Performance-Driven Load Balancing with a Primary-Backup Approach for Computational Grids with Low Communication Cost and Replication Cost

Balasangameshwara, Jasma; Nedunchezhian, R.

doi:10.1109/tc.2012.44

Cited by 46 publications

(24 citation statements)

References 40 publications

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“…Scheduling mentioned above like minmin and maxmin maps different tasks to different available resources efficiently but it does not maintain proper load balancing among the resources due to which some resources are utilized and some remain idle. This load balancing concept can be applied to this scheduling to get done execution faster [8].…”

Section: Load Balancing In Distributed Systemmentioning

confidence: 99%

Scheduling Tasks in Heterogeneous System using Load Balancing Algorithm

Patil¹,

Ade²

2017

IJCA

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Innovative idea of distributing the tasks to their best processor to reduce the execution time of task by using various scheduling techniques is given in this paper. This paper presents hybrid scheduling techniques which provide better solution of scheduling task that means combination of different scheduling provides better performance without degrading the result quality. Scheduling algorithms such as MinMin+, MaxMin+ and Sufferage+ are suitable for overcomes the drawback of previously used scheduling methods such as MinMin, MaxMin and Sufferage as well as scheduling in this paper provides better complexity as compare to previous scheduling methods. This scheduling are also suitable for heterogeneous environment more effectively to execute different set of task on different processors with different configurations. To get better the show of the existing system we have to improve existing algorithm with the load balancing.So same load should overloaded to all processors.The future algorithm have implement with detailed pseudocodes.

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Section: Load Balancing In Distributed Systemmentioning

confidence: 99%

Scheduling Tasks in Heterogeneous System using Load Balancing Algorithm

Patil¹,

Ade²

2017

IJCA

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“…Several strategies are proposed to distribute the load using dynamic and distributed load balancing mechanisms, called sender-initiated and receiver-initiated strategies. In the sender-initiated strategy, a portion of the load of over-loaded processor is sent to another computing node [2]. In receiver-initiated strategy, the under-loaded processor initiates the transaction by sending a message to other nodes [6].…”

Section: Related Researchesmentioning

confidence: 99%

Adaptive Load Balancing Dashboard in Dynamic Distributed Systems

Mirtaheri

Fatemi

Grandinetti

2017

JSFI

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Considering the dynamic nature of new generation scientific problems, load balancing is a necessity to manage the load in an efficient manner. Load balancing systems are used to optimize the resource consumption, maximize the throughput, minimize response time, and to prevent overload in resources. In current research, we consider operational distributed systems with dynamic variables caused by different nature of the applications and heterogeneity of the various levels in the system. The conducted studies indicate that many different factors should be considered to select the load balancing algorithm, including the processing power, load transfer and communication delay of nodes. In this work, We aim to design a dashboard that is capable of merging the load balancing algorithms in different environments. We design an adaptive system infrastructure with the ability to adjust various factors in the run time of a load balancing algorithm. We propose a task and a resource allocation mechanism and further introduce a mathematical model of load balancing process in the system. We calculate a normalized hardware score that determines the maturity of the system according to the environmental conditions of the load balancing process. The evaluation results confirm that the proposed method performs well and reduces the probability of system failure.

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“…The goal of all load balancing solutions is to evenly distribute workload to all available resources [4], [23]. In addition, strategy and method of load balancing will directly affect the performance of the network system.…”

Section: Load Balancing and Replicationmentioning

confidence: 99%

Community-Based Event Dissemination with Optimal Load Balancing

Xia

Ahmed

Yang

et al. 2015

IEEE Trans. Comput.

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Distributed publish/subscribe systems are poised with challenges of performance degradation and poor scalability. This is typically caused by an uneven load distribution of real-world applications and the susceptibility of link failure in networks. Partitioning and replication techniques have been implemented by exploring community-based load balancing to cope with such issues. The novel approach herein exploits offloading at the inter-community level as well as filter replication at the intra-community level. This results in the dynamic distribution and forwarding of publication and subscription services among brokers during run time. The proposed method, Co-Lab (COmmunity-based LoAd Balancing), seeks to improve the network performance by clustering brokers in a community by taking into consideration interest similarity and filter replication. It attempts to effectively achieve a more consistent and uniform load distribution among brokers and to circumvent the occurrence of highly overloaded brokers. Performance evaluations indicate that Co-Lab has promising advantages by achieving relatively better load balance, reduced overall load and robustness against failures.

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Performance-Driven Load Balancing with a Primary-Backup Approach for Computational Grids with Low Communication Cost and Replication Cost

Cited by 46 publications

References 40 publications

Scheduling Tasks in Heterogeneous System using Load Balancing Algorithm

Scheduling Tasks in Heterogeneous System using Load Balancing Algorithm

Adaptive Load Balancing Dashboard in Dynamic Distributed Systems

Community-Based Event Dissemination with Optimal Load Balancing

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