Using multiple grid resources for bioinformatics applications in GADU

2006 ◽  
Author(s):  
D. Sulakhe ◽  
A. Rodriguez ◽  
M. Wilde ◽  
I. Foster ◽  
N. Maltsev
Keyword(s):  
Grid Resources

A commodity market algorithm for pricing substitutable Grid resources

2007 ◽  
Vol 23 (5) ◽  
pp. 688-701 ◽  
Author(s):  
Gunther Stuer ◽  
Kurt Vanmechelen ◽  
Jan Broeckhove
Keyword(s):  
Commodity Market ◽  
Grid Resources

scholarly journals Fault Tolerant PLBGSA: Precedence Level Based Genetic Scheduling Algorithm for P2P Grid

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Piyush Chauhan ◽  
Nitin
Keyword(s):  
Genetic Algorithm ◽  
Directed Acyclic Graph ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Complex Task ◽  
Grid Scheduling ◽  
Complex Tasks ◽  
Small Organizations ◽  
Grid Resources ◽  
Desirable Trait

Due to monetary limitation, small organizations cannot afford high end supercomputers to solve highly complex tasks. P2P (peer to peer) grid computing is being used nowadays to break complex task into subtasks in order to solve them on different grid resources. Workflows are used to represent these complex tasks. Finishing such complex task in a P2P grid requires scheduling subtasks of workflow in an optimized manner. Several factors play their part in scheduling decisions. The genetic algorithm is very useful in scheduling DAG (directed acyclic graph) based task. Benefit of a genetic algorithm is that it takes into consideration multiple criteria while scheduling. In this paper, we have proposed a precedence level based genetic algorithm (PLBGSA), which yields schedules for workflows in a decentralized fashion. PLBGSA is compared with existing genetic algorithm based scheduling techniques. Fault tolerance is a desirable trait of a P2P grid scheduling algorithm due to the untrustworthy nature of grid resources. PLBGSA handles faults efficiently.

scholarly journals A concept for attribute-based authorization on D-Grid resources

2009 ◽  
Vol 25 (3) ◽  
pp. 275-280 ◽  
Author(s):  
Ralf Groeper ◽  
Christian Grimm ◽  
Siegfried Makedanz ◽  
Hans Pfeiffenberger ◽  
Wolfgang Ziegler ◽  
...  
Keyword(s):  
Grid Resources

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 A Weight-based Query Forwarding Technique for Super-peer-based Grid Resource Discovery

2017 ◽  
Vol 7 (1) ◽  
pp. 1398-1404
Author(s):  
M. Mollamotalebi ◽  
R. Maghami ◽  
A. S. Ismail
Keyword(s):  
Response Time ◽  
Resource Discovery ◽  
Search Process ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Applications ◽  
Computing Environments ◽  
Grid Resources ◽  
Grid Resource Discovery ◽  
Super Peer

Grid computing environments include heterogeneous resources shared by a large number of computers to handle data and process intensive applications. The required resources must be accessible for the grid applications on demand, which makes resource discovery a critical service. In recent years, different techniques are provided to index and discover grid resources. Response time and message load during the search process highly affect the efficiency of resource discovery. This paper proposes a technique to forward the queries based on the resource types accessible through each neighbor in super-peer-based grid resource discovery approaches. The proposed technique is simulated in GridSim and the experimental results indicated that it is able to reduce the response time and message load during the search process especially when the grid environment contains a large number of nodes.

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