Grid computing technology can be seen as a positive alternative for implementing high-performance distributed computing. The goal of Grid computing is to create the illusion of virtual computer out of a large collection of connected heterogeneous nodes sharing various resources. The Grid system needs competent load balancing algorithms for the distribution of tasks in order to increase performance and efficiency. The process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring grid resources over time in order to run grid applications efficiently is known as Grid Resource Management. The main aim of load balancing is to provide a distributed, low-cost scheme that balances the load across all the processors. This book guides about a dynamic load balancing algorithm strategy in a simulated grid environment which fulfils the objective to achieve high performance computing by optimal usage of geographically distributed and heterogeneous resources in the grid environment.
Kapil B. Morey has completed his Master's in Computer Engineering from the Amravati University, India. He has worked in IT domain of different Private and Government organizations as well as an Assistant Professor in Engineering Institute. He has published various research papers in reputed journals and completed various technical certifications.
Über den Autor
Kapil B. Morey hat seinen Master in Computertechnik an der Universität Amravati, Indien, abgeschlossen. Er hat im IT-Bereich verschiedener privater und staatlicher Organisationen sowie als Assistenzprofessor in einem technischen Institut gearbeitet. Er hat verschiedene Forschungsarbeiten in renommierten Fachzeitschriften veröffentlicht und verschiedene technische Zertifizierungen erworben.
Klappentext
Grid computing technology can be seen as a positive alternative for implementing high-performance distributed computing. The goal of Grid computing is to create the illusion of virtual computer out of a large collection of connected heterogeneous nodes sharing various resources. The Grid system needs competent load balancing algorithms for the distribution of tasks in order to increase performance and efficiency. The process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring grid resources over time in order to run grid applications efficiently is known as Grid Resource Management. The main aim of load balancing is to provide a distributed, low-cost scheme that balances the load across all the processors. This book guides about a dynamic load balancing algorithm strategy in a simulated grid environment which fulfils the objective to achieve high performance computing by optimal usage of geographically distributed and heterogeneous resources in the grid environment.
