55%, while trimming the image creation time by 66%. Furthermore, the repository optimization algorithms, can reduce the VMI delivery time by up to 51% and cut down the storage expenses by 3%. Moreover, by implementing replication strategies, the optimization algorithms can increase the system reliability by 74%