Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

Large-scale software systems are currently designed as distributed entities and deployed in
cloud data centers. To overcome the limitations inherent to this type of deployment …

The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …

Apache Spark is an open source distributed data processing platform that uses distributed
memory abstraction to process large volume of data efficiently. However, performance of a …

Performance is arguably the most crucial attribute that reflects the quality of a configurable
software system. However, given the increasing scale and complexity of modern software …

The centralized architecture of Software-Defined Networking (SDN) reduces networking
complexity and improves network manageability by omitting the need for box-by-box …

Predicting the performance of highly configurable software systems is the foundation for
performance testing and quality assurance. To that end, recent work has been relying on …

High performance computing (HPC) applications, such as metagenomics and other big data
systems, need to store and analyze huge volumes of semi-structured data. Such …

This article focuses on the problem of optimizing the system utility of Machine Learning (ML)-
based systems in the presence of ML mispredictions. This is achieved via the use of self …

Given the ever-increasing complexity of adaptable software systems and their commonly
hidden internal information (eg, software runs in the public cloud), machine learning based …