High quality of security is increasingly critical for applications running on heterogeneous distributed systems. However, existing scheduling algorithms for heterogeneous distributed systems disregard security requirements of applications. To address this issue, in this paper, we introduce security heterogeneity concept for our scheduling model in the context of distributed systems. Based on th...

The static scheduling algorithms are widely used to evaluate the performance of distributed computing system. In such systems, purpose of scheduling algorithm is to allocate tasks to available processor so as to efficiently utilize this processor and to reduce the makespan, total computational cost and various other such factors, with the motive of achieving optimal solution. Scheduling algorit...

Thanks to vast improvements in wide-area network performance and powerful yet low-cost computers, Grid computing has emerged as a promising attractive computing paradigm. Computational Grids aim to aggregate the power of heterogeneous, geographically distributed, multiple-domain-spanning computational resources to provide high performance or high-throughput computing. To achieve the promising p...

The scheduling of tasks in distributed real-time systems has attracted many researchers in the recent past. The distributed real-time system considered here consists of uniprocessor or multiprocessor nodes connected through a multihop network. Scheduling in such a system involves scheduling of dynamically arriving tasks within a node (local scheduling) and migration of tasks across the network ...

One of the main problems in the field of scheduling algorithms for distributed memory systems is finding heuristics that produce good schedules at a low cost. We propose two new approaches for the scheduling problem. Both algorithms are intended to be used at compile time, to schedule task graphs on a distributed systems. Compared to known scheduling algorithms, the proposed algorithms preserve...

| Runtime Incremental Parallel Scheduling (RIPS) is an alternative strategy to the commonly used dynamic scheduling. In this scheduling strategy, the system scheduling activity alternates with the underlying computation work. RIPS utilizes the advanced parallel scheduling technique to produce a low-overhead, high-quality load balancing, as well as adapting to irregular applications. This paper ...

This work presents dispatching strategies based on methods of job-flow and application-level scheduling in virtual organizations of distributed computational environments with non-dedicated resources. Job-flow management is implemented with the set of specific rules for resource usage. Applications are considered as parallel jobs. Strategies are based on economic scheduling models and diverse a...

Data driven programming models such as many-task computing (MTC) have been prevalent for running data-intensive scientific applications. MTC applies over-decomposition to enable distributed scheduling. To achieve extreme scalability, MTC proposes a fully distributed task scheduling architecture that employs as many schedulers as the compute nodes to make scheduling decisions. Achieving distribu...

Automated planning and scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences b y a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed coll...

Nowdays, energy consumption as a critical issue in distributed computing systems with high performance has become so green computing tries to energy consumption, carbon footprint and CO2 emissions in high performance computing systems (HPCs) such as clusters, Grid and Cloud that a large number of parallel. Reducing energy consumption for high end computing can bring various benefits such as red...