摘要
随着Web网络和无线传感器网络的不断发展,大数据的出现对数据查询和处理产生了挑战。研究了MapReduce框架下移动对象的并行Skyline计算问题,采用基于角度划分的方法解决负载平衡问题,并提出了一种过滤策略进行剪枝提高计算效率,在此基础上分别实现了静态Skyline算法和基于事件跟踪的MR-Track算法。最后通过对比实验验证了算法的有效性。
With the development of Web and wireless sensor networks, the appearance of big data has brought a great challenge to data query and process. The parallel Skyline computing issue of a moving query object under the MapReduce framework was studied. To solve the problem of load balance, a method based on angle partition was adopted. Then a filtering method was introduced to improve the efficiency. On the basis of those methods, a static Skyline algorithm and an event tracking algorithm named MR-Track were implemented respectively. Finally, many experiments were made to verify the effective and efficient of MR-Track algorithm.
出处
《电信科学》
北大核心
2014年第5期94-104,共11页
Telecommunications Science
基金
国家自然科学基金资助项目(No.61202007)
宁波市自然科学基金资助项目(No.2013A610063)
