Custom Network Protocol Stack for Communication Between Nodes in a Cloudlet System
Pages 1 - 24
Abstract
With the advent of internet of things (IoT), new network paradigms have emerged. One such technology is cloudlets. Cloudlets are being increasingly used in various IoT-based applications such as smart homes, smart cities, healthcare, and industrial automations. Cloudlets have an advantage of proximity to the end-device while offering services similar to the cloud. Existing cloudlets use IEEE 802.11 for communication between nodes. In this paper, the authors present a protocol customized for usage in cloudlets, which also considers various limitations of the node that constitute the cloudlet. The nodes on the cloudlet are generally constrained in terms of power and memory when compared to nodes on a cloud. The custom protocol also incorporates fault-tolerance, time synchronization, and factors such as task affinities for communication. The protocol proposed in this paper gave an excellent packet delivery ratio, the lowest being 91% even with increased bandwidth usage when compared to IEEE 802.11.
References
[1]
About NS2 v2.35. (n.d.). Information sciences institute. Retrieved September 19, 2023, from https://www.isi.edu/nsnam/ns/edu/index.html
[2]
Ali, A., Ming, Y., Chakraborty, S., & Iram, S. (2017). A comprehensive survey on real-time applications of WSN. Future Internet, 9(4), 77.
[3]
Alkenani, J., & Nassar, K. A. (2022). Enhanced system for ns2 trace file analysis with network performance evaluation. Iraqi Journal of Intelligent Computing and Informatics, 1(2), 119–130.
[4]
Babar, M., Khan, M. S., Ali, F., Imran, M., & Shoaib, M. (2021). Cloudlet computing: Recent advances, taxonomy, and challenges. IEEE Access : Practical Innovations, Open Solutions, 9, 29609–29622.
[5]
Basic Kit for DragonBoard-410c. (n.d.). 96 Boards. Retrieved October 19, 2023, from https://www.96boards.org/documentation/consumer/dragonboard/dragonboard410c/getting-started/basic-kit/
[6]
Cao, K., Liu, Y., Meng, G., & Sun, Q. (2020). An overview on edge computing research. IEEE Access : Practical Innovations, Open Solutions, 8, 85714–85728.
[7]
DragonBoard 820c Hardware Documentation. (n.d.). 96 Boards. Retrieved October 19, 2023, from https://www.96boards.org/documentation/consumer/dragonboard/dragonboard820c/hardware-docs/
[8]
Fernández-Caramés, T. M., Fraga-Lamas, P., Suárez-Albela, M., & Vilar-Montesinos, M. (2018). A fog computing and cloudlet based augmented reality system for the industry 4.0 shipyard. Sensors (Basel), 18(6), 1798. 29865266.
[9]
Galloway, B., & Hancke, G. P. (2012). Introduction to industrial control networks. IEEE Communications Surveys and Tutorials, 15(2), 860–880.
[10]
Jia, M., Cao, J., & Liang, W. (2015). Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Transactions on Cloud Computing, 5(4), 725–737.
[11]
Kakade, M. S., Karuppiah, A., Mathur, M., Bibekar, M., Basu, G., Raghavan, A., Raghav, A., & Lekshminarayanan, P. (2023). A completely distributed cloudlet framework using 410c SoC. In 2023 14th International Conference on Computing Communication and Networking Technologies (pp. 1–7). IEEE. 10.1109/ICCCNT56998.2023.10307503
[12]
Kakade, M. S., Karuppiah, A., Mathur, M., Bibekar, M., Basu, G., Raghavan, A., Raghav, A., Lekshminarayanan, P., & Garang, S. (2023). Multitask scheduling on distributed cloudlet system built using SoCs. Journal of Systemics, Cybernetics and Informatics, 21(1), 61–72.
[13]
Ketshabetswe, L. K., Zungeru, A. M., Mangwala, M., Chuma, J. M., & Sigweni, B. (2019). Communication protocols for wireless sensor networks: A survey and comparison. Heliyon, 5(5), e01591. Advance online publication. 31193432.
[14]
Khan, B. U. I., Olanrewaju, R. F., Anwar, F., Najeeb, A. R., & Yaacob, M. (2018). A survey on MANETs: Architecture, evolution, applications, security issues and solutions. Indonesian Journal of Electrical Engineering and Computer Science, 12(2), 832–842.
[15]
Khan, W. Z., Ahmed, E., Hakak, S., Yaqoob, I., & Ahmed, A. (2019). Edge computing: A survey. Future Generation Computer Systems, 97, 219–235.
[16]
Khanh, T. T., Nguyen, V., Pham, X. Q., & Huh, E. N. (2020). Wi-fi indoor positioning and navigation: A cloudlet-based cloud computing approach. Human-Centric Computing and Information Sciences, 10(1), 1–26.
[17]
Le, H. Q., Al-Shatri, H., & Klein, A. (2017). Efficient resource allocation in mobile-edge computation offloading: Completion time minimization. In 2017 IEEE international symposium on information theory. IEEE.
[18]
Lou, D., Holler, J., Patel, D., Graf, U., & Gillmore, M. (2021). The industrial internet of things networking framework. Industry IoT Consortium Networking Task Group. https://www.iiconsortium.org/wp-content/uploads/sites/2/2022/08/IINF_Update_2022_08_03.pdf
[19]
Ma, X., Lin, C., Zhang, H., & Liu, J. (2018). Energy-aware computation offloading of IoT sensors in cloudlet-based mobile edge computing. Sensors (Basel), 18(6), 1945. 29914104.
[20]
Malik, P. K., Sharma, R., Singh, R., Gehlot, A., Satapathy, S. C., Alnumay, W. S., Pelusi, D., Ghosh, U., & Nayak, J. (2021). Industrial internet of things and its applications in industry 4.0: State of the art. Computer Communications, 166, 125–139.
[21]
Munari, A., Clazzer, F., & Liva, G. (2015). Multi-receiver aloha systems-a survey and new results. In 2015 IEEE international conference on communication workshop. IEEE.
[22]
Pham, Q. V., Ruby, R., Fang, F., Nguyen, D. C., Yang, Z., Le, M., Ding, Z., & Hwang, W.-J. (2022). Aerial computing: A new computing paradigm, applications, and challenges. IEEE Internet of Things Journal, 9(11), 8339–8363.
[23]
Prajapati, A. G., Sharma, S. J., & Badgujar, V. S. (2018). All about cloud: A systematic survey. In 2018 international conference on smart city and emerging technology. IEEE.
[24]
Ramasubbareddy, S., & Sasikala, R. (2021). RTTSMCE: A response time aware task scheduling in multi-cloudlet environment. International Journal of Computers and Applications, 43(7), 691–696.
[25]
Ren, J., Zhang, D., He, S., Zhang, Y., & Li, T. (2019). A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet. ACM Computing Surveys, 52(6), 1–36.
[26]
Shaukat, U., Ahmed, E., Anwar, Z., & Xia, F. (2016). Cloudlet deployment in local wireless networks: Motivation, architectures, applications, and open challenges. Journal of Network and Computer Applications, 62, 18–40.
[27]
Snapdragon 888 Mobile Hardware Development Kit. (n.d.). Qualcomm Developer Network. Retrieved October 19, 2023, from https://developer.qualcomm.com/hardware/snapdragon-888-hdk
[28]
Tawalbeh, L. A., Jararweh, Y., Ababneh, F., & Dosari, F. (2015). Large scale cloudlets deployment for efficient mobile cloud computing. Journal of Networks, 10(1), 70–76.
[29]
Wang, W., Nešić, D., & Postoyan, R. (2015). Emulation-based stabilization of networked control systems implemented on FlexRay. Automatica, 59, 73–83.
[30]
Watt, S. T., Achanta, S., Abubakari, H., Sagen, E., Korkmaz, Z., & Ahmed, H. (2015). Understanding and applying precision time protocol. In 2015 Saudi Arabia smart grid. IEEE.
[31]
Xiang, L., & Shaobin, L. (2020). Hybrid cloud networking design based on Openstack architecture. In Journal of Physics: Conference Series (Vol. 1693, No. 1, p. 012011). IOP Publishing.
Index Terms
- Custom Network Protocol Stack for Communication Between Nodes in a Cloudlet System
Index terms have been assigned to the content through auto-classification.
Recommendations
A Multi-Cloudlet Infrastructure for Future Smart Cities: An Empirical Study
EdgeSys'18: Proceedings of the 1st International Workshop on Edge Systems, Analytics and NetworkingThe emerging paradigm of edge computing has proposed cloudlets to offload data and computations from mobile, resource-constrained devices. However, little attention has been paid to the question on where to deploy cloudlets in the context of smart city ...
Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing
Employing mobile cloud computing (MCC) to enable mobile users to acquire benefits of cloud computing by an environmental friendly method is an efficient strategy for meeting current industrial demands. However, the restrictions of wireless bandwidth and ...
Edge computing: A survey
AbstractIn recent years, the Edge computing paradigm has gained considerable popularity in academic and industrial circles. It serves as a key enabler for many future technologies like 5G, Internet of Things (IoT), augmented reality and ...
Highlights- A comprehensive survey on edge computing, i.e., Fog, Mobile-edge and Cloudlet.
- ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2024.
Publisher
IGI Global
United States
Publication History
Published: 09 April 2024
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 13 Nov 2024
Other Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in