Task scheduling for multicore processors typically has aimed at higher throughput and lower power consumption, but the lifetime reliability may be harmed if negative bias temperature instability is not considered together. In this letter, a task scheduling which extends lifetime is proposed. Cores are given the chance to recover as long as performance is not degraded. The degradation simulator ...

Many scientific applications running in Cloud Computing system are workflow applications that contains large number of tasks and in which tasks are connected by precedence relations. Efficient scheduling the workflow tasks become a challenging issue in Cloud Computing environments because the scheduling decides performance of the applications. Unfortunately, finding the optimal scheduling is kn...

The architectural features of modern computers highlight the need of parallel programming for sustained performance. This paper deals with task based programming to program modern computers. Due to lack of data locality, communication optimization and lack of task characterization support in an existing task scheduling, we intends to overview the characterization of locality aware task scheduli...

The Foundation for Intelligent Physical Agents (FIPA) provides a rich set of standards for implementing industrial scale multi-agent infrastructures. Despite its manifold possibilities for achieving coordinated action execution based on interaction protocols, it still lacks direct support of multi-agent planning and scheduling for goal directed action execution. In this paper, we discuss a desi...

We present the Dynamic Priority (DP) parallel task scheduler for Hadoop. It allows users to control their allocated capacity by adjusting their spending over time. This simple mechanism allows the scheduler to make more efficient decisions about which jobs and users to prioritize and gives users the tool to optimize and customize their allocations to fit the importance and requirements of their...

SHOP (Simple Hierarchical Ordered Planner) is a domain-independent H T N planning system with the following characteristics. • SHOP plans for tasks in the same order that they will later be executed. This avoids some goalinteraction issues that arise in other HTN planners, so that the planning algorithm is relatively simple. • Since SHOP knows the complete world-state at each step of the planni...

This paper is focused on how a general-purpose hierarchical planning representation, based on the HTN paradigm, can be used to support the representation of oncology treatment protocols. The planning algorithm used is a temporally extended HTN planning process capable of interpreting such representation and generating oncology treatment plans that have been proven to support clinical decisions ...

This paper explores the task scheduling algorithm for cloud computing on the basis of Particle Swarm Optimization (PSO). Based on task scheduling problems of the cloud computing, first of all, this paper detailed introduction to cloud computing, task scheduling of cloud computing, particle swarm optimization algorithm and ant colony optimization algorithm. On this basis of the above, task sched...

In list scheduling algorithm, at each scheduling step one task is scheduled to the processor on which the task achieves the earliest start time. As a result, each task is tentatively scheduled to each processor to find the destination processor. This paper presents a technique to be applied to the list scheduling algorithms which significantly reduces scheduling cost without sacrificing perform...

Many real-world planning applications have to deal with resource allocation problems, and so does planning in the domain of crisis management assistance. In order to support resource allocation in these kind of applications, we present a new approach to the integration of scheduling capabilities and planning. The proposed methodology relies on a hybrid planner, which combines action and state a...