Current Issue : October - December Volume : 2012 Issue Number : 4 Articles : 3 Articles
One of the major benefits of cloud computing is the ability for users to access resources on a pay-as-you go basis,\r\nthereby potentially reducing their costs and enabling them to scale applications rapidly. However, this approach\r\ndoes not necessarily benefit the provider. Providers have the responsibility of ensuring that they have the physical\r\ninfrastructure to meet their users� demand and that their performance meets agreed service level agreements.\r\nWithout an accurate view of future demand, planning for variable costs such as staff, replacement servers or\r\ncoolers, and electricity supplies, can all be very difficult, and optimising the distribution of virtual machines presents\r\na major challenge.\r\nHere, we explore an extension of an approach first proposed in a theoretical study by Wu, Zhang, & Huberman\r\nwhich we refer to as the WZH model. The WZH model utilises a third-party intermediary, the Coordinator, who uses\r\na variety of cloud assets to deliver resources to clients at a reduced price, while making a profit and assisting the\r\nprovider(s) in resource forecasting. The Coordinator acts as a broker.\r\nUsers purchase resources in advance from the broker using a form of financial derivative contract called an option.\r\nThe broker uses the uptake of these options contracts to decide if it should invest in buying resource access for an\r\nextended period; the resources can then subsequently be provided to clients who demand it.\r\nWe implement an extension of the WZH model in an agent-based simulation, using asset classes and price-levels\r\ndirectly modelled on currently available real-world data from markets relevant to cloud computing, for both\r\nservice-providers provisioning and customers� demand patterns. We show that the broker profits in all market\r\nconditions simulated, and can increase her profit by up to 36% by considering past performance when deciding to\r\ninvest in reserved instances. Furthermore, we show that the broker can increase profits by up to 33% by investing\r\nin 36-month instances over 12-month. By considering past performance and investing in longer term reserved\r\ninstances, the broker can increase her profit by up to 44% for the same market conditions....
Design and analysis of complex nanophotonic and nanoelectronic structures require significant computing resources. Cloud\r\ncomputing infrastructure allows distributed parallel applications to achieve greater scalability and fault tolerance. The problems\r\nof effective use of high-performance computing systems for modeling and simulation of subwavelength diffraction gratings are\r\nconsidered. Rigorous coupled-wave analysis (RCWA) is adapted to cloud computing environment. In order to accomplish this,\r\ndata flow of the RCWA is analyzed and CPU-intensive operations are converted to data-intensive operations. The generated data\r\nsets are structured in accordance with the requirements of MapReduce technology....
Cloud computing is a new paradigm that combines several computing concepts\r\nand technologies of the Internet creating a platform for more agile and cost-effective\r\nbusiness applications and IT infrastructure. The adoption of Cloud computing has been\r\nincreasing for some time and the maturity of the market is steadily growing. Security is the\r\nquestion most consistently raised as consumers look to move their data and applications to\r\nthe cloud. We justify the importance and motivation of security in the migration of legacy\r\nsystems and we carry out an analysis of different approaches related to security in\r\nmigration processes to cloud with the aim of finding the needs, concerns, requirements,\r\naspects, opportunities and benefits of security in the migration process of legacy systems....
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