EAGER: Cost- and Energy-Aware Query Processing in Mobile Clouds

创新的移动的技术在许多领域提供了令人感兴趣的机会，如医疗保健、交通和商业。它们能够实现远程监控，并允许考虑患者和医生的移动性等参数。这使得有可能开发新的应用，例如用于远程医疗和辅助环境生活（特别是在农村地区）的移动的保健服务和移动的交通服务。然而，需要生成和查询的数据量非常大，而且多种多样，而且是从多个来源收集的。 大数据和移动性的结合带来了一个重大挑战：如何有效地处理来自无数移动的设备对大量数据的查询，特别是当数据存储在由几个云提供商提供的新型数据管理系统中时，这些云提供商可能具有不同的定价模型？ 为了解决这一挑战，该项目开发了新型的移动的云数据管理架构和新型的查询处理算法，这些架构和算法利用了移动的用户的存储和计算能力，并考虑了移动的用户的移动性、断开连接、能量限制和云服务提供商的定价模型，以提高查询响应时间，同时减少必须支付给云服务提供商的金额。该研究通过原型设计使用真实的和合成数据集进行评估。该项目是俄克拉荷马州大学（University of Oklahoma）和法国布莱斯帕斯卡大学（Blaise Pascal University）之间的国际合作项目。 对于研究，这两所大学都参与了架构和算法的设计，原型和评估。 在教育方面，IBM通过Skype为Blaise Pascal大学的大数据管理课程提供有关移动的和大数据管理的讲座，而Blaise Pascal大学则为IBM的高级数据库管理课程提供有关云数据管理的讲座。这两门课程的学生都参与测试构建的原型，作为课堂作业的一部分。 该项目不仅对研究而且对教育产生了重要影响，因为它为研究生和本科生提供了国家关键需求领域的培训：云和移动的数据库管理系统，大数据和高端计算。开发的架构，算法，原型，数据集和性能评估结果可在网站上向公众提供：http://cs.ou.edu/~database。

Innovative mobile technologies offer interesting opportunities in many domains, such as health care, transportation, and commerce. They enable distant monitoring and permit consideration of parameters such as patient's and physician's mobility. This makes it possible to develop novel applications, such as mobile health services for telemedicine and assisted ambient living (particularly in rural areas) and mobile traffic services. Nevertheless, the amount of data to be generated and queried is very large and diverse and is collected from multiple sources. The combination of big data and mobility leads to a major challenge: how to efficiently process queries from a myriad of mobile devices on a large amount of data, especially when the data are to be stored in a novel data management system supplied by several cloud providers with possibly different pricing models? To solve this challenge, this project develops novel mobile cloud data management architectures and novel query processing algorithms that leverage mobile users' storage and computation power and take mobile users' mobility, disconnection, energy limitation, and cloud service providers' pricing models into consideration in order to improve query response time, while reducing the amount of money that must be paid to the cloud service providers. The research is evaluated using both real and synthetic datasets by means of prototyping.The project is an international collaboration effort between the University of Oklahoma (OU) and Blaise Pascal University in France. For research, both universities participate in the design, prototype and evaluation of the architectures and algorithms. For education, via Skype, OU provides lectures on mobile and big data management for the Big Data Management course at Blaise Pascal University, while Blaise Pascal University provides lectures on cloud data management for the Advanced Database Management course at OU. The students in both courses participate in testing the constructed prototype as a part of their class assignments. The project makes important impacts not only on research but also on education as it provides training for graduate and undergraduate students in the areas of critical national needs: cloud and mobile database management systems, big data and high-end computing. The developed architectures, algorithms, prototype, datasets and performance evaluation results are made available to the public at the Website: http://cs.ou.edu/~database.