On parallel and distributed heterogeneous computing systems, a heuristic-based task
scheduling algorithm typically consists of two phases: task prioritization and processor …

The growth of energy consumption has been explosive in current data centers, super
computers, and public cloud systems. This explosion has led to greater advocacy of green …

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 …

In this paper, we investigate the problem of scheduling precedence-constrained parallel
applications on heterogeneous computing systems (HCSs) like cloud computing …

Traditionally, the primary performance goal of computer systems has focused on reducing
the execution time of applications while increasing throughput. This performance goal has …

Workflow scheduling is one of the key issues in the management of workflow execution.
Scheduling is a process that maps and manages execution of inter-dependent tasks on …

In a cloud computing environment, it is not easy to schedule various Internet of Things (IoT)
application tasks due to the heterogeneity characterises of IoT. Efficient scheduling and load …

Grid technologies have progressed towards a service-oriented paradigm that enables a new
way of service provisioning based on utility computing models, which are capable of …

Load-balancing problems arise in many applications, but, most importantly, they play a
special role in the operation of parallel and distributed computing systems. Load-balancing …

Scheduling for directed acyclic graph (DAG) tasks with the objective of minimizing
makespan has become an important problem in a variety of applications on heterogeneous …