@Article{csse.2021.016683,
AUTHOR = {Donglei Lu, Dongjie Zhu, Yundong Sun, Haiwen Du, Xiaofang Li, Rongning Qu, Yansong Wang, Ning Cao, Helen Min Zhou},
TITLE = {Exploration on the Load Balancing Technique for Platform of Internet of Things},
JOURNAL = {Computer Systems Science and Engineering},
VOLUME = {38},
YEAR = {2021},
NUMBER = {3},
PAGES = {339--350},
URL = {http://www.techscience.com/csse/v38n3/42581},
ISSN = {},
ABSTRACT = {In recent years, the Internet of Things technology has developed rapidly, and smart Internet of Things devices have also been widely popularized. A large amount of data is generated every moment. Now we are in the era of big data in the Internet of Things. The rapid growth of massive data has brought great challenges to storage technology, which cannot be well coped with by traditional storage technology. The demand for massive data storage has given birth to cloud storage technology. Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems. Therefore, it is of great practical significance to study how to improve the performance and resource utilization of cloud storage systems through load balancing technology. On the basis of studying the read strategy of Swift, this article proposes a reread strategy based on load balancing of storage resources to solve the problem of unbalanced read load between interruptions caused by random data copying in Swift. The storage asynchronously tracks the I/O conversion to select the storage with the smallest load for asynchronous reading. The experimental results indicate that the proposed strategy can achieve a better load balancing state in terms of storage I/O utilization and CPU utilization than the random read strategy index of Swift.},
DOI = {10.32604/csse.2021.016683}
}