Emerging fast, persistent memories will enable systems that combine conventional DRAM
with large amounts of non-volatile main memory (NVMM) and provide huge increases in …

Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of
fail-slow hardware incidents, collected from large-scale cluster deployments in 14 …

We conduct a comprehensive study of development and deployment issues of six popular
and important cloud systems (Hadoop MapReduce, HDFS, HBase, Cassandra, ZooKeeper …

The last five years have seen a rise of implementationlevel distributed system model
checkers (dmck) for verifying the reliability of real distributed systems. Existing dmcks …

Due to its high performance and decreasing cost per bit, flash storage is the main storage
medium in datacenters for hot data. However, flash endurance is a perpetual problem, and …

We introduce protocol-aware recovery (Par), a new approach that exploits protocol-specific
knowledge to correctly recover from storage faults in distributed systems. We demonstrate …

Over the last decade, Hadoop has evolved into a widely used platform for Big Data
applications. Acknowledging its wide-spread use, we present a comprehensive analysis of …

Data corruption is the most common consequence of file-system bugs. When such
corruption occurs, offline check and recovery tools must be used, but they are error prone …

Solid state drives (SSDs) have been widely used in Hadoop clusters ever since their
introduction to the big data industry. However, the current Hadoop framework is not …

Nearest neighbor classification assumes locally constant class conditional probabilities. This
assumption becomes invalid in high dimensions with finite samples due to the curse of …