Priority based Distributed Job Processing System
نویسندگان
چکیده
منابع مشابه
Agent Based Priority Heuristic for Job Scheduling on Computational Grids
A grid is an infrastructure for resource sharing. At present, many scientific applications require high computing power in processing, which can only be achieved by using the computational grid. For the selection and allocation of grid resources to current and future applications, grid job scheduling is playing a very vital role for computational grids. They constitute the building blocks for m...
متن کاملRecurring Job Optimization for Massively Distributed Query Processing
Companies providing cloud-scale data services have increasing needs to store and analyze massive data sets. For cost and performance reasons, processing is typically done on large clusters of tens of thousands of commodity machines. Developers use high-level scripting languages that simplify understanding various system trade-offs, but introduce new challenges for query optimization. One key op...
متن کاملScalable Distributed Job Processing with Dynamic Load Balancing
We present here a cost effective framework for a robust scalable and distributed job processing system that adapts to the dynamic computing needs easily with efficient load balancing for heterogeneous systems. The design is such that each of the components are self contained and do not depend on each other. Yet, they are still interconnected through an enterprise message bus so as to ensure saf...
متن کاملDesign and configuration of distributed job processing systems
A key criterion in the design, procurement and use of computer systems is performance. Performance typically means the throughput and response time of a system. The effects of poorly performing systems range from dissatisfied users to high penalties for companies due to missed processing deadlines. As a result of continuously increasing hardware performance, companies often solve performance pr...
متن کاملDima: A Distributed In-Memory Similarity-Based Query Processing System
Data analysts in industries spend more than 80% of time on data cleaning and integration in the whole process of data analytics due to data errors and inconsistencies. It calls for effective query processing techniques to tolerate the errors and inconsistencies. In this paper, we develop a distributed in-memory similarity-based query processing system called Dima. Dima supports two core similar...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2012
ISSN: 0975-8887
DOI: 10.5120/9783-4319