Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 12, Pages 9645-9653Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3040019
Keywords
Cloud computing; Task analysis; Scheduling; Throughput; Internet of Things; Load modeling; Energy consumption; Internet of Things (IoT); many-objective intelligent algorithm; multicloud; sine function; task scheduling
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Funding
- National Natural Science Foundation of China [61806138, 61772478]
- Key Research and Development Program of Shanxi Province (High Technology) [201903D121119]
- Natural Science Foundation of Shanxi Province [201801D121127]
- Postgraduate Education Innovation Project of Shanxi Province [2020SY436]
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The rapid development of IoT leads to unprecedented data demand and security challenges. Multicloud platform, as a high-performance secure computing platform, can address data processing and security issues to some extent.
Internet of Things (IoT) is a huge network and establishes ubiquitous connections between smart devices and objects. The flourishing of IoT leads to an unprecedented data explosion, traditional data storing or processing techniques have the problem of low efficiency, and if the data are used maliciously, the security loss may be further caused. Multicloud is a high-performance secure computing platform, which combines multiple cloud providers for data processing, and the distributed multicloud platform ensures the security of data to some extent. Based on multicloud and task scheduling in IoT, this article constructs a many-objective distributed scheduling model, which includes six objectives of total time, cost, cloud throughput, energy consumption, resource utilization, and balancing load. Furthermore, this article presents a many-objective intelligent algorithm with sine function to implement the model, which considers the variation tendency of diversity strategy in the population is similar to the sine function. The experimental results demonstrate excellent scheduling efficiency and hence enhancing the security. This work provides a new idea for addressing the difficult problem of data processing in IoT.
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