Improving Big Data Infrastructure to Effectively Utilize Resources for Data Processing and Services

大数据分析被誉为下一波创新浪潮的新兴驱动力。它已经形成了从业务工作流到工程活动和科学计算等广泛领域的许多新颖应用的基础。其中一个典型的应用是面向企业和个人移动用户或车辆用户的基于云的网络服务，通过日常日志文件从固定或移动实体（如配备各种内置传感器的智能手机）收集数据，然后由大数据基础设施进行处理，以便将数据作为服务提供。例如，可以从视频数据实时生成车辆轨迹，方便交通流参数分析，便于交通管理。显然，在此类应用程序中，用于数据处理的底层基础设施的响应时间对服务质量（QoS）有很大影响。

Big data analytics is hailed as an emerging driving force of the next innovation wave. It has formed the basis for many novel applications across a wide range of fields from business workflows to engineering activities and scientific computing. One such typical application is cloud-based network services for business and individual mobile or vehicular users, where data is collected through daily log files, from stationary or mobile entities such as smartphones equipped with a variety of built-in sensors (e.g., GPS, accelerometers and cameras) and then processed by a big-data infrastructure in order to provision data as a service. For example, vehicle trajectories can be generated in real time from video data to facilitate the analysis of traffic flow parameters for transportation management. Clearly, in such applications, the response time of the underlying infrastructure for data processing has great impact on Quality of Service (QoS).