Resource provisioning for cloud applications: a 3-D,provident and flexible approach

The scalability feature of cloud computing attracts application service providers (ASPs) to use cloud application hosting. In cloud environments, resources can be dynamically provisioned on demand for ASPs. Autonomic resource provisioning for the purpose of preventing resources over-provisioning or under-provisioning is a widely investigated topic in cloud environments. There has been proposed a lot of resource-aware and/or service-level agreement (SLA)-aware solutions to handle this problem. However, intelligence solutions such as exploring the hidden knowledge on the Web users’ behavior are more effective in cost efficiency. Most importantly, with considering cloud service diversity, solutions should be flexible and customizable to fulfill ASPs’ requirements. Therefore, lack of a flexible resource provisioning mechanism is strongly felt. In this paper, we proposed an autonomic resource provisioning mechanism with resource-aware, SLA-aware, and user behavior-aware features, which is called three-dimensional mechanism. The proposed mechanism used radial basis function neural network in order to provide providence and flexibility features. The experimental results showed that the proposed mechanism reduces the cost while guarantees the quality of service.     

Novel resource allocation algorithms to performance and energy efficiency in cloud computing

The rapid growth in demand for computational power has led to a shift to the cloud computing model established by large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy. Cloud providers must ensure that their service delivery is flexible to meet various consumer requirements. However, to support green computing, cloud providers also need to minimize the cloud infrastructure energy consumption while conducting the service delivery. In this paper, for cloud environments, a novel QoS-aware VMs consolidation approach is proposed that adopts a method based on resource utilization history of virtual machines. Proposed algorithms have been implemented and evaluated using CloudSim simulator. Simulation results show improvement in QoS metrics and energy consumption as well as demonstrate that there is a trade-off between energy consumption and quality of service in the cloud environment.     

Integrating Owicki–Gries for C11-Style Memory Models into Isabelle/HOL

Journal of Automated Reasoning - Weak memory presents a new challenge for program verification and has resulted in the development of a variety of specialised logics. For C11-style memory models,...     

Effect of heat storage and fuel price on energy management and economics of micro CCHP cogeneration systems

In the present work, a typical combined cooling, heating and power (CCHP) system comprised of boiler, flat solar collectors, absorption chiller and heat storage tank was investigated. The described system was considered to supply the given electricity, cooling and heating demand of a residential building; with heating and cooling needs of 100 and 50 kW, respectively. To find the optimum hybrid configurations with high reliability, low costs, low fuel consumption and emissions, a computer program was provided by authors in FORTRAN language. Different fuel prices were considered in the present work. The results indicated that the optimal operation strategy changes with Boiler and NGG fuel prices while it also changes with increasing the number of solar collectors, heat storage capacity and consequently decreasing total annual emission.     

Rapid tooling analysis of Stereolithography injection mould tooling

Increasing competition in global markets is exerting intense pressure on companies to trim their product cycles continuously. As delivery times and costs of tools are on a downward trend, the modern tool manufacturer is under pressure to produce tools quickly, accurately and at a lower cost. Reducing the time to produce prototypes is a key to speed up the development of new products. Rapid tooling (RT) with particular regard to injection mould fabrication using rapid prototyping (RP) technology of Stereolithography (SL) may lead to savings in cost and time. In this paper, SL is used to directly build rapid injection mould tools for short run production. SL tools have been evaluated to analyse the maximum number of successful injections and quality of performance. SL epoxy tools were able to resist the injection pressure and temperature and 500 injections were achieved. The tool failure mechanisms during injection are investigated and tool failure either occurs due to excessive flexural stresses, or because of excessive shear stresses.     

Physicochemical,rheological, and molecular characterization of colloidal gelatin produced from Common carp by‐products using microwave and ultrasound‐assisted extraction

The effects of ultrasound‐assisted extraction (UAE) and microwave‐assisted extraction (MAE) methods on molecular and physicochemical characteristics of the resultant gelatin were examined. Before extraction procedure, we investigated the optimum pH for swelling of Common carp by‐products, which is an important pretreatment for gelatin production. The highest swelling yield was achieved at pH 13 among pH 1–14 with unit intervals. Results indicated that the UAE gelatin has a higher gel strength, viscosity, melting point, and gelling point. The power and time of sonication showed a reverse relation with these characteristics. In addition, as the time of microwave heating was raised, the gel strength, viscosity, melting point, and gelling point were decreased. The FT‐IR spectra showed similar peaks but the Amide B in UAE gelatin slightly vanished. The electrophoretic pattern also revealed the higher gel strength and viscosity of UAE gelatin due to the higher intensity of α and β chains compared to MAE gelatin. It can be concluded from all of the results of this study that the produced gelatin using these procedures can be a good source of gelatin in food and drug industries.     

Mathematical model for prediction of oil recovery of core-flood tests in process of viscoelastic polymer flooding

In this study a new mathematical model was developed that considers thermal effects, dispersion, effective concentration, elastic behavior of viscoelastic polymers, polymer retention, permeability reduction of aqueous phase, salt effects, inaccessible pore volume, and equivalent shear rate in porous media to predict oil recovery of core-flood experiments in process of viscoelastic polymer flooding as a tertiary stage of enhanced oil recovery. The model was found highly reliable when compared to material balance and experimental data. Displacement performance of core-flood tests could be predicted by presented model, therefore, experimental costs will be decreased significantly.