Fault Tolerance Based Load Balancing Approach for Web Resources in Cloud Environment

Fault Tolerance Based Load Balancing

Approach for Web Resources in Cloud Environment

Anju Shukla, Shishir Kumar, and Harikesh Singh

Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, India

Abstract: Cloud computing consists group of heterogeneous resources scattered around the world connected through the network. Since high performance computing is strongly interlinked with geographically distributed service to interact with each other in wide area network, Cloud computing makes the architecture consistent, low-cost, and well-suited with concurrent services. This paper presents a fault tolerance load balancing technique based on resource load and fault index value. The proposed technique works in two phases: resource selection and task execution. The resource selection phase selects the suitable resource for task execution. A resource with least resource load and fault index value is selected for task execution. Further task execution phase sets checkpoints at various intervals for saving the task state periodically. The checkpoints are set at various intervals based on resource fault index. When a task is executed on a resource, fault index value of selected resource is updated accordingly. This reduces the checkpoint overhead by avoiding unnecessary placements of checkpoints. The proposed model is validated on CloudSim and provides improved performance in terms of response time, makespan, throughput and checkpoint overhead in comparison to other state-of-the-art methods.

Keywords: Scheduler, checkpoint manager, cloud computing, checkpointing, fault index, high performance computing.

Received June 6, 2018; accepted July 2, 2019
https://doi.org/10.34028/iajit/17/2/10

Full text      

Read 1354 times Last modified on Wednesday, 26 February 2020 05:50
Share
Top
We use cookies to improve our website. By continuing to use this website, you are giving consent to cookies being used. More details…