Document Type : Research Article

Authors

Faculty of Engineering, Shahrekord University, Shahrekord, Iran.

10.22108/jcs.2021.129685.1072

Abstract

The Internet of Things (IoT) has provided a platform for different devices to interact extensively over the Internet. This technology produces a large amount of data that needs to be stored and processed in devices. On the other hand, hardware constraints on IoT devices pose a major challenge to energy consumption and latency. Edge Computing (EC) has brought many benefits as a promising solution to increase the computing and storage capacity of internet-connected devices. It is expected that EC helps IoT to reduce energy consumption and computational delay of devices. However, the conditions of the wireless channel and specifically the possibility of errors in data transmission over wireless links could have an adverse impact on the performance of the whole system. In this paper, by performing calculations in both local and edge environments and by considering the retransmission of data to eliminate possible errors, the role of wireless channels in the efficiency of offloading to the EC is investigated. The results show that offloading the calculations to EC does not always reduce energy consumption and delay. Therefore, the conditions of the wireless channel should be considered for an appropriate decision regarding the offloading of tasks to the EC or its execution in IoT devices.

Keywords

[1] M. Stoyanova, Y. Nikoloudakis, S. Panagiotakis, E. Pallis, and E. K. Markakis. A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues. IEEE Communications Surveys & Tutorials, 22(2):1191 -- 1221, 2020. [ bib | DOI ]
[2] L. Liu, Z. Chang, X. Guo, S. Mao, and T. Ristaniemi. Multiobjective Optimization for Computation Offloading in Fog Computing. IEEE Internet of Things Journal, 5(1):283 -- 294, 2017. [ bib | DOI ]
[3] C. Wang, F. R. Yu, C. Liang, Q. Chen, and L. Tang. Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing. IEEE Transactions on Vehicular Technology, 66(8):7432 -- 7445, 2017. [ bib | DOI ]
[4] Z. Ali, Z. H. Abbas, G. Abbas, A. Numani, and M. Bilal. Smart computational offloading for mobile edge computing in next-generation Internet of Things networks. Computer Networks, 198:108356, 2021. [ bib | DOI ]
[5] D. Liu, G. Zhu, J. Zhang, and K. Huang. Wireless Data Acquisition for Edge Learning: Importance-Aware Retransmission. In 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pages 1--5. IEEE, 2019. [ bib | DOI ]
[6] K. Cao, Y. Liu, G. Meng, and Q. Sun. An Overview on Edge Computing Research. IEEE Access, 8:85714 -- 85728, 2020. [ bib | DOI ]
[7] N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie. Mobile Edge Computing: A Survey. IEEE Internet of Things Journal, 5(1):450 -- 465, 2018. [ bib | DOI ]
[8] W. Yu, F. Liang, X. He, W. G. Hatcher, C. Lu, J. Lin, and X. Yang. A Survey on the Edge Computing for the Internet of Things. IEEE Access, 6:6900 -- 6919, 2017. [ bib | DOI ]
[9] Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief. A Survey on Mobile Edge Computing: The Communication Perspective. IEEE Communications Surveys & Tutorials, 19(4):2322 -- 2358, 2017. [ bib | DOI ]
[10] H. Lu, X. He, M. Du, X. Ruan, Y. Sun, and K. Wang. Edge QoE: Computation Offloading With Deep Reinforcement Learning for Internet of Things. IEEE Internet of Things Journal, 7(10):9255 -- 9265, 2020. [ bib | DOI ]
[11] X. Chen, J. Zhang, B. Lin, Z. Chen, K. Wolter, and G. Min. Energy-Efficient Offloading for DNN-Based Smart IoT Systems in Cloud-Edge Environments. IEEE Transactions on Parallel and Distributed Systems, 33(3):683 -- 697, 2021. [ bib | DOI ]
[12] W. Zhang, X. Li, L. Zhao, and X. Yang. Competition of Duopoly MVNOs for IoT Applications through Wireless Network Virtualization. Wireless Communications and Mobile Computing, 2020, 2020. [ bib | DOI ]
[13] W. Zhang, I. A. Elgendy, M. Hammad, A. M. Iliyasu, X. Du, M. Guizani, and A. A. Abd El-Latif. Secure and Optimized Load Balancing for Multitier IoT and Edge-Cloud Computing Systems. IEEE Internet of Things Journal, 8(10):8119 -- 8132, 2020. [ bib | DOI ]
[14] H. Zhang, Z. Zhang, L. Zhang, Y. Yang, Q. Kang, and D. Sun. Object Tracking for a Smart City Using IoT and Edge Computing. Sensors, 19(9):1987, 2019. [ bib | DOI ]
[15] D. Liu, G. Zhu, J. Zhang, and K. Huang. A Nested Two Stage Game-Based Optimization Framework in Mobile Cloud Computing System. In 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering, pages 494--502. IEEE, 2013. [ bib | DOI ]
[16] A. Goldsmith. Wireless Communications. Cambridge University Press, 2005. [ bib ]
[17] S. M. Ross. A First Course in Probability. Macmillan USA, 1988. [ bib ]
[18] L. Kleinrock. Queueing Systems. Volume 1: Theory. Wiley-Interscience, 1975. [ bib ]