An enhanced meta-scheduling system for grid computing that considers the job type and priority

Abstract

Meta-scheduling systems play a crucial role in scheduling jobs that are submitted for execution and require special attention because an increasing number of jobs are being executed using a limited number of resources. The primary problem of meta-scheduling is selecting the best resources (sites) to use to execute the underlying jobs while still achieving the following objectives: reducing the mean job turnaround time, ensuring site load balance, and considering job priorities. We introduce an enhanced meta-scheduling system, called Job Nature Meta-scheduling over Grid (JNMgrid), that achieves these objectives. JNMgrid consists of three components: (1) Job Analyzer and Monitor, which is responsible for determining the types of jobs in specific ratios; (2) Job Decider, which is responsible for matching the jobs with the appropriate resources; and (3) Job Batcher, which is responsible for determining the best number of jobs for execution. The performance of JNMgrid is compared with similar existing systems, such as Random, Queue Length, File Access Cost, and File Access Cost + Job Queue Access Cost. The simulation results demonstrate that JNMgrid outperforms these systems and can thus be deployed in any grid middleware to improve sharing of limited resources among grid users.

MapReduce based location selection algorithm for utility maximization with capacity constraints

“…Like in earlier parallel processing techniques such P2P computing [21] and Grid computing [1], many efforts have been made in MapReduce for load balancing on skewness input and complex, non-linear algorithms. For example, Kolb et al [11] designed methods to handle skewed data for entity resolution.…”

Quantitative Evaluation of Job and Resources for Better Selection to Improve Makespan in Grid Scheduling

“…The suggested scheduling scheme selects next task to be scheduled based on task priorities and I/O usage status of virtual machines. Al-Khateeb et al (2012) stated that primary metascheduling problem was selecting best resources (sites) to execute underlying jobs while achieving objectives: Reducing mean job turnaround time, ensuring site load balance and considering job priorities. A user's priority is considered to indicate user's requirements.…”

An effective fixed priority co-scheduling algorithm for periodic update and application transactions

“…Scheduling a set of periodic application transactions to meet their deadlines is a typical real-time scheduling problem and various efficient methods such as Earliest Deadline First (EDF) and Rate Monotonic (RM) [3,21] can be adopted. However, simply satisfying the real-time constraints of the application transactions is not sufficient to support real-time monitoring.…”