scholarly journals A REVIEW OF GRID COMPUTING

2020 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Armu Sungkar ◽  
Tena Kogoya
Keyword(s):  
Parallel Computing ◽  
Parallel Processing ◽  
Grid Computing ◽  
Resource Utilization ◽  
Task Scheduling ◽  
Memory Capacity ◽  
Batch Mode ◽  
Grid Network ◽  
The World ◽  
Grid Resources

Grid computing is a combination of interconnected resources which can be spread all over the world having higher computing capabilities. The benefit of grid computing includes higher computation and memory capacity because of grid resources spread all over the world. The grid computing is managed by intra-grid scope which refers to the methodologies and the algorithms used for managing the grid network related issues such as task scheduling, resource balancing and security of the network. The advantages of grid computing include access to inaccessible resources, resource utilization and balancing, reliability, and parallel computing and scalability. The limitations of the grid computing include application in limited fields and suitability with applications running in batch mode only based on parallel processing

scholarly journals COST ESTIMATION OF ADVANCE RESERVATIONS OVER QUEUED JOBS: A QUANTITATIVE STUDY

2010 ◽  
Vol 01 (03) ◽  
pp. 317-332 ◽  
Author(s):  
CHUNJIANG ZHAO ◽  
JUNWEI CAO ◽  
HUARUI WU ◽  
FAN ZHANG
Keyword(s):  
Resource Utilization ◽  
Waiting Time ◽  
Cost Estimation ◽  
Resource Sharing ◽  
Cost Ratio ◽  
Advance Reservation ◽  
Batch Mode ◽  
Advance Reservations ◽  
The Impact ◽  
Grid Resources

A grid is a geographically distributed resource sharing environment across multiple organizations. The most typical grid resources are clusters with high performance/cost ratio. In general, these clusters are shared as non-dedicated grid resources since local users may run their jobs simultaneously. Local jobs are usually queued and processed in a batch mode with uncertain waiting time, while grid jobs always require advance reservations with guaranteed resource allocation. In this paper, we provide quantitative analysis on the impact of advance reservations over queued jobs, in terms of job waiting time and resource utilization, respectively. It is observed that advance reservations will lead to longer job waiting time and lower resource utilization. That is to say, advance reservations should cost more than queued jobs. In this work, based on quantitative experimental results, an empirical formula for cost estimation of advance reservations over queued jobs is presented. It is suggested that compared with queued jobs, advance reservations should be doubly charged to compensate resource utilization loss. If the notice time of an advance reservation is short below a threshold, additional cost should be applied further since queue waiting time is increased.

scholarly journals Yield gap and resource utilization efficiency of three major food crops in the world – A review

2021 ◽  
Vol 20 (2) ◽  
pp. 349-362 ◽  
Author(s):  
Liang-bing RONG ◽  
Kai-yuan GONG ◽  
Feng-ying DUAN ◽  
Shao-kun LI ◽  
Ming ZHAO ◽  
...  
Keyword(s):  
Resource Utilization ◽  
Utilization Efficiency ◽  
Food Crops ◽  
Yield Gap ◽  
Major Food ◽  
The World ◽  
Resource Utilization Efficiency

Parallel Scheduling Algorithms Investigation of Support Strict Resource Reservation from Grid

2014 ◽  
Vol 519-520 ◽  
pp. 108-113 ◽  
Author(s):  
Jun Chen ◽  
Bo Li ◽  
Er Fei Wang
Keyword(s):  
Parallel Computing ◽  
Resource Utilization ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Resource Reservation ◽  
Parallel Scheduling ◽  
Scheduling Model ◽  
Computing Grid ◽  
Simulation Results ◽  
Reservation Request

This paper studies resource reservation mechanisms in the strict parallel computing grid,and proposed to support the parallel strict resource reservation request scheduling model and algorithms, FCFS and EASY backfill analysis of two important parallel scheduling algorithm, given four parallel scheduling algorithms supporting resource reservation. Simulation results of four algorithms of resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. The results show that the EASY backfill + firstfit algorithm can ensure QoS of AR jobs while taking into account the performance of good non-AR jobs.

A Heuristic Resource Management Method in Grid Computing Environment

2011 ◽  
Vol 50-51 ◽  
pp. 521-525
Author(s):  
Xian Mei Fang
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Collaborative Research ◽  
Ant Colony Optimization Algorithm ◽  
Computing Environment ◽  
Grid Resource ◽  
Grid Environment ◽  
Load Imbalance ◽  
The World ◽  
Management Method

Grid is an emerging infrastructure which enables effective coordinate access to various distributed computing resources in order to serve the needs of collaborative research and work across the world. Grid resource management is always a key subject in the grid computing. We first analyze the resource management in the grid computing environment, then according to the load imbalance question in the ant colony optimization algorithm, propose an improved algorithm that suits to be used in the grid environment.

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

scholarly journals Enterprise firewall virtualization design

2018 ◽  
Vol 154 ◽  
pp. 03004
Author(s):  
Ari Sujarwo ◽  
Jefferson Tan
Keyword(s):  
Grid Computing ◽  
Resource Provider ◽  
The World

Grid computing could consists of thousand of computers across the world with the role as the resource provider or Grid users. This conditions make a challenge for engineer to keep the Grid secure but at the same the Grid must be easily joined by clients and providers. This paper aims to propose a method to control enterprise firewall which is basically a static engine to be a dynamic engine to cope with the Grid needs. At the end of the paper, the results shows that this method is works and was tested using a real enterprise firewall.

Task Scheduling in Parallel Processing: Analysis

2015 ◽  
Vol 06 (05) ◽  
Author(s):  
Abdul Haq ◽  
Munam Ali Shah
Keyword(s):  
Parallel Processing ◽  
Task Scheduling

Probabilistic State Estimation Based Scheduling Approach for Cloud Computing

2011 ◽  
Vol 55-57 ◽  
pp. 1053-1057
Author(s):  
Gui De Zheng ◽  
Ming Chen
Keyword(s):  
Cloud Computing ◽  
Grid Computing ◽  
State Estimation ◽  
Distributed Data ◽  
Scientific Instruments ◽  
Next Generation ◽  
Data Intensive ◽  
Application Model ◽  
Scientific Experiments ◽  
The World

The next generation of scientific experiments and studies are being carried out by large collaborations of researchers distributed around the world engaged in analysis of huge collections of data generated by scientific instruments. Grid computing has emerged as an enabler for such collaborations as it aids communities in sharing resource to achieve common objective. This paper defines the problem of scheduling distributed data-intensive application on to Gird resource and presents a formal resource and application model for the problem.

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