The New Genetic Based Method with Optimum Number of Super Node for Fault Tolerant System in Heterogeneous Wireless Sensor Network

Navimipour, Nima Jafari; Rahmani, Amir Masoud

doi:10.7763/ijcee.2010.v2.120

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…GA is a nature‐inspired method, and the evolution of behavior in humans and animals is utilized in this algorithm. Recent studies have proved that GA finds near‐optimal solutions in complex and NP‐hard problems 5–7,10,13,49,50 . Each solution in the problem's search space is named “chromosome” and is constructed by genes.…”

Section: Proposed Algorithm (Ratsa)mentioning

confidence: 99%

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A new reliability‐based task scheduling algorithm in cloud computing

Motlagh

Movaghar

Rahmani

2021

Int J Communication

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Summary In the last decade, the scale of heterogeneous computing (HC) systems such as heterogeneous cloud computing environments was growing like never before. So network failures are unavoidable in such systems, which affect system reliability. Since the task scheduling algorithm in HC is challenging, we investigate a new reliability‐aware task scheduling algorithm (RATSA) in this paper. RATSA is designed to schedule tasks on directed acyclic graphs (DAGs) by using the shuffled frog‐leaping algorithm (SFLA) and genetic algorithm (GA) as evolutionary algorithms. The population‐based SFLA‐GA is applied to optimize makespan in the RATSA as an NP‐complete problem. Moreover, the proposed algorithm exploits a new heuristic‐based earliest finish time technique for task mapping to virtual machines (VMs) section to decrease the failure rate. Experimental results on random DAGs indicate that RATSA improves some current algorithms in terms of reliability and has acceptable performance in makespan. The results reveal that the RATSA decreases the overall failure rate by 43% compared to some current task scheduling algorithms.

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Section: Proposed Algorithm (Ratsa)mentioning

confidence: 99%

“…Recent studies have proved that GA finds near-optimal solutions in complex and NP-hard problems. [5][6][7]10,13,49,50 Each solution in the problem's search space is named "chromosome" and is constructed by genes. Moreover, the fitness value for each chromosome is computed to evaluate the quality of solutions.…”

Section: Sfla and Gamentioning

confidence: 99%

A new reliability‐based task scheduling algorithm in cloud computing

Motlagh

Movaghar

Rahmani

2021

Int J Communication

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“…As a result of the growth of IT-based systems [1,2], grid computing [3][4][5], cloud computing [6,7], expert cloud [8,9], and MapReduce [10] provide efficient means to transfer data and share resources [11]. In particular, cloud computing is a new idea that represents the collaboration between multiple services and computers over a network, giving users many robust on-demand services at their fingertips.…”

Section: Introductionmentioning

confidence: 99%

An Implementation of Modified Blowfish Technique with Honey Bee Behavior Optimization for Load Balancing in Cloud System Environment

Rani

Singh

Verma

et al. 2022

Wireless Communications and Mobile Computing

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Cloud computing is a system that allows data to be saved in the cloud on a virtual worker. Outsiders and virtual machines in the cloud worker supplier played a critical part in efficiently storing and accessing information. Security, access control, and load balancing are critical challenges in cloud engineering. In the past, various solutions for adjusting cloud load have been proposed. Operator-based burden adjustment calculation surpassed all other offered CPU use, cost, and idle time strategies. The productivity of the specialist-based load adjustment computation decreased when any of the client hubs changed regions. Experimental outcomes show that Modified-HBB-LB performs better than the existing load balancing strategies such as HBB-LB, DLB, FCFS, WRR, HDLB, and FIFO by achieving the load balance of the complete system. The Modified-HBB-LB technique reduces the number of migrations tasks (30%, 25% and 20%) as compared to HDLB, DLB, and HBB-LB. The proposed Modified-HBB-LB technique maintains the 3-5% higher performance levels on makespan, completion, and response time as compared to existing comparative techniques.

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