Scheduling in Distributed Computing Environment Using Dynamic Load Balancing
Title | Scheduling in Distributed Computing Environment Using Dynamic Load Balancing PDF eBook |
Author | Priyesh Kanungo |
Publisher | Anchor Academic Publishing |
Pages | 153 |
Release | 2016-08 |
Genre | Computers |
ISBN | 396067046X |
This book illustrates various components of Distributed Computing Environment and the importance of distributed scheduling using Dynamic Load Balancing. It describes load balancing algorithms for better resource utilization, increasing throughput and improving user’s response time. Various theoretical concepts, experiments, and examples enable students to understand the process of load balancing in computing cluster and server cluster. The book is suitable for students of Advance Operating Systems, High Performance Computing, Distributed Computing in B.E., M.C.A., M. Tech. and Ph.D courses.
Scheduling in Distributed Computing Environment Using Dynamic Load Balancing
Title | Scheduling in Distributed Computing Environment Using Dynamic Load Balancing PDF eBook |
Author | Priyesh Kanungo |
Publisher | Anchor Academic Publishing |
Pages | 147 |
Release | 2016-05-26 |
Genre | Computers |
ISBN | 3960675461 |
This book illustrates various components of Distributed Computing Environment and the importance of distributed scheduling using Dynamic Load Balancing. It describes load balancing algorithms for better resource utilization, increasing throughput and improving user’s response time. Various theoretical concepts, experiments, and examples enable students to understand the process of load balancing in computing cluster and server cluster. The book is suitable for students of Advance Operating Systems, High Performance Computing, Distributed Computing in B.E., M.C.A., M. Tech. and Ph.D courses.
Performance Studies of Dynamic Load Balancing in Distributed Systems
Title | Performance Studies of Dynamic Load Balancing in Distributed Systems PDF eBook |
Author | University of California, Berkeley. Computer Science Division |
Publisher | |
Pages | 336 |
Release | 1987 |
Genre | |
ISBN |
Distributed systems are often characterized by uneven loads on hosts and other resources. In this thesis, the problems concerning dynamic load balancing in loosely-coupled distributed systems are studied using trace-driven simulation, implementation, and measurement. Information about job CPU and I/O demands is collected from three production systems and used as input to a simulator that includes a representative CPU scheduling policy and considers the message exchange and job transfer costs explicitly. A prototype load balancer is implemented in the Berkeley UNIX and Sun/UNIX environments, and the results of a large number of measurement experiments performed on six workstations are presented.
Scheduling and Load Balancing in Parallel and Distributed Systems
Title | Scheduling and Load Balancing in Parallel and Distributed Systems PDF eBook |
Author | Behrooz A. Shirazi |
Publisher | Wiley-IEEE Computer Society Press |
Pages | 524 |
Release | 1995-05-14 |
Genre | Computers |
ISBN |
This book focuses on the future directions of the static scheduling and dynamic load balancing methods in parallel and distributed systems. It provides an overview and a detailed discussion of a wide range of topics from theoretical background to practical, state-of-the-art scheduling and load balancing techniques.
A FRAMEWORK FOR SCALABLE DISTRIBUTED JOB PROCESSING WITH DYNAMIC LOAD BALANCING USING DECENTRALIZED APPROACH
Title | A FRAMEWORK FOR SCALABLE DISTRIBUTED JOB PROCESSING WITH DYNAMIC LOAD BALANCING USING DECENTRALIZED APPROACH PDF eBook |
Author | Dr P. SrinivasaRao |
Publisher | Lulu.com |
Pages | 97 |
Release | 2017-12-30 |
Genre | Education |
ISBN | 1387388762 |
A distributed system consists of many heterogeneous processors with different processing power and all processors are interconnected with a communication channel. In such a system, if some processors are less loaded or idle and others are heavily loaded, the system performance will be reduced drastically. System performance can be improved by using proper load balancing [1, 4]. The aim of load balancing is to improve the performance measures and reduce the overall completion time and cost
Emerging Trends in Expert Applications and Security
Title | Emerging Trends in Expert Applications and Security PDF eBook |
Author | Vijay Singh Rathore |
Publisher | Springer |
Pages | 723 |
Release | 2018-11-19 |
Genre | Technology & Engineering |
ISBN | 9811322856 |
The book covers current developments in the field of expert applications and security, which employ advances of next-generation communication and computational technology to shape real-world applications. It gathers selected research papers presented at the ICETEAS 2018 conference, which was held at Jaipur Engineering College and Research Centre, Jaipur, India, on February 17–18, 2018. Key topics covered include expert applications and artificial intelligence; information and application security; advanced computing; multimedia applications in forensics, security and intelligence; and advances in web technologies: implementation and security issues.
Intelligent and Cloud Computing
Title | Intelligent and Cloud Computing PDF eBook |
Author | Debahuti Mishra |
Publisher | Springer Nature |
Pages | 834 |
Release | 2020-10-30 |
Genre | Technology & Engineering |
ISBN | 9811559716 |
This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2019), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, on December 20, 2019. Including contributions on system and network design that can support existing and future applications and services, it covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems.