An Efficient Diffusion Load Balancing Algorithm in Distributed System

Khan, Rafiqul Zaman; Ali, Feroz

doi:10.5815/ijitcs.2014.08.09

Cited by 8 publications

(5 citation statements)

References 24 publications

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“…It has been shown that as more information is collected by an algorithm, the algorithm can make better load balancing decisions however at an increased overhead [16]. Dynamic load balancing technique is opted for heterogeneous systems in computational grids because the technique considers nodes with different processing speeds and memory sizes, bandwidth and load [16].…”

Section: Related Workmentioning

confidence: 99%

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Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids

Balasangameshwara¹

2015

IJIEEB

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Fault tolerant scheduling of many jobs in an environment with millions of unpredictable nodes is not an easy issue. To the best of our knowledge, no work in the literature has proposed a solution that combines the merits of active and passive replication schemes of fault tolerance with the advantages of performance-driven load balancing so as to make the most of the strong points of each. While extensive fault tolerant scheduling and load balancing methods have been presented for the sequential jobs, none have taken into account fault-tolerant load balancing that minimizes the job make-span, provides efficient network and node utilization, achieves a Ill-balanced load and high system flexibility even during the resource failures. Hence, in this article, I present an Adaptive Scheduling Algorithm namely ASA that overcomes these problems. With thorough simulations, I conclude that ASA allocates any number of jobs to a million nodes with relatively low overhead and high flexibility. Experimental results show that the performance of ASA is better than those of its counterparts.

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Section: Related Workmentioning

confidence: 99%

“…Rafiqul and Ali proposed a diffusion load balancing algorithm for distributed computing systems [16]. They have shown that the communication overhead depends on the load of the nodes.…”

Section: Related Workmentioning

confidence: 99%

Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids

Balasangameshwara¹

2015

IJIEEB

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“…In cloud computing, load balancing refers to the distribution of client requirements across multiple application servers operating in the cloud background. Cloud load balancing, aided by various types of load balancers, significantly enhances application performance and reliability [1]. The advantages of dispersing resources from typical local sources often involve cost reduction and meeting demand more efficiently [2].…”

Section: Introductionmentioning

confidence: 99%

Cloud Storage Level Service Offering in Virtualized Load Balancer using AWS

Mohanaprakash T A

2023

IJRITCC

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Distributed computing epitomizes an approach perfectly suited to the realm of IT commitments, leveraging the aggregation of information and resources through electronic cloud service providers utilizing interconnected hardware and software primarily based online, all at a reasonable cost. However, resource sharing can lead to challenges in their accessibility, potentially causing system crashes. To counter this, the technique of distributing network traffic across multiple servers, known as load balancing, plays a pivotal role. This paper ensures that no single server is overwhelmed, thereby preventing overloads and enhancing user responsiveness by equitably distributing tasks. Moreover, it significantly enhances the accessibility of tasks and websites to users. The fundamental objective of this concept is to comprehend load regulation, which operates in tandem with associated frameworks within communication structures like the Web. Load balancing stands as a critical domain within distributed computing, designed to prevent overburdening and to provide equally significant support. Various algorithms are employed to assess the system's complexity. In our proposed strategy, a process is outlined to determine optimal storage space utilization in real-time, utilizing 100 virtual computers, achieving an impressive 92% accuracy rate in its computations. This innovative approach promises efficient resource allocation within the distributed computing framework, thereby optimizing performance and accessibility for end-users.

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“…• Distributes incoming traffic across multiple computational resources Load balancing significantly improves global system performance in terms of throughput and resource utilization. The several reasons to use LBAs are as follows: cost optimization, fault tolerance ability, system adaptability and extensibility, decreased response time, idle time of resources, increased throughput, reliability, and starvation prevention [1,2].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Effective Load Balancing Techniques in Distributed Environment

Shukla¹,

Kumar²,

Singh³

2020

Linked Open Data - Applications, Trends and Future Developments

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Computational approaches contribute the significance role in various fields such as medical applications, astronomy, and weather science, to perform complex calculations in speedy manner. Today, personal computers are very powerful but underutilized. Most of the computer resources are idle; 75% of the time and server are often unproductive. This brings the sense of distributed computing, in which the idea is to use the geographically distributed resources to meet the demand of high-performance computing. The Internet facilitates users to access heterogeneous services and run applications over a distributed environment. Due to openness and heterogeneous nature of distributed computing, the developer must deal with several issues like load balancing, interoperability, fault occurrence, resource selection, and task scheduling. Load balancing is the mechanism to distribute the load among resources optimally. The objective of this chapter is to discuss need and issues of load balancing that evolves the research scope. Various load balancing algorithms and scheduling methods are analyzed that are used for performance optimization of web resources. A systematic literature with their solutions and limitations has been presented. The chapter provides a concise narrative of the problems encountered and dimensions for future extension.

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An Efficient Diffusion Load Balancing Algorithm in Distributed System

Cited by 8 publications

References 24 publications

Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids

Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids

Cloud Storage Level Service Offering in Virtualized Load Balancer using AWS

Analysis of Effective Load Balancing Techniques in Distributed Environment

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