scholarly journals Monitoring and Resource Management in P2P Grid-Based Web Services

2012 ◽  
Vol 1 (2) ◽  
pp. 71-84
Author(s):  
Djafri Laouni ◽  
Mekki Rachida
Keyword(s):  
Fault Tolerance ◽  
Resource Management ◽  
Load Balancing ◽  
Grid Computing ◽  
Grid Infrastructure ◽  
P2p Computing ◽  
P2p Systems ◽  
Processing Power ◽  
Service Load ◽  
High Bandwidth

Grid computing has recently emerged as a response to the growing demand for resources (processing power, storage, etc.) exhibited by scientific applications. However, as grid sizes increase, the need for self-organization and dynamic reconfigurations is becoming more and more important. Since such properties are exhibited by P2P systems, the convergence of grid computing and P2P computing seems natural. However, using P2P systems (usually running on the Internet) on a grid infrastructure (generally available as a federation of SAN-based clusters interconnected by high-bandwidth WANs) may raise the issue of the adequacy of the P2P communication mechanisms. Among the interesting properties of P2P systems is the  volatility of  peers  which  causes  the  need  for  integration  of  a  service fault tolerance. And service Load balancing,   As a solution, we proposed a mechanism of fault tolerance and model of Load balancing  adapted to a grid P2P model, named SGRTE (Monitoring and Resource Management, Fault Tolerances and Load Balancing).DOI: 10.18495/comengapp.12.071084

Ant colony optimization algorithm for load balancing in grid computing

2012 ◽  
Author(s):  
Ku Ruhana Ku-Mahamud ◽  
Aniza Mohamed Din
Keyword(s):  
Resource Management ◽  
Load Balancing ◽  
Grid Computing ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Computing System ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Grid Resource ◽  
Grid Resource Management

Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. The proposed algorithm is known as the enhance ant colony optimization (EACO). The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. The resource allocation problem is modelled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element. The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job. EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job.Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. Experimental results show that EACO produced better grid resource management solution.

A resource management and fault tolerance services in grid computing

2005 ◽  
Vol 65 (11) ◽  
pp. 1305-1317 ◽  
Author(s):  
HwaMin Lee ◽  
KwangSik Chung ◽  
SungHo Chin ◽  
JongHyuk Lee ◽  
DaeWon Lee ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Resource Management ◽  
Grid Computing

scholarly journals The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1410
Author(s):  
Murad B. Khorsheed ◽  
Qasim M. Zainel ◽  
Oday A. Hassen ◽  
Saad M. Darwish
Keyword(s):  
Fault Tolerance ◽  
Load Balancing ◽  
Grid Computing ◽  
Computing Time ◽  
Index Structure ◽  
Computational Grids ◽  
Optimum Number ◽  
Logical Network ◽  
Proposed Model ◽  
Cloud Of Points

This paper applies the entropy-based fractal indexing scheme that enables the grid environment for fast indexing and querying. It addresses the issue of fault tolerance and load balancing-based fractal management to make computational grids more effective and reliable. A fractal dimension of a cloud of points gives an estimate of the intrinsic dimensionality of the data in that space. The main drawback of this technique is the long computing time. The main contribution of the suggested work is to investigate the effect of fractal transform by adding R-tree index structure-based entropy to existing grid computing models to obtain a balanced infrastructure with minimal fault. In this regard, the presented work is going to extend the commonly scheduling algorithms that are built based on the physical grid structure to a reduced logical network. The objective of this logical network is to reduce the searching in the grid paths according to arrival time rate and path’s bandwidth with respect to load balance and fault tolerance, respectively. Furthermore, an optimization searching technique is utilized to enhance the grid performance by investigating the optimum number of nodes extracted from the logical grid. The experimental results indicated that the proposed model has better execution time, throughput, makespan, latency, load balancing, and success rate.

Data Replication in P2P Systems

2010 ◽  
pp. 589-615
Author(s):  
Vassilios V. Dimakopoulos ◽  
Spiridoula Margariti ◽  
Mirto Ntetsika ◽  
Evaggelia Pitoura
Keyword(s):  
Fault Tolerance ◽  
Load Balancing ◽  
Response Time ◽  
Distributed System ◽  
Data Replication ◽  
System Availability ◽  
P2p Systems ◽  
Network Links ◽  
Multiple Copies ◽  
Additional Reason

Maintaining multiple copies of data items is a commonly used mechanism for improving the performance and fault-tolerance of any distributed system. By placing copies of data items closer to their requesters, the response time of queries can be improved. An additional reason for replication is load balancing. For instance, by allocating many copies to popular data items, the query load can be evenly distributed among the servers that hold these copies. Similarly, by eliminating hotspots, replication can lead to a better distribution of the communication load over the network links. Besides performance-related reasons, replication improves system availability, since the larger the number of copies of an item, the more site failures can be tolerated. In this chapter we survey replication methods applicable to p2p systems. Although there exist some general techniques, methodologies are distinguished according to the overlay organization (structured and unstructured) they are aimed at. After replicas are created and distributed, a major issue is their maintenance. We present strategies that have been proposed for keeping replicas up to date so as to achieve a desired level of consistency.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

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