CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Context-Adaptive Hybrid MAC Scheme for Provisioning QoS and Energy Savings in Delay Sensitive Wireless Sensor Network Application

by Kavya A.P., D.J. Ravi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 49
Year of Publication: 2023
Authors: Kavya A.P., D.J. Ravi
10.5120/ijca2023922614

Kavya A.P., D.J. Ravi . A Context-Adaptive Hybrid MAC Scheme for Provisioning QoS and Energy Savings in Delay Sensitive Wireless Sensor Network Application. International Journal of Computer Applications. 184, 49 ( Mar 2023), 40-45. DOI=10.5120/ijca2023922614

@article{ 10.5120/ijca2023922614,
author = { Kavya A.P., D.J. Ravi },
title = { A Context-Adaptive Hybrid MAC Scheme for Provisioning QoS and Energy Savings in Delay Sensitive Wireless Sensor Network Application },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2023 },
volume = { 184 },
number = { 49 },
month = { Mar },
year = { 2023 },
issn = { 0975-8887 },
pages = { 40-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number49/32638-2023922614/ },
doi = { 10.5120/ijca2023922614 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:24:26.070420+05:30
%A Kavya A.P.
%A D.J. Ravi
%T A Context-Adaptive Hybrid MAC Scheme for Provisioning QoS and Energy Savings in Delay Sensitive Wireless Sensor Network Application
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 49
%P 40-45
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An effective WSN communication protocol can help IoT applications to offer faster services in an efficient way. In order to reduce the energy consumptions various MAC protocols are introduced by the researchers based on duty cycle mechanism. However, none of the existing MAC protocols have been able to successfully balance the need for high power efficiency, low latency, and excellent QoS. A context-adaptive hybrid MAC (CA-HMAC) protocol is proposed in this paper for providing a higher degree of energy conservation under low traffic loads, and better transmission rates under high traffic loads. It presents hybrid scheduling algorithm to handle packet collisions, control idle listening, and conserve energy. The proposed protocol also focuses on adjusting power for packet transmission and data prioritization, followed by delay-aware routing mechanism. The design of the proposed MAC protocol is carried out in such a way that its response is faster towards executing its operation associated with duty cycle and packet transmission. The design and development of the proposed scheme is carried out on MATLAB tool. The experimental results show, that the proposed MAC protocol outperforms similar existing techniques in terms of throughput, remaining energy, and reduced packet delay.

References
  1. Fahmy, H. M. A. (2021). WSN applications. In Concepts, applications, experimentation, and analysis of wireless sensor networks (pp. 67-232). Springer, Cham.
  2. Sharma, R., Prakash, S., & Roy, P. (2020, February). Methodology, applications, and challenges of WSN-IoT. In 2020 International Conference on Electrical and Electronics Engineering (ICE3) (pp. 502-507). IEEE.
  3. Gulati, K., Boddu, R. S. K., Kapila, D., Bangare, S. L., Chandnani, N., & Saravanan, G. (2022). A review paper on wireless sensor network techniques in Internet of Things (IoT). Materials Today: Proceedings, 51, 161-165.
  4. Kaur, T., & Kumar, D. (2019). QoS mechanisms for MAC protocols in wireless sensor networks: a survey. IET Communications, 13(14), 2045-2062
  5. Singh, J., Kaur, R., & Singh, D. (2020). A survey and taxonomy on energy management schemes in wireless sensor networks. Journal of Systems Architecture, 111, 101782.
  6. Singh, D., Bhanipati, J., Biswal, A. K., Samanta, D., Joshi, S., Shukla, P. K., &Nuagah, S. J. (2021). Approach for collision minimization and enhancement of power allocation in WSNs. Journal of Sensors, 2021.
  7. Ezhilarasi, M., &Krishnaveni, V. (2018). A survey on wireless sensor network: energy and lifetime perspective. Taga Journal, 14(6), 41-48.
  8. Singh, D., &Singhai, J. (2015). Energy Conservation MAC Protocols with Low Duty Cycling for WSN: A Review. International Journal of Computer Applications, 975, 8887.
  9. Alfayez, F., Hammoudeh, M., &Abuarqoub, A. (2015). A survey on MAC protocols for duty-cycled wireless sensor networks. Procedia Computer Science, 73, 482-489.
  10. Maitra, T., & Roy, S. (2016). A comparative study on popular MAC protocols for mixed Wireless Sensor Networks: From implementation viewpoint. Computer Science Review, 22, 107-134.
  11. Ye, W.; Heidemann, J.; Estrin, D. An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the TwentyFirst Annual Joint Conference of the IEEE Computer and Communications Societies, New York, NY, USA, 23–27 June 2002; pp. 1567–1576
  12. Van Dam, T.; Langendoen, K. An adaptive energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 5–7 November 2003; pp. 171–180.
  13. Al-Janabi, T.A.; Al-Raweshidy, H.S. An Energy Efficient Hybrid MAC Protocol with Dynamic Sleep-Based Scheduling for High Density IoT Networks. IEEE Internet Things J. 2019, 6, 2273–2287.
  14. Zhao, L.; Guo, L.; Zhang, J.; Zhang, H. Game-theoretic medium access control protocol for wireless sensor networks. IET Commun. 2009, 3, 1274–1283.
  15. Doudou, M.; Barcelo-Ordinas, J.M.; Djenouri, D.; Garcia-Vidal, J.; Bouabdallah, A.; Badache, N. Game Theory Framework for MAC Parameter Optimization in Energy-Delay Constrained Sensor Networks. ACM Trans. Sens. Netw. 2016, 12, 1–35.
  16. Uchiteleva, E.; Shami, A.; Refaey, A. Time-varying keys for encryption in WSNs: IEEE CNS 17 poster. In Proceedings of the 2017 IEEE Conference on Communications and Network Security (CNS), Las Vegas, NV, USA, 9–11 October 2017; pp. 380–381.
  17. Collotta, M.; Pau, G.; Maniscalco, V. A Fuzzy Logic Approach by Using Particle Swarm Optimization for Effective Energy Management in IWSNs. IEEE Trans. Ind. Electron. 2017, 64, 9496–9506.
  18. Khamayseh, Y.M.; Mardini, W.; Halima, N.B. Evolutionary Algorithm for Scheduling in Wireless Sensor Networks. J. Comput. 2018, 13, 262–270.
  19. Caetano, M.F.; Makiuchi, M.R.; Fernandes, S.S.; Lamar, M.V.; Bordim, J.L.; Barreto, P.S. A recurrent neural network mac protocol towards to opportunistic communication in wireless networks. In Proceedings of the 2019 16th International Symposium on Wireless Communication Systems (ISWCS), Oulu, Finland, 27–30 August 2019; pp. 63–68.
  20. Xu, S.; Liu, P.; Wang, R.; Panwar, S.S. Realtime scheduling and power allocation using deep neural networks. In Proceedings of the 2019 IEEE Wireless Communications and Networking Conference (WCNC), Marrakesh, Morocco, 15–18 April 2019; pp. 1–5.
  21. Zhou, X.; Sun, M.; Li, G.Y.; Juang, B.H.F. Intelligent wireless communications enabled by cognitive radio and machine learning. China Commun. 2018, 15, 16–48.
Index Terms

Computer Science
Information Sciences

Keywords

Internet of Things Hybrid Medium Access Protocol Quality of Service Energy Efficiency

Powered by PhDFocusTM