Abstract
Wireless Sensor Network (WSN) has been penetrating deeper into various commercial monitoring services/application which demands substantial amount of residual energy to assure superior network lifetime. In this perspective, there are various Medium Access Control (MAC) as well as Carrier Sense Multiple Access (CSMA) scheme which is frequently adopted to address this problem; however, they too have shortcomings. Hence, this paper introduces a novel computational model of radio scheduling where a network model and neighborhood exploration are carried out using graph-based method. Further, the scheme introduces a novel management of routing to effectively control timeslots and message. Further, a simplified packet prioritization scheme is implemented balancing the demands of normal and urgent services. The simulation outcome shows that proposed scheme excels better data transmission performance in contrast to existing MAC and CSMA-based schemes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Naskar, S.: Wireless sensor networks challenges and solutions. In: Sen, P.J. (ed.), Wireless Sensor Networks - Research Issues and Effective Smart Solutions [Working Title]. IntechOpen (2023)
Eghonghon Ukhurebor, K., Odesanya, I., Soo Tyokighir, S., George Kerry, R., Samson Olayinka, A., Oluwafemi Bobadoye, A.: Wireless sensor networks: applications and challenges. In: Yellampalli, S.S. (ed.), Wireless Sensor Networks - Design, Deployment and Applications. IntechOpen (2021)
Li, J., Lv, J., Zhao, P., Sun, Y., Yuan, H., Xu, H.: Research and application of energy-efficient management approach for wireless sensor networks. Sensors (Basel, Switzerland) 23(3), 1567 (2023). https://doi.org/10.3390/s23031567
Evangelakos, E.A., Kandris, D., Rountos, D., Tselikis, G., Anastasiadis, E.: Energy sustainability in wireless sensor networks: an analytical survey. J. Low Power Electron. Appl. 12(4), 65 (2022). https://doi.org/10.3390/jlpea12040065
Bahadur, D.J., Lakshmanan, L.: A novel method for optimizing energy consumption in wireless sensor network using genetic algorithm. Microprocess. Microsyst. 96(104749), 104749 (2023). https://doi.org/10.1016/j.micpro.2022.104749
Kaur, L., Kaur, R.: A survey on energy efficient routing techniques in WSNs focusing IoT applications and enhancing fog computing paradigm. Glob. Trans. Proc. 2(2), 520–529 (2021). https://doi.org/10.1016/j.gltp.2021.08.001
Kumar, D.S., Saravana Sundaram, S., Prakash, S., Selvaperumal, S.: Effective aggregate data collection and enhanced network lifetime using energy efficient aggregation data convening routing in wireless sensor network. Wirel. Pers. Commun. (2023). https://doi.org/10.1007/s11277-023-10419-y
Pedditi, R.B., Debasis, K.: Energy efficient routing protocol for an IoT-based WSN system to detect forest fires. Appl. Sci. (Basel, Switzerland) 13(5), 3026 (2023). https://doi.org/10.3390/app13053026
Prasad, V.K.H., Periyasamy, S.: Energy optimization-based clustering protocols in wireless sensor networks and Internet of Things-survey. Int. J. Distrib. Sens. Netw. 2023, 1–18 (2023). https://doi.org/10.1155/2023/1362417
Abidoye, A.P., Kabaso, B.: Energy-efficient hierarchical routing in wireless sensor networks based on fog computing. EURASIP J. Wirel. Commun. Netw. 2021(1) (2021). https://doi.org/10.1186/s13638-020-01835-w
Rehman, A.U., et al.: A survey on MAC-based physical layer security over wireless sensor network. Electronics 11(16), 2529 (2022). https://doi.org/10.3390/electronics11162529
Raut, A.R., Khandait, S.P., Dongre, S.S.: Time-critical data transmission scheme in wireless sensor networks using machine learning approach. Int. J. Softw. Innov. 10(1), 1–11 (2022). https://doi.org/10.4018/ijsi.303586
Kaur, T., Kumar, D.: QoS mechanisms for MAC protocols in wireless sensor networks: a survey. IET Commun. 13(14), 2045–2062 (2019). https://doi.org/10.1049/iet-com.2018.5110
Abid, K., Lakhlef, H., Bouabdallah, A.: A survey on recent contention-free MAC protocols for static and mobile wireless decentralized networks in IoT. Comput. Netw. 201(108583), 108583 (2021). https://doi.org/10.1016/j.comnet.2021.108583
Afroz, F., Braun, R.: Energy-efficient MAC protocols for wireless sensor networks: a survey. Int. J. Sens. Netw. 32(3), 150 (2020). https://doi.org/10.1504/ijsnet.2020.105563
Mathew, K.D., Jones, A.: Survey: energy efficient protocols using radio scheduling in wireless sensor network. Int. J. Electr. Comput. Eng. (IJECE) 10(2), 1296 (2020). https://doi.org/10.11591/ijece.v10i2.pp1296-1307
Sakib, A.N., Drieberg, M., Sarang, S., Aziz, A.A., Hang, N.T.T., Stojanović, G.M.: Energy-aware QoS MAC protocol based on prioritized-data and multi-hop routing for wireless sensor networks. Sensors (Basel, Switzerland) 22(7), 2598 (2022). https://doi.org/10.3390/s22072598
Hai, T., Zhou, J., Padmavathy, T.V., Md, A.Q., Jawawi, D.N.A., Aksoy, M.: Design and validation of lifetime extension low latency MAC protocol (LELLMAC) for wireless sensor networks using a hybrid algorithm. Sustainability 14(23), 15547 (2022). https://doi.org/10.3390/su142315547
Tomovic, S., Radusinovic, I.: DR-ALOHA-Q: a Q-learning-based adaptive MAC protocol for underwater acoustic sensor networks. Sensors (Basel, Switzerland) 23(9), 4474 (2023). https://doi.org/10.3390/s23094474
Fu, X., Kim, J.G.: Deep-Q-network-based packet scheduling in an IoT environment. Sensors (Basel, Switzerland) 23(3), 1339 (2023). https://doi.org/10.3390/s23031339
Sarang, S., Stojanović, G.M., Drieberg, M., Stankovski, S., Bingi, K., Jeoti, V.: Machine learning prediction based adaptive duty cycle MAC protocol for solar energy harvesting wireless sensor networks. IEEE Access Pract. Innov. Open Solut. 11, 17536–17554 (2023). https://doi.org/10.1109/access.2023.3246108
Kherbache, M., Sobirov, O., Maimour, M., Rondeau, E., Benyahia, A.: Reinforcement learning TDMA-based MAC scheduling in the industrial internet of things: a survey. IFAC-PapersOnLine 55(8), 83–88 (2022). https://doi.org/10.1016/j.ifacol.2022.08.014
Miśkowicz, M.: Unfairness of random access with collision avoidance in industrial internet of things networks. Sensors (Basel, Switzerland) 21(21), 7135 (2021). https://doi.org/10.3390/s21217135
Su, H., Pan, M.-S., Chen, H., Liu, X.: MDP-based MAC protocol for WBANs in edge-enabled eHealth systems. Electronics 12(4), 947 (2023). https://doi.org/10.3390/electronics12040947
C, T., MG, J.: An enhancement for IEEE 802.11p to provision quality of service with context aware channel access for the forward collision avoidance application in vehicular ad hoc network. Sensors (Basel, Switzerland) 21(20), 6937 (2021). https://doi.org/10.3390/s21206937
Khun, A.T.P., Shan, L., Lim, Y., Tan, Y.: MCST scheme for UAV systems over LoRa networks. Drones 7(6), 371 (2023). https://doi.org/10.3390/drones7060371
Sadeq, A.S., Hassan, R., Sallehudin, H., Aman, A.H.M., Ibrahim, A.H.: Conceptual framework for future WSN-MAC protocol to achieve energy consumption enhancement. Sensors (Basel, Switzerland) 22(6) (2022). https://doi.org/10.3390/s22062129
Zhang, H., Wang, F.: MAC protocol analysis for wireless sensor networks. J. Inf. Technol. Res. 15(1), 1–12 (2022). https://doi.org/10.4018/jitr.298617
Uthayakumar, G.S., Dappuri, B., Vanitha, M., Suganthi, R., Savithiri, V., Kamatchi, S.: Design criteria for enhanced energy constraint MAC protocol for WSN. Meas. Sens. 25(100642), 100642 (2023). https://doi.org/10.1016/j.measen.2022.100642
Pradhan, N., Chaudhari, B.S.: Traffic-aware autonomous scheduling for 6TiSCH networks. Int. J. Comput. Appl. 44(11), 1039–1046 (2022). https://doi.org/10.1080/1206212x.2022.2103889
Subramanyam, R., Bala, G.J., Perattur, N., Kanaga, E.G.M.: Energy efficient MAC with variable duty cycle for wireless sensor networks. Int. J. Electron. 109(3), 367–390 (2022). https://doi.org/10.1080/00207217.2021.1892202
Thippun, P., Sasiwat, Y., Buranapanichkit, D., Booranawong, A., Jindapetch, N., Saito, H.: Implementation and experimental evaluation of dynamic capabilities in wireless body area networks: different setting parameters and environments. J. Eng. Appl. Sci. 70(1) (2023). https://doi.org/10.1186/s44147-022-00171-8
Khalifeh, A., Tanash, R., AlQudah, M., Al-Agtash, S.: Enhancing energy efficiency of IEEE 802.15.4- based industrial wireless sensor networks. J. Ind. Inf. Integr. 33(100460), 100460 (2023). https://doi.org/10.1016/j.jii.2023.100460
Nisha, N., Manikandan, A., Venkataramanan, C., Dhanapal, R.: A score based link delay aware routing protocol to improve energy optimization in wireless sensor network. J. Eng. Res. 100115, 100115 (2023). https://doi.org/10.1016/j.jer.2023.100115
Zhong, C., Springer, A.: Design and evaluation of innovative protocols for LoRa. IET Wirel. Sens. Syst. 12(1), 12–20 (2022). https://doi.org/10.1049/wss2.12033
Mathew, K.D., Jones, A.: CSRS-MAC: cluster based synchronous radio scheduling MAC protocol using carrier sense multiple access for wireless sensor network. Wirel. Pers. Commun. 126(1), 209–229 (2022). https://doi.org/10.1007/s11277-022
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Mathew, K.D., Mary Pushpa, T.A.J. (2024). Novel Radio Scheduling Framework for Optimal Energy Efficiency in Wireless Sensor Network. In: Silhavy, R., Silhavy, P. (eds) Software Engineering Methods in Systems and Network Systems. CoMeSySo 2023. Lecture Notes in Networks and Systems, vol 909. Springer, Cham. https://doi.org/10.1007/978-3-031-53549-9_17
Download citation
DOI: https://doi.org/10.1007/978-3-031-53549-9_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-53548-2
Online ISBN: 978-3-031-53549-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)