Computationally intensive tasks of IoT applications can be offloaded to powerful devices in
the edge. Code offloading reduces energy consumption and increases performance …

Effective data management is a crucial problem in distributed systems such as data grid and
cloud. This can be achieved by replicating file in a wise manner, which reduces data access …

A virtual machine (VM), during its lifecycle, can be scheduled for execution at geographically
disparate cloud locations depending upon the cost of computation and the load at these …

Real-time Grid applications are emerging in many disciplines of science and engineering. In
order to run these applications while meeting the associated real-time constraints with them …

Due to recent advancements in mobile computing and communication technologies, mobile
ad hoc computational Grids are emerging as a new computing paradigm, enabling …

We seek to enable efficient large-scale parallel execution of applications in which a shared
filesystem abstraction is used to couple many tasks. Such parallel scripting (many-task …

Grid resource management systems and schedulers are important components for building
Grids. They are responsible for the selection and allocation of Grid resources to current and …

Migrating virtual machines (VM) at run time within acceptable time limits is significantly
challenging due to large size of the virtual disk files. In this paper, we propose our framework …

In large-scale data-intensive applications data plays a pivotal role in the execution of these
applications, and data transfer is the primary cause of job execution delay. In environments …

In a grid computing environment, a great many users may access the same database
simultaneously. To reduce the average waiting time for all users, a grid designer usually …