Context: In recent years, the valuable knowledge that can be retrieved from petabyte scale
datasets–known as Big Data–led to the development of solutions to process information …

Over the last decade, several advancements have happened in distributed and parallel
computing. A lot of data is generated daily from various sources, and this speedy data …

MapReduce 并行编程模型通过定义良好的接口和运行时支持库, 能够自动并行执行大规模计算
任务, 隐藏底层实现细节, 降低并行编程的难度. 本文对MapReduce 的国内外相关研究现状进行 …

Data center-scale clusters are evolving towards heterogeneous hardware for power, cost,
differentiated price-performance, and other reasons. MapReduce is a well-known …

MapReduce is a powerful platform for large-scale data processing. To achieve good
performance, a MapReduce scheduler must avoid unnecessary data transmission by …

Erasure coding is a technique for achieving high availability and reliability in storage and
communication systems. We revisit the analysis of erasure code replication and point out …

Over the last decade, several interconnected disruptions have happened in the large scale
distributed and parallel computing landscape. The volume of data currently produced by …

Increased complexity and scale of virtualized distributed systems has resulted in the
manifestation of emergent phenomena substantially affecting overall system performance …

Distributed denial of service (DDoS) attacks continues to grow as a threat to organizations
worldwide. From the first known attack in 1999 to the highly publicized Operation Ababil, the …

With the development of information technologies, we have entered the era of Big Data.
Google's MapReduce programming model and its open-source implementation in Apache …