Alfonso Quarati

Hybrid Clouds brokering: Business opportunities, QoS and energy-saving issues

Abstract Hybrid Clouds couple the scalability offered by public Clouds with the greater control supplied by private ones. A (hybrid) Cloud broker acting as an intermediary between users and providers of public Cloud services, may support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. The paper presents a Cloud brokering algorithm delivering services with different level of non-functional requirements, to the private or public resources, on the basis of different scheduling criteria. With the objective of maximize user satisfaction and broker’s revenues, the algorithm pursues profit increases by reducing energy costs, through the adoption of energy saving mechanisms. A simulation model is used to evaluate performance in terms of broker’s revenue, user satisfaction and energy behavior of various allocation policies. Simulation results show that differences among policies depend on system loads and that the use of turn on and off techniques greatly improves energy savings at low and medium load rates.

Job-resource matchmaking on Grid through two-level benchmarking

Grid environments must provide effective mechanisms able to select the most adequate resources satisfying application requirements. A description of applications and resources, grounded on a common and shared basis, is crucial to favour an effective pairing. A suitable criterion to match demand with supply is to characterize resources by means of their performance evaluated through the execution of low-level and application-specific benchmarks. We present GREEN, a distributed Matchmaker, based on a two-level benchmarking methodology. GREEN facilitates the ranking of Grid resources and the submission of jobs to the Grid, through the specification of both syntactic and performance requirements, independently of the underlying middleware and thus fostering Grid interoperability.

Cloud infrastructures for in silico drug discovery: economic and practical aspects.

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

Job allocation strategies for energy-aware and efficient Grid infrastructures

Complex distributed architectures, like Grid, supply effective platforms to solve computations on huge datasets, often at the cost of increased power consumption. This energy issue affects the sustainability of the infrastructures and increases their environmental impact. On the other hand, due to Grid heterogeneity and scalability, possible power savings could be achieved if effective energy-aware allocation policies were adopted. These policies are meant to implement a better coupling between application requirements and the Grid resources, also taking energy parameters into account. In this paper, we discuss different allocation strategies which address jobs submitted to Grid resources, subject to efficiency and energy constraints. Our aim is to analyze the potential benefits that can be obtained from the adoption of a metric able to capture both performance and energy-savings. Based on an experimental study, we simulated two alternative scenarios aimed at comparing the behavior of different strategies for allocating jobs to resources. Moreover we introduced the Performance/Energy Trade-off function as a useful means to evaluate the tendency of an allocation strategy toward efficiency or power consumption. Our conclusion seems to suggest that performance and energy-savings are not always enemies, and these objectives may be combined if suitable energy metrics are adopted.

Scheduling strategies for enabling meteorological simulation on hybrid clouds

The flexible and pay-as-you-go computing capabilities offered by Cloud infrastructures are very attractive for high-demanding e-Science applications like weather prediction simulators. For their ability to couple the scalability offered by public service provider with the greater control and customization provided by Private Clouds, Hybrid Clouds seem a particularly appealing solution to support meteorological researchers and weather departments in their every-day activity. Cloud Brokers interfacing customers with Cloud providers, may support scientists in the deployment and execution of demanding meteorological simulations, by hiding all the intricacies related to the management of powerful but often complex HPC systems.The paper presents a set of brokering strategies for Hybrid Clouds aimed at the execution of various instances of the weather prediction WRF model subject to different user requirements and computational conditions. A simulation-based analysis documents the performance of the different scheduling strategies at varying workloads and system configuration.

A QoS-aware broker for hybrid clouds

Hybrid Clouds seems able to offer their customers with differentiate solutions capable of providing more and personalized guarantees with respect to the basic service availability generally supplied. In the context of an Italian research project aimed to transfer ICT advancements from research centers towards ICT SMEs, the paper focuses on the design of a brokering tool for hybrid clouds capable to adequately respond to specific Quality of Service (QoS) constraints. Aimed at satisfying the highest number of user requests while trying maximizing the profit of the private provider, in the context of a posted price economic model, the proposed brokering algorithm may apply different allocation policies, based on the reservation of a quota of private resources to high-level QoS applications.

Setting Up an Hydro-Meteo Experiment in Minutes: The DRIHM e-Infrastructure for HM Research

Predicting weather and climate and its impacts on the environment, including hazards such as floods and landslides, is a big challenge that can be efficiently supported by a distributed and heterogeneous infrastructure, exploiting several kinds of computational resources: HPC, Grids and Clouds. This can help researchers in speeding up experiments, improve resolution and accuracy, simulate with different numerical models and model chains. Such numerical models are complex with heavy computational requirements, huge numbers of parameters to tune, and not fully standardized interfaces. Hence, each research entity is usually focusing on a limited set of tools and hard-wired solutions to enable their interaction. The DRIHM approach is based on strong standardization, well defined interfaces, and an easy to use web interface for model configuration and experiment definition. A researcher can easily compare outputs from different hydrologic models forced by the same meteorological model, or compare different meteorological models to validate or improve her research. This paper presents the benefit of a web-based interface for hydro-meteorology research through a detailed analysis of the portal (based on liferay-gUse) developed by the DRIHM project.

CUDA accelerated blobby molecular surface generation

A proper and efficient representation of molecular surfaces is an important issue in biophysics from several view points. Molecular surfaces indeed are used for different aims, in particular for visualization, as support tools for biologists, computation, in electrostatics problems involving implicit solvents (e.g. while solving the Poisson-Boltzmann equation) or for molecular dynamics simulations. This problem has been recognized in the literature, resulting in a multitude of algorithms that differ on the basis of the adopted representation and the approach/ technology used. Among several molecular surface definitions, the Blobby surface is particularly appealing from the computational and the graphics point of view. In the paper we describe an efficient software component able to produce high-resolution Blobby surfaces for very large molecules using the CUDA architecture. Experimental results show a speedup of 35.4 considering a molecule of 90,898 atoms and a resulting mesh of 168 million triangles.

A Distributed Approach for Structured Resource Discovery on Grid

We present a distributed approach for grid resource discovery, which combines a structured view of resources (single machines, homogeneous and heterogeneous clusters) at the physical organization (PO) level with a super-peer network connecting the various POs. The proposed architecture is modular and independent of the particular grid middleware. After a general description, we present some implementation aspects which refer to the Globus Toolkit 4 as grid middleware and to the JXTA platform to set-up the super-peer network. The system is particularly suitable for discovering resources for structured parallel applications on very large grids.

Reconstructing positive Boolean functions with shadow clustering

The problem of reconstructing the AND-OR expression of a positive Boolean function starting from a portion of its truth table is solved by adopting a proper algorithm, called shadow clustering (SC). It generates a collection of prime implicants by descending the part of the diagram of the Boolean lattice (associated with the input domain) that lies beneath the available examples. Three different versions of SC are proposed, according to the approaches adopted to perform a single move downward.