Task Execution Efficiency Enrichment in Cloud Based Load Balancing Approaches

Author(s):  
Jay Patel ◽  
Chirag S. Thaker ◽  
Hardik Chaudhari
2019 ◽  
Vol 17 (2) ◽  
pp. 225-232 ◽  
Author(s):  
Anju Shukla ◽  
Shishir Kumar ◽  
Harikesh Singh

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.


Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


2003 ◽  
Vol 123 (10) ◽  
pp. 1847-1857
Author(s):  
Takahiro Tsukishima ◽  
Masahiro Sato ◽  
Hisashi Onari
Keyword(s):  

2014 ◽  
Vol 134 (8) ◽  
pp. 1104-1113
Author(s):  
Shinji Kitagami ◽  
Yosuke Kaneko ◽  
Hidetoshi Kambe ◽  
Shigeki Nankaku ◽  
Takuo Suganuma
Keyword(s):  

2013 ◽  
Vol 133 (4) ◽  
pp. 891-898
Author(s):  
Takeo Sakairi ◽  
Masashi Watanabe ◽  
Katsuyuki Kamei ◽  
Takashi Tamada ◽  
Yukio Goto ◽  
...  

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