随着发达国家经济状况逐渐好转,由次贷危机(Subprim e Crisis)引起的百年一遇的金融危机正逐渐离我们远去。痛定思痛,回顾危机的起源和发展,作为金融支柱行业的商业银行能从中获取不少有益的经验和教训。严格约束资本金充足率,完善风险...随着发达国家经济状况逐渐好转,由次贷危机(Subprim e Crisis)引起的百年一遇的金融危机正逐渐离我们远去。痛定思痛,回顾危机的起源和发展,作为金融支柱行业的商业银行能从中获取不少有益的经验和教训。严格约束资本金充足率,完善风险管理机制,稳健实施金融创新、提高资本利用率,是商业银行在后金融危机时代的发展策略。展开更多
Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/rem...Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/remote sensing(GIS/RS) researchers rent more public clouds or establish more private clouds.However,a large proportion of these clouds are found to be underutilized,since users do not deal with big data every day.The low usage of cloud resources violates the original intention of cloud computing,which is to save resources by improving usage.In this work,a low-cost cloud computing solution was proposed for geo-information processing,especially for temporary processing tasks.The proposed solution adopted a hosted architecture and can be realized based on ordinary computers in a common GIS/RS laboratory.The usefulness and effectiveness of the proposed solution was demonstrated by using big data simplification as a case study.Compared to commercial public clouds and dedicated private clouds,the proposed solution is more low-cost and resource-saving,and is more suitable for GIS/RS applications.展开更多
文摘随着发达国家经济状况逐渐好转,由次贷危机(Subprim e Crisis)引起的百年一遇的金融危机正逐渐离我们远去。痛定思痛,回顾危机的起源和发展,作为金融支柱行业的商业银行能从中获取不少有益的经验和教训。严格约束资本金充足率,完善风险管理机制,稳健实施金融创新、提高资本利用率,是商业银行在后金融危机时代的发展策略。
基金Project(41401434)supported by the National Natural Science Foundation of China
文摘Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/remote sensing(GIS/RS) researchers rent more public clouds or establish more private clouds.However,a large proportion of these clouds are found to be underutilized,since users do not deal with big data every day.The low usage of cloud resources violates the original intention of cloud computing,which is to save resources by improving usage.In this work,a low-cost cloud computing solution was proposed for geo-information processing,especially for temporary processing tasks.The proposed solution adopted a hosted architecture and can be realized based on ordinary computers in a common GIS/RS laboratory.The usefulness and effectiveness of the proposed solution was demonstrated by using big data simplification as a case study.Compared to commercial public clouds and dedicated private clouds,the proposed solution is more low-cost and resource-saving,and is more suitable for GIS/RS applications.
