Cloud computing is very popular because of its unique features such as scalability, elasticity,
on-demand service, and security. A large number of tasks are performed simultaneously in a …

Heterogeneous multi-processor architecture which achieves rich functionalities with different
types of processors, is widely used to provide powerful calculating capability while kee** …

Abstract The Internet of Things (IoT) is constantly evolving. The variety of IoT applications
has caused new demands to emerge on users' part and competition between computing …

Recently, the multi-cloud environment (MCE) has increasingly become the preferred choice
of users. As with the cloud environment, efficient workflow scheduling in a MCE remains …

Scheduling is an important issue in distributed computing platforms which decides the
allocation of resources to the user-submitted tasks to optimize certain scheduling objectives …

Fog computing paradigm attempts to provide diverse processing at the edge of IoT networks.
Energy usage being one of the important elements that may have a direct influence on the …

Multi-cloud is the use of multiple cloud computing in a single heterogeneous architecture.
Workflow scheduling in multi-cloud computing is an NP-Hard problem for which many …

The researcher's predilection towards the concerned infinite resources and the dynamic
provisioning on rental premises encourages the scheduling of complex scientific …

Abstract Teaching-Learning-Based Optimization (TLBO) algorithm was developed to solve
single-objective optimization problems. TLBO is inspired by the theory of teaching-learning …

Scientific workflows are appropriate for treating large volumes of data and leading large-
scale experiments. They are time-consuming and resource-intensive applications that profit …