- Title
- Adaptive transmission optimization in SDN-based industrial internet of things with edge computing
- Creator
- Li, Xiaomin; Li, Di; Wan, Jiafu; Liu, Chengliang; Imran, Muhammad
- Date
- 2018
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185414
- Identifier
- vital:16670
- Identifier
-
https://doi.org/10.1109/JIOT.2018.2797187
- Identifier
- ISBN:2327-4662 (ISSN)
- Abstract
- In recent years, smart factory in the context of Industry 4.0 and industrial Internet of Things (IIoT) has become a hot topic for both academia and industry. In IIoT system, there is an increasing requirement for exchange of data with different delay flows among different smart devices. However, there are few studies on this topic. To overcome the limitations of traditional methods and address the problem, we seriously consider the incorporation of global centralized software defined network (SDN) and edge computing (EC) in IIoT with EC. We propose the adaptive transmission architecture with SDN and EC for IIoT. Then, according to data streams with different latency constrains, the requirements can be divided into two groups: 1) ordinary and 2) emergent stream. In the low-deadline situation, a coarse-grained transmission path algorithm provided by finding all paths that meet the time constrains in hierarchical Internet of Things (IoT). After that, by employing the path difference degree (PDD), an optimum routing path is selected considering the aggregation of time deadline, traffic load balances, and energy consumption. In the high-deadline situation, if the coarse-grained strategy is beyond the situation, a fine-grained scheme is adopted to establish an effective transmission path by an adaptive power method for getting low latency. Finally, the performance of proposed strategy is evaluated by simulation. The results demonstrate that the proposed scheme outperforms the related methods in terms of average time delay, goodput, throughput, PDD, and download time. Thus, the proposed method provides better solution for IIoT data transmission. © 2018 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Internet of Things Journal Vol. 5, no. 3 (2018), p. 1351-1360
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2018 IEEE
- Subject
- 40 Engineering; 46 Information and computing sciences; Adaptive routing; edge computing (EC); industrial Internet of Things (IIoT); software-defined network
- Reviewed
- Funder
- This work was supported in part by the National Natural Science Foundations of China under Grant 51575194, in part by the Key Program of Natural Science Foundation of Guangdong Province, China, under Grant 2017B030311008, and in part by the National Key Research and Development Project under Grant 2017YFE0101000. The work of M. Imran was supported by the Deanship of Scientific Research at King Saud University through Research Group No. (RG # 1435-051).
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