Load balancing techniques in grid environment: A survey

Raj, R. Joshua Samuel; Fiona, Rex

doi:10.1109/iccci.2013.6466142

Cited by 6 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the case of a GRID system, the intensity µ cl is interpreted as the average number of computational resources included per unit of time by the RU (namely, the resource broker) in the GRID instead of the failed resources. In this case, the average recovery time of one computational resource will be equal to (21).…”

Section: Grid System Reliability Assessment Modelmentioning

confidence: 99%

“…The proposed algorithm is divided into two steps to reduce the time spent on executing jobs or to reduce the response time and communication cost between transferring jobs from one computing node to another in a GRID architecture. The authors of [21] classify methods for solving GRID system load balancing and load balancing problems based on their objective functions into two categories: application-oriented and resource-intensive methods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical Models for the Design of GRID Systems to Solve Resource-Intensive Problems

Tynchenko,

Nelyub

et al. 2024

Mathematics

View full text Add to dashboard Cite

Artificial neural networks are successfully used to solve a wide variety of scientific and technical problems. The purpose of the study is to increase the efficiency of distributed solutions for problems involving structural-parametric synthesis of neural network models of complex systems based on GRID (geographically disperse computing resources) technology through the integrated application of the apparatus of evolutionary optimization and queuing theory. During the course of the research, the following was obtained: (i) New mathematical models for assessing the performance and reliability of GRID systems; (ii) A new multi-criteria optimization model for designing GRID systems to solve high-resource computing problems; and (iii) A new decision support system for the design of GRID systems using a multi-criteria genetic algorithm. Fonseca and Fleming’s genetic algorithm with a dynamic penalty function was used as a method for solving the stated multi-constrained optimization problem. The developed program system was used to solve the problem of choosing an effective structure of a centralized GRID system that was configured to solve the problem of structural-parametric synthesis of neural network models. To test the proposed approach, a Pareto-optimal configuration of the GRID system was built with the following characteristics: average performance–103.483 GFLOPS, cost–500 rubles per day, availability rate–99.92%, and minimum performance–51 GFLOPS.

show abstract

Section: Grid System Reliability Assessment Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical Models for the Design of GRID Systems to Solve Resource-Intensive Problems

Tynchenko,

Nelyub

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

“…Although there have been some related surveys previously, but most of which only made a very preliminary review on the state of art of one single type of distributed system, such as the survey of load balancing in grids [91] [92], the survey of load balancing in cloud computing [93] [94], and the survey of load balancing in P2P systems [95]. Then, how to correlate the related studies in varying types of distributed systems and make a general taxonomy on them?…”

Section: Introductionmentioning

confidence: 99%

A Survey of Task Allocation and Load Balancing in Distributed Systems

Jiang

2016

IEEE Trans. Parallel Distrib. Syst.

166

View full text Add to dashboard Cite

In past decades, significant attention has been devoted to the task allocation and load balancing in distributed systems. Although there have been some related surveys about this subject, each of which only made a very preliminary review on the state of art of one single type of distributed systems. To correlate the studies in varying types of distributed systems and make a comprehensive taxonomy on them, this survey mainly categorizes and reviews the representative studies on task allocation and load balancing according to the general characteristics of varying distributed systems. First, this survey summarizes the general characteristics of distributed systems. Based on these general characteristics, this survey reviews the studies on task allocation and load balancing with respect to the following aspects: 1) typical control models; 2) typical resource optimization methods; 3) typical methods for achieving reliability; 4) typical coordination mechanisms among heterogeneous nodes; and 5) typical models considering network structures. For each aspect, we summarize the existing studies and discuss the future research directions. Through the survey, the related studies in this area can be well understood based on how they can satisfy the general characteristics of distributed systems.

show abstract

“…Also there are many studies about load balancing in distributed and peer to peer networks [19][20][21][22][23], but a little comprehensive research about load balancing in the field of cloud computing has been done yet and we just can refer to some papers that there are in the field of load balancing in cloud computing [24][25][26][27][28]. In this paper we present a survey of the algorithms, architectures and all techniques which have proposed for cloud computing load balancing.…”

Section: Introductionmentioning

confidence: 99%

Load Balancing in Cloud Computing: A State of the Art Survey

Mesbahi

Rahmani

2016

IJMECS

View full text Add to dashboard Cite

Abstract-Cloud computing has proposed a new perspective for provisioning the large-scale computing resources by using virtualization technology and a payper-use cost model. Load balancing is taken into account as a vital part for parallel and distributed systems. It helps cloud computing systems by improving the general performance, better computing resources utilization, energy consumption management, enhancing the cloud services' QoS, avoiding SLA violation and maintaining system stability through distribution, controlling and managing the system workloads. In this paper we study the necessary requirements and considerations for designing and implementing a suitable load balancer for cloud environments. In addition we represent a complete survey of current proposed cloud load balancing solutions which according to our classification, they can be classified into three categories: General Algorithm-based, Architectural-based and Artificial Intelligence-based load balancing mechanisms. Finally, we propose our evaluation of these solutions based on suitable metrics and discuss their pros and cons.

show abstract

Load balancing techniques in grid environment: A survey

Cited by 6 publications

References 6 publications

Mathematical Models for the Design of GRID Systems to Solve Resource-Intensive Problems

Mathematical Models for the Design of GRID Systems to Solve Resource-Intensive Problems

A Survey of Task Allocation and Load Balancing in Distributed Systems

Load Balancing in Cloud Computing: A State of the Art Survey

Contact Info

Product

Resources

About