Research on Information Processing with Delay Fair Scheduling Algorithm Based on Resource Situation

2014 ◽  
Vol 1046 ◽  
pp. 363-366 ◽  
Author(s):  
Xue Ying Jiang ◽  
Yang Yang ◽  
Di Jing
Keyword(s):  
Information Processing ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Experimental Results ◽  
Original Algorithm ◽  
Fair Scheduling ◽  
Key Technologies ◽  
Hadoop Platform ◽  
Run Time ◽  
Resource Situation

Job scheduling algorithm is one of the key technologies Hadoop platform. In this paper, waiting for a fair scheduling algorithm based on delay resource situation. The algorithm periodically obtain status through the use of cluster resources to determine the wait timeout, it has dynamic. Experimental results show that the Delay Fair Scheduling Algorithm Based On the Resource Situation than the original algorithm to some extent reduces the job run time and improve the throughput of Hadoop platform.

Research on Information Processing with Dynamic Adaptive Job Scheduling Algorithm Based on Hadoop Platform

2014 ◽  
Vol 1046 ◽  
pp. 359-362
Author(s):  
Xue Ying Jiang ◽  
Yao Wang ◽  
Yan Yan Meng
Keyword(s):  
Resource Allocation ◽  
Information Processing ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Feedback Mechanism ◽  
Control Node ◽  
Optimal Resource ◽  
Hadoop Platform ◽  
Overall Performance ◽  
Job Scheduling Algorithm

Job scheduling and resource allocation problems relate to the overall performance and resource utilization of Hadoop platform. This paper proposes a dynamic adaptive job scheduling algorithm based on Hadoop platform. This algorithm monitors the change of each computing resource nodes in real time. And through the feedback mechanism pass this information to the control node. It implements the purpose of assign the optimal resource for each of tasks.

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2010 ◽  
Vol 2 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
Grid Environment ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2012 ◽  
pp. 13-30
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
System Load ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this paper is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

scholarly journals Improved fair Scheduling Algorithm for Hadoop Clustering

2017 ◽  
Vol 10 (1) ◽  
pp. 194-200 ◽  
Author(s):  
Sneha Sneha ◽  
Shoney Sebastian
Keyword(s):  
Response Time ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Map Reduce ◽  
Process Data ◽  
Strategy Analysis ◽  
Fair Scheduling ◽  
New Strategy ◽  
And Performance

Traditional way of storing such a huge amount of data is not convenient because processing those data in the later stages is very tedious job. So nowadays, Hadoop is used to store and process large amount of data. When we look at the statistics of data generated in the recent years it is very high in the last 2 years. Hadoop is a good framework to store and process data efficiently. It works like parallel processing and there is no failure or data loss as such due to fault tolerance. Job scheduling is an important process in Hadoop Map Reduce. Hadoop comes with three types of schedulers namely FIFO (First in first out), Fair and Capacity Scheduler. The schedulers are now a pluggable component in the Hadoop Map Reduce framework. This paper talks about the native job scheduling algorithms in Hadoop. Fair scheduling algorithm is analysed with its algorithm considering its response time, throughput and performance. Advantages and drawbacks of fair scheduling algorithm is discussed. Improvised fair scheduling algorithm is proposed with new strategy. Analysis is made with respect to response time, throughput and performance is calculated in naive fair scheduling and improvised fair scheduling. Improvised fair Scheduling algorithms is used in the cases where there is jobs with high and less processing time.

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2012 ◽  
pp. 1114-1131
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
System Load ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this paper is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

Compiler-Aided Run-Time Performance Speed-Up in Super-Scalar Processor

10.28945/3391 ◽  
2009 ◽  
Author(s):  
Moshe Pelleh
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
General Purpose ◽  
Experimental Results ◽  
Medium Size ◽  
Organic System ◽  
Software Application ◽  
Organic Systems ◽  
Special Cases ◽  
Run Time

In our world, where most systems become embedded systems, the approach of designing embedded systems is still frequently similar to the approach of designing organic systems (or not embedded systems). An organic system, like a personal computer or a work station, must be able to run any task submitted to it at any time (with certain constrains depending on the machine). Consequently, it must have a sophisticated general purpose Operating System (OS) to schedule, dispatch, maintain and monitor the tasks and assist them in special cases (particularly communication and synchronization between them and with external devices). These OSs require an overhead on the memory, on the cache and on the run time. Moreover, generally they are task oriented rather than machine oriented; therefore the processor's throughput is penalized. On the other hand, an embedded system, like an Anti-lock Braking System (ABS), executes always the same software application. Frequently it is a small or medium size system, or made up of several such systems. Many small or medium size embedded systems, with limited number of tasks, can be scheduled by our proposed hardware architecture, based on the Motorola 500MHz MPC7410 processor, enhancing its throughput and avoiding the software OS overhead, complexity, maintenance and price. Encouraged by our experimental results, we shall develop a compiler to assist our method. In the meantime we will present here our proposal and the experimental results.

Fair scheduling algorithm in IEEE 802.16e system

2009 ◽  
Vol 29 (5) ◽  
pp. 1204-1207
Author(s):  
Hong-xia ZHANG ◽  
Ju-feng DAI
Keyword(s):  
Scheduling Algorithm ◽  
Ieee 802.16E ◽  
Fair Scheduling
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