A Multicloud-Model-Based Many-Objective Intelligent Algorithm for Efficient Task Scheduling in Internet of Things

被引:231
作者
Cai, Xingjuan [1 ]
Geng, Shaojin [1 ]
Wu, Di [1 ]
Cai, Jianghui [1 ]
Chen, Jinjun [2 ]
机构
[1] Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan 030024, Peoples R China
[2] Swinburne Univ Technol, Dept Comp Sci & Software Engn, Melbourne, NSW 3000, Australia
基金
中国国家自然科学基金;
关键词
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; SERVICES; WORKFLOW;
D O I
10.1109/JIOT.2020.3040019
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:9645 / 9653
页数:9
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