This survey article reviews the challenges associated with deploying and optimizing big data
applications and machine learning algorithms in cloud data centers and networks. The …

The rapid growth of stream applications in financial markets, health care, education, social
media, and sensor networks represents a remarkable milestone for data processing and …

Modern large-scale online service providers typically deploy microservices into containers to
achieve flexible service management. One critical problem in such container-based …

Although the industry has embraced the cloud computing model, there are still significant
challenges to be addressed concerning the quality of cloud services. Network-intensive …

Distributed computing systems (eg, clouds) have been widely employed to support an
expanding range of applications. As the scale of data generation grows in regards to …

The availability of computing resources has significantly changed due to the growing
adoption of the cloud computing paradigm. Aiming at potential advantages such as cost …

This paper contributes to a performance analysis of real-world workloads under private
cloud conditions. We selected six benchmarks from PARSEC related to three mainstream …

This article investigates how to satisfy network performance requirements that are crucial in
achieving the service level objectives (SLOs) in clouds. Traditional techniques for network …

Stream Processing Engines (SPEs) have to support high data ingestion to ensure the quality
and efficiency for the end-user or a system administrator. The data flow processed by SPE …

The availability of computational resources changed significantly due to cloud computing. In
addition, we have witnessed efforts to execute High-Performance Computing (HPC) …