An evolution of the state of affairs of grid computing : current and future projections by Haque, Mesbah, 1972-

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ALiCE: A Java-based Grid Computing System by Teo, Yong Meng

“…Firstly, we give an overview of the main issues in grid computing. Next, we introduce ALiCE (Adaptive and Scalable Internet-based Computing Engine), a platform independent and lightweight grid. …”
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CST333 – Distributed & Grid Computing (Perkomputeran Teragih & Grid) by PPSKOM, Pusat Pengajian Sains Komputer

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Enchancement of a simple user authentication scheme for grid computing by Ramamoorthy, Viknesh

Automatic visualizaion pipeline formation for medical on grid computing environment by Ahmed, Aboamama Atahar, Abd. Latif, Muhammad Shafie, Abu Bakar, Kamalrulnizam, Ahmad Rajion, Zainul

“…Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. …”
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Enhancement of a simple user authentication scheme for grid computing by Ramamoorthy, Viknesh

“…Grid computing means a multiple independent computing, because it is composed of resource nodes not located within a single administrative domain. …”
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Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

“…Job scheduling algorithm has a significant influence on grid computing performance. Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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Towards self-resource discovery and selection models in grid computing by Alzboon, M. S., Ariffin, Ahmad Shabudin, Mahmuddin, Massudi

“…Global computational grids nowadays are suffered from ossification problems due to the following fundamental challenges related to different existing solutions in grid computing: scalability, adaptability, security, reliability, availability and manageability.The management difficulty is due to heterogeneity, dynamicity and locality of the resources within global grid networks.Large-scale grids make the fundamental problem of resource discovery a great challenge.This paper presents a self-resource discovery mechanism (SRDM) that achieves efficient grid resource discovery and takes advantage of the strengths of both hierarchy and decentralized approaches that were previously developed for grid based P2P resource discovery.P2P systems offer potential strengths such as self-organization, self-healing, and robustness to failure or attacks. …”
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A critical review on resource allocation mechanisms in grid computing by Dakkak, Omar, Awang Nor, Shahrudin, Che Mohamed Arif, Ahmad Suki

“…t- In recent years, the fast evolution in the industry of computer hardware such as the processors, has led the application developers to design advanced softwares that require massive computational power.Thus, Grid Computing has emerged in order to handle the computational power demands that requested from the application.To manage the scheduling of resources and arranging the jobs based on certain criteria, resource allocation mechanisms are used.In this paper, we critically review some of these mechanisms in “Grid Computing” environment.In addition, the paper offers a comparison among the reviewed mechanisms in order to guide the researcher in choosing the suitable mechanism that fits the running application…”
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Load balancing using enhanced ant algorithm in grid computing by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Load balancing is one of the critical issues that must he considered in managing a grid computing environment.It is complicated due to the distributed and heterogeneous nature of the resources.An enhanced ant algorithm for load balancing in grid computing is proposed in this papcr.The proposed algorithm will determine the best resource to he allocated to the jobs based on job characteristics and resource capacity, and at the same time to balance the entire resources.The proposed algorithm focuses on local pheromone trail update and trail limit. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.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 modeled 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. …”
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Automatic visualization pipeline formation for medical datasets on grid computing environment / by Muhammad Shafie Abd. Latiff, author, Aboamama Atahar Ahmed, author, Kamalrulnizam Abu Bakar, author, Zainul Ahmad Rajion, author, International Conference on Computer Systems Design and Architecture (2007 : Italy)

Grid resource management : towards virtual and services compliant grid computing / by Magoules, F. (Frederic), Nguyen, Thi-Mai-Huong, Yu, Lei

Subjects: “…Computational grids (Computer systems)…”

Power system security analysis using grid computing [electronic resource] / by Husham Idan Hussein, 1978-, Mohamed Abd El-Moneim Shaaban, supervisor

Subjects:

A New resource ranking and selection technique for grid computing environments / by Ssozi Michael, 1987-, Aboamama Atahar Ahmed, Fakulti Sains Komputer dan Sistem Maklumat

Subjects: “…Computational grids (Computer systems)…”

Experiences with distributed computing for meteorological applications: grid computing and cloud computing by F. Oesterle, S. Ostermann, R. Prodan, G. J. Mayr

“…Through presenting cloud and grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. …”
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Min-Min Chromosome Genetic Algorithm for Load Balancing in Grid Computing by Wanneng Shu, Jiangqing Wang

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SELF-LEARNING OF PARAMETER WEIGHTS FOR TASK SCHEDULING IN GRID COMPUTING ENVIRONMENT by Donatas Sandonavičius, Aušra Gadeikytė, Giedrius Paulikas, Mindaugas Vaitkūnas, Gytis Vilutis, Gintaras Butkus

“…The Grid computing environment is very important for solving scientific problems. …”
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Greedy Firefly Algorithm for Optimizing Job Scheduling in IoT Grid Computing by Adil Yousif, Samar M. Alqhtani, Mohammed Bakri Bashir, Awad Ali, Rafik Hamza, Alzubair Hassan, Tawfeeg Mohmmed Tawfeeg

“…New job scheduling techniques are crucial for the effective integration and management of IoT with grid computing as they provide optimal computational solutions. …”
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