Big Data analytics for storing, processing, and analyzing large-scale datasets has become
an essential tool for the industry. The advent of distributed computing frameworks such as …

Big Data has become a very popular term. It refers to the enormous amount of structured,
semi-structured and unstructured data that are exponentially generated by high …

Spark has been increasingly adopted by industries in recent years for big data analysis by
providing a fault tolerant, scalable and easy-to-use in memory abstraction. Moreover, the …

Modern On-Line Data Intensive (OLDI) applications have evolved from monolithic systems to
instead comprise numerous, distributed microservices interacting via Remote Procedure …

Cloud services have recently undergone a shift from monolithic applications to
microservices, with hundreds or thousands of loosely-coupled microservices comprising the …

With the emergence of data science, graph computing is becoming a crucial tool for
processing big connected data. Although efficient implementations of specific graph …

The performance of compute hardware varies: software run repeatedly on the same server
(or a different server with supposedly identical parts) can produce performance results that …

Main memory (DRAM) consumes as much as half of the total system power in a computer
today, due to the increasing demand for memory capacity and bandwidth. There is a …

A modern datacenter server aims to achieve high energy efficiency by co-running multiple
applications. Some of such applications (eg, web search) are latency sensitive. Therefore …

Interference among distributed cloud applications can be classified into three types: full,
partial and zero. While prior research merely focused on full interference, the partial …