Computational Grids (Shupeng Wang & Yu, 2006) are emerging as next generation of parallel and distributed computing platforms for solving large-scale computational and data-intensive problems in science, engineering, and commerce. They enable the sharing, selection, and aggregation of a wide variety of geographically distributed resources including supercomputers, storage systems, databases, da...

The amount of data movement in an application has a direct impact on both its execution time and power consumption. One way to reduce this, is the implementation of locality-aware scheduling algorithms to maximize the reuse of data during the assignment of work to hardware threads. Locality-Driven Code Scheduling (LDCS), an example of such algorithms, groups the tasks that process a common data...

The scheduling of application tasks is a problem that occurs in all multiprocessor systems This problem becomes even more compli cated if the tasks are not independent but are interrelated by mutual exclusion and precedence constraints This paper presents an approach for pre runtime scheduling of periodic tasks on multiple processors for a real time system that must meet hard deadlines The task...

The recent introduction of task dependencies in the OpenMP specification provides new ways of synchronizing tasks. Application programmers can now describe the data a task will read as input and write as output, letting the runtime system resolve fine-grain dependencies between tasks to decide which task should execute next. Such an approach should scale better than the excessive global synchro...

This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...

The rapid development of IoT-based services has resulted in an exponential increase the number connected smart mobile devices (SMDs). Processing massive data generated by large SMDs is becoming a big problem for devices, servers, and wireless communication channels. A Multi-access Edge Computing (MEC) paradigm partially mitigates this deploying edge server nodes at networks nearby SMDs, but cha...