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Scheduling internet of things applications in cloud computing

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Abstract

Internet of Things (IoT) is one of the greatest technology revolutions in the history. Due to IoT potential, daily objects will be consciously worked in harmony with optimized performances. However, today, technology is not ready to fully bring its power to our daily life because of huge data analysis requirements in instant time. On the other hand, the powerful data management of cloud computing gives IoT an opportunity to make the revolution in our life. However, the traditional cloud computing server schedulers are not ready to provide services to IoT because IoT consists of a number of heterogeneous devices and applications which are far away from standardization. Therefore, to meet the expectations of users, the traditional cloud computing server schedulers should be improved to efficiently schedule and allocate IoT requests. There are several proposed scheduling algorithms for cloud computing in the literature. However, these scheduling algorithms are limited because of considering neither heterogeneous servers nor dynamic scheduling approach for different priority requests. Our objective is to propose dynamic dedicated server scheduling for heterogeneous and homogeneous systems to efficiently provide desired services by considering priorities of requests. Results show that the proposed scheduling algorithm improves throughput up to 40 % in heterogeneous and homogeneous cloud computing systems for IoT requests. Our proposed scheduling algorithm and related analysis will help cloud service providers build efficient server schedulers which are adaptable to homogeneous and heterogeneous environments by considering system performance metrics, such as drop rate, throughput, and utilization in IoT.

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Acknowledgments

This research was supported in part by U.S. NSF grants NSF-1404981.

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Correspondence to Husnu S. Narman.

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Narman, H.S., Hossain, M.S., Atiquzzaman, M. et al. Scheduling internet of things applications in cloud computing. Ann. Telecommun. 72, 79–93 (2017). https://doi.org/10.1007/s12243-016-0527-6

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  • DOI: https://doi.org/10.1007/s12243-016-0527-6

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