Abstract
In today’s Internet of Things (IoT) era, a wide range of wireless devices communicates together through wireless communication. Wi-Fi has been used for a large number of data transmissions due to its high range, high performance and universal IP accessibility. Wi-Fi is generally power consuming, and it may put a lot of stress on energy-constrained IoT devices and gateways. Conversely, ZigBee has now become a broadly used transmission technique in IoT because of its minimal price, low power consumption and ease of implementation. Many power saving management schemes have been designed to increase energy efficiency, but they do not perform well for all power constraint services. To deal with such situations, we have proposed an Energy-Efficient Scheduling (EES) using Wi-Fi and ZigBee and utilized the high transmission rate of Wi-Fi and low power consumption nature of ZigBee. While working on these two technologies of the same frequency band (2.4 GHz), we have resolved the interference problem using Interference Avoidance (IA) algorithm. Inet framework of Omnet++ simulator is used for the simulation. The implementation result shows a significant reduction in energy consumption on the device and gateway. In the presence of Wi-Fi, ZigBee functions better and the outcomes indicate better throughput while maintaining the energy consumption and interference level.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Availability of data and materials
No new data were generated or analyzed in support of this research
References
Shaikh FK, Zeadally S, Exposito E (2017) Enabling technologies for green Internet of Things. IEEE Syst J 11(2):983–994
Said O, Al-Makhadmeh Z, Tolba A (2020) EMS: an energy management scheme for green IoT environment. IEEE Access 8:44983–44998
Qin H, Cao B, He J, Xiao X, Chen W, Peng Y (2020) Cross-interface scheduling toward energy-efficient device-to-gateway communications in IoT. IEEE Internet Things J 7(3):2247–2262
Qin H, Chen W, Cao B, He J, Peng Y (2019) BCS: bidirectional cross-interface scheduling for sustainable end-to-end data delivery in IoT. IEEE Syst J 13(4):4146–4157
Qin H, Chen W, Cao B, Zeng M, Li J, Peng Y (2019) DIPS: dual-interface dual-pipeline scheduling for energy-efficient multihop communications in IoT. IEEE Internet Things J 6(1):718–733
Kumar S, Kim H (2019) Energy efficient scheduling in wireless sensor networks for periodic data gathering. IEEE Access 7:11410–11426
Ahmad A, Hanzalek Z (2020) An energy-efficient distributed TDMA scheduling algorithm for ZigBee-like cluster-tree WSNs. ACM Trans Sensor Netw 16(1):1–41
Kulkarni V, Sahoo SK (2018) A collaborative framework for avoiding interference between ZigBee and Wi-Fi for effective smart metering applications. Electron J 22(1):48–56
Tang M, Jin Y, Yao L (2017) Wi-Fi-ZigBee coexistence based on collision avoidance for wireless body area network. In: 2017 3rd International Conference on Big Data Computing and Communications (BIGCOM), Chengdu, China, pp 245–250
Wagh SS, More A, Kharote PR (2015) Performance evaluation of IEEE 802.15.4 protocol under coexistence of Wi-Fi 802.11b. Procedia Comput Sci 57:745–751
Zhai, Zhang R, Cai L, Li B, Jiang Y (2018) Energy-efficient user scheduling and power allocation for NOMA-based wireless networks with massive IoT devices. IEEE Internet Things J 5(3):1857–1868
Cho Y, Kim M, Woo S (2018) Energy efficient IoT based on wireless sensor networks. In: 20th International Conference on Advanced Communication Technology (ICACT), pp 294–299
Ko H, Lee J, Pack S (2017) Consistency-guaranteed and energy efficient sleep scheduling algorithm with data aggregation for IoT. In: 23th European Wireless Conference, pp 1–5
Sarangi SR, Goel S, Singh B (2018) Energy efficient scheduling in IoT networks. In: Proceedings of the 33rd Annual ACM Symposium on Applied Computing Association for Computing Machinery New York, vol 8, pp 733–740
Haseeb K, Almustafa KM, Jan Z, Saba T, Tariq U (2020) Secure and energy-aware heuristic routing protocol for wireless sensor network. IEEE Access 8:163962–163974
Bouachir O, Mnaouer AB, Touati F, Crescini D (2017) EAMP-AIDC—energy-aware mac protocol with adaptive individual duty cycle for EH-WSN. In: 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp 2021–2028
Aihara N, Adachi K, Takyu O, Ohta M, Fujii T (2020) Generalized interference detection scheme in heterogeneous low power wide area networks. IEEE Sens Lett, Artical number 7500504, 4(6):1–4
Memos VA, Psannis KE, Minopoulos G, Kokkonis G, Ishibashi Y (2019) An energy efficient scheme for IoT (EES4IoT). In: 2nd World Symposium on Communication Engineering (WSCE), pp 11–15
Lutui PR, Cusack B, Maeakafa G (2018) Energy efficiency for IoT devices in home environments. In: 2018 IEEE International Conference on Environmental Engineering (EE), pp 1–6
Gomaa NN, Youssef KY, Abouelatta M (2019) An IoT-based energy efficient system for industrial sector. In: 15th International Computer Engineering Conference (ICENCO), pp 132–137
Zhang, Zuo J, Mao W (2019) SmartWAZ: design and implementation of a smart Wi-Fi access system assisted by ZigBee, IEEE Access, 1–1
Guo X, He Y, Zheng X, Yu L, Gnawali O (2020) ZigFi: harnessing channel state information for cross-technology communication. IEEE/ACM Trans Netw 28(1):301–311
Li Z, He T (2017) WEBee: physical-layer cross-technology communication via emulation. In: Proceedings of ACM MobiCom, pp 493–494
Shao C, Park H, Roh H, Lee W, Kim H (2020) PolarScout: Wi-Fi interference-resilient ZigBee communication via shell-shaping. IEEE/ACM Trans Netw 28(4):1587–1600
Yang, Yan P, Li Y, Zhang X, Tao Y, Lizhao Y (2015) Taming cross-technology interference for WiFi and ZigBee coexistence networks. IEEE Trans Mobile Comput 15:1–1
Lu B, Qin Z, Sun Y, Hu J, Wang L (2018) A dynamic self-adapting mechanism for ZigBee performance assurance under Wi-Fi interference. IEEE Sens J 18(9):3900–3909
Nomura K, Sato F (2014) A performance study of ZigBee network under Wi-Fi interference. In: 17th International Conference on Network-Based Information Systems, Salerno, Italy, pp 201–207
Li F, Luo J, Shi G, He Y (2017) ART: adaptive frequency-temporal co-existing of ZigBee and WiFi. IEEE Trans Mobile Comput 16(3):662–674
Davoli L, Belli L, Cilfone A, Ferrari G (2018) From Micro to Macro IoT: Challenges and solutions in the integration of IEEE 802.15.4/802.11 and Sub-GHz technologies. IEEE Internet Things J 5(2):784–793
Funding
No funding was received for conducting this study.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Material preparation and analysis were performed by [Am]. [RK] has read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests to declare that are relevant to the content of this article.
Ethical approval
The submitted work is original and has not been submitted or published elsewhere in any form. The authors have submitted this manuscript in accordance with Springer journal policies on author responsibilities.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Malik, A., Kushwah, R. Energy-efficient scheduling in IoT using Wi-Fi and ZigBee cross-technology. J Supercomput 79, 10977–11006 (2023). https://doi.org/10.1007/s11227-023-05093-7
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11227-023-05093-7