Performance Analysis in Distributed System of Dynamic Load Balancing Using Fuzzy Logic

Saxena, Shailesh; Khan, Mohd Zubair; Singh, Ravendra

doi:10.1109/scet.2012.6341923

Cited by 6 publications

(6 citation statements)

References 7 publications

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“…In Figure 14, the comparison of throughput is illustrated for RRA and RA, where the respective data are gathered, filtered and compared from Saxena et al (2012), Kwork and Cheung (2004), Ahn et al (2007) and Ali and Derakhshi (2016). As illustrated in Figure 14, the performance of RA is aperiodic and tends to overshoot or undershoot with respect to the number of nodes.…”

Section: Analysis Of Algorithmic Performancesmentioning

confidence: 99%

“…Following the above statistics it can be stated that the average response time per node is not directly dependent on the number of nodes, instead it is highly dependent on the increasing communication overhead due to increasing node count in the system. In Figure 23, the comparative study of variations of normalised average response time (∆Tna) with respect to CRA and DRA is illustrated, where the respective data are gathered, filtered and compared from (Kwork and Cheung, 2004;Saxena et al, 2012;Cheung, 2001). In centralised approach which employs Random algorithm (CRA), the average response time per node decreases rapidly when the number of nodes is increased.…”

Section: Analysis Of Algorithmic Performancesmentioning

confidence: 99%

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A comparative study and analysis of agent based monitoring and fuzzy load balancing in distributed systems

Ali

Bagchi

2019

IJCNDS

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Load balancing algorithms are designed to achieve efficient resource utilisation in large-scale distributed systems. The primary goal of designing load balancing algorithms is to balance the overall workload among all the nodes in distributed systems to improve the performance. This paper presents an in-depth study and detailed comparative analysis of different load monitoring and balancing algorithms employing fuzzy logic and mobile agents. A detailed qualitative as well as quantitative analysis of algorithmic performances is included. The analytical survey presented in this paper would enable understanding of applications of different algorithms under different computing environments. Furthermore, this paper proposes a hybrid architecture combining fuzzy logic and mobile agents for load balancing and monitoring in distributed systems.

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Section: Analysis Of Algorithmic Performancesmentioning

confidence: 99%

Section: Analysis Of Algorithmic Performancesmentioning

confidence: 99%

A comparative study and analysis of agent based monitoring and fuzzy load balancing in distributed systems

Ali

Bagchi

2019

IJCNDS

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“…Gang [2] proposed a method to classify the user requested services to allocate the system resources, so as to achieve dynamic load balancing. Shailesh [3] used a fuzzy dynamic load balancing algorithm to achieve load balancing through task scheduling. Liu [6] proposed a distributed load balancing algorithm using a defined protocol sequence, and developed a model of queuing distributed asynchronous multi-server system.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, it is important that special attention should be given to restructure the system behaviors in accordance with the changes in user behaviors by balancing the system load. Existing system load balancing methods [1][2][3] are mainly based on resource allocation and task scheduling strategies, but not consider when and how to dynamically reconstruct the system behaviors for the real-time load equilibrium.…”

Section: Introductionmentioning

confidence: 99%

Behavior Reconstruction Models for Large-scale Network Service Systems

Zhang

Liu

Wang

et al. 2018

Peer-to-Peer Netw. Appl.

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In large-scale network service systems, the phenomenon of instantaneous gathering of a large number of users can cause system abnormality, whenever the load imposed by the user behaviors does not match the system load. This paper proposes a behavior reconstruction model for large-scale network service systems integrated with Petri net reconstruction methodology, for the purpose of achieving load balancing in the system under increasing number of users. Based on the features of the user interaction behavior sequence, the behavioral load balancing model defines a user behavior membership function. Then, a random fuzzy Petri net with delay is presented to control the user behavior reconstruction. Experiments conducted by considering various changes in the number of user behaviors and their distribution in unit time demonstrate that the proposed methodology can effectively trigger the reconstructed model to balance the system load when the system load exceeds the defined warning point.

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“…Qin [5] and Gong [6] have introduced feedback to dynamically adjust the weight of each resource. Zhang [7] and Saxena [8] have presented fuzzy control theory to grade server load to different levels. But in these algorithms, resource utilization between monitoring intervals is unknown.…”

Section: Related Workmentioning

confidence: 99%

A predictive dynamic load balancing algorithm with service differentiation

Jiang

Deng

Xue

2013

2013 15th IEEE International Conference on Communication Technology

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The existing dynamic load balancing algorithms usually monitor load on servers and allocate requests to the least loaded server. But load between monitoring intervals is unknown because the monitoring is not real-time. And most of them can not differentiate services. This paper proposes a predictive dynamic load balancing algorithm which takes services types into consideration. The scheduler monitors resource utilization and number of active requests in each server. Considering service's preference for different resources, the average resource overhead of each service can be calculated using multiple reverse differentials. During request allocation, the appropriate server node is chosen to achieve optimal load balancing. Moreover, the resource utilization of each server node between monitoring intervals can be real-time predicted. The results demonstrate that the proposed algorithm can achieve shorter response time, fewer failed requests and more balanced load compared with existing dynamic load balancing algorithms.

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Performance Analysis in Distributed System of Dynamic Load Balancing Using Fuzzy Logic

Cited by 6 publications

References 7 publications

A comparative study and analysis of agent based monitoring and fuzzy load balancing in distributed systems

A comparative study and analysis of agent based monitoring and fuzzy load balancing in distributed systems

Behavior Reconstruction Models for Large-scale Network Service Systems

A predictive dynamic load balancing algorithm with service differentiation

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