Heterogeneous distributed computing systems are the emerging for executing scientific and
computationally intensive applications. Cloud computing in this context describes a …

Workflow scheduling in scientific computing systems is one of the most challenging
problems that focuses on satisfying user-defined quality of service requirements while …

Function-as-a-Service (FaaS) and serverless applications have proliferated significantly in
recent years because of their high scalability, ease of resource management, and pay-as …

In Infrastructure as a Service (IaaS) Clouds, users are charged to utilize cloud services
according to a pay-per-use model. If users intend to run their workflow applications on cloud …

To program in distributed computing environments such as grids and clouds, workflow is
adopted as an attractive paradigm for its powerful ability in expressing a wide range of …

This work introduces Mashup, a novel strategy to leverage serverless computing model for
executing scientific workflows in a hybrid fashion by taking advantage of both the traditional …

Most of existing Multi-access edge computing (MEC) studies consider the remote cloud
server as a special edge server, the opportunity of edge-cloud collaboration has not been …

Cloud computing is a suitable platform to execute the deadline-constrained scientific
workflows which are typical big data applications and often require many hours to finish …

Cloud computing is emerging with growing popularity in workflow scheduling, especially for
scientific workflow. Deploying data-intensive workflows in the cloud brings new factors to be …

Security is increasingly critical for various scientific workflows that are big data applications
and typically take quite amount of time being executed on large-scale distributed …