Strategi Efisiensi Wireless Sensor Network (WSN)
Strategi Efisiensi Wireless Sensor Network (WSN)
Abstract
Abstrak: Wireless Sensor Network adalah teknologi yang berkembang pesat yang menawarkan potensi luar biasa untuk merevolusi banyak industri dan bidang. Wireless Sensor Network menjadi semakin populer karena keserbagunaannya, biaya yang rendah serta kemudahan dalam penerapannya. Terlepas dari keunggulan tersebut, masih ada beberapa tantangan yang perlu diatasi untuk mencapai kinerja tinggi dalam WSN yang terdistribusi secara total. Tujuan dari penelitian ini adalah menyajikan strategi ataupun solusi kepada user dalam kaitannya mencapai atau meningkatkan kinerja WSN yang berdampak pada keberhasilan pengumpulan data. Studi empiris dari peneliti-peneliti terkait menjadi metode pilihan yang digunakan.. Terdapat dua strategi yang diajukan untuk mencapai dan meningkatkan efisiensi WSN yaitu dengan pengoptimalan topologi jaringan sensor nirkabel dan memanfaatkan mode tidur. Adapun langkahnya dengan merencanakan penerapan node sensor, mengoptimalkan konsumsi energi melalui perutean yang efisien dan teknik agregasi data, mempertimbangkan skalabilitas dan lokalisasi, serta menggabungkan toleransi kesalahan dan ketahanan, jaringan dapat mencapai keseimbangan antara cakupan, konektivitas, efisiensi energi, dan ketahanan.Kata kunci: wireless sensor network, efisiensi, topologi jaringan, mode tidur jaringan.
Abstract: Wireless Sensor Networks are a rapidly evolving technology that offers tremendous potential to revolutionize many industries and fields. Wireless sensor networks are becoming increasingly popular because of their versatility, low cost and ease of implementation. Despite these advantages, there are still some challenges that need to be overcome to achieve high performance in a totally distributed WSN. The purpose of this study is to present strategies or solutions to users in relation to achieving or improving WSN performance which has an impact on the success of data collection. Empirical studies from related researchers are the method of choice used. There are two strategies proposed to achieve and improve WSN efficiency, namely by optimizing the wireless sensor network topology and utilizing sleep mode. The steps are by planning the implementation of sensor nodes, optimizing energy consumption through efficient routing and data aggregation techniques, considering scalability and localization, and combining fault tolerance and robustness, the network can achieve a balance between coverage, connectivity, energy efficiency, and resilience.
Keywords: wireless sensor network, efficiency, network topology, network sleep mode.
References
[1] Biljana Risteska Stojkoska, â€Nodes Localization in 3D Wireless Sensor Networks Based on Multidimensional Scaling Algorithm,†International Scholarly Research Notices, pp. 1-10. 2014. https://doi.org/10.1155/2014/845027
[2] Neng-Chung Wang, et al., “An Energy Efficient Load Balancing Tree-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks,†Sensors, vol. 22 no. 23. pp. 9303. 2022. https://doi.org/10.3390/s22239303
[3] Guoxi Ma and Zhengsu Tao, “A Hybrid Energy- and Time-Driven Cluster Head Rotation Strategy for Distributed Wireless Sensor Networks,†International Journal of Distributed Sensor Networks, vol. 13. 2013. http://dx.doi.org/10.1155/2013/109307
[4] Rohit D. Gawade and Sanjay L. Nalbalwar, “Mean Territorial Energy Based Clustering Protocol for Randomly Deployed Wireless Sensor Networks,†Advances in Internet of Things, vol 7, pp. 87-96. 2017. https://doi.org/10.4236/ait.2017.73006
[5] Yuling Zhang and and Wenwei He, “Cooperative Communication in Clustered Wireless Sensor Network Based on LDPC Codesâ€. 4th National Conference on Electrical, Electronics and Computer Engineering (NCEECE 2015). DOI: 10.2991/nceece-15.2016.203
[6] Annalisa Bertoli et al., “Smart Node Networks Orchestration: A New E2E Approach for Analysis and Design for Agile 4.0 Implementationâ€. Sensors, vol. 21. pp. 1624, 2021. https://doi.org/ 10.3390/s21051624
[7] Yuan Qiang et al., “An Efficient Cluster Head Selection Approach for Collaborative Data Processing in Wireless Sensor Networksâ€. International Journal of Distributed Sensor Networks, Vol 11, no. 6, June 2015. https://scite.ai/reports/10.1155/2015/794518
[8] Y. Yan, H. Wang, X. Shen and X. Zhong. "Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks". Sensors. vol. 15. no. 8. pp. 19157-19180. Aug. 2015. 10.3390/s150819157.
[9] Y. Yang, X. Zhang and X. Guo. "Study on Wireless Sensor Network Localization Technology Based on DV-Hop Algorithm". Jan. 2013. 10.2991/wiet-13.2013.42
[10] L. Jiang, X. Jin, Y. Xia, B. Ouyang, D. Wu and X. Chen. "A Scale-Free Topology Construction Model for Wireless Sensor Networks". Aug. 2014.
[11] Xi Ning, “Online Learning Platform for Air Environment Detection and Career Planning Based on 5G Networkâ€. Hindawi Mobile Information Systems, pp. 12. 2022. https://doi.org/10.1155/2022/9981624
[12] Feng, Yingying., Shasha Zhao and Hui Liu, (2020, 1 Januari). “Analysis of Network Coverage Optimization Based on Feedback K-Means Clustering and Artificial Fish Swarm Algorithm,†IEEE Access, vol. 8 pp. 42864 – 42876, January 2020. https://doi.org/10.1109/ACCESS.2020.2970208
[2] Neng-Chung Wang, et al., “An Energy Efficient Load Balancing Tree-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks,†Sensors, vol. 22 no. 23. pp. 9303. 2022. https://doi.org/10.3390/s22239303
[3] Guoxi Ma and Zhengsu Tao, “A Hybrid Energy- and Time-Driven Cluster Head Rotation Strategy for Distributed Wireless Sensor Networks,†International Journal of Distributed Sensor Networks, vol. 13. 2013. http://dx.doi.org/10.1155/2013/109307
[4] Rohit D. Gawade and Sanjay L. Nalbalwar, “Mean Territorial Energy Based Clustering Protocol for Randomly Deployed Wireless Sensor Networks,†Advances in Internet of Things, vol 7, pp. 87-96. 2017. https://doi.org/10.4236/ait.2017.73006
[5] Yuling Zhang and and Wenwei He, “Cooperative Communication in Clustered Wireless Sensor Network Based on LDPC Codesâ€. 4th National Conference on Electrical, Electronics and Computer Engineering (NCEECE 2015). DOI: 10.2991/nceece-15.2016.203
[6] Annalisa Bertoli et al., “Smart Node Networks Orchestration: A New E2E Approach for Analysis and Design for Agile 4.0 Implementationâ€. Sensors, vol. 21. pp. 1624, 2021. https://doi.org/ 10.3390/s21051624
[7] Yuan Qiang et al., “An Efficient Cluster Head Selection Approach for Collaborative Data Processing in Wireless Sensor Networksâ€. International Journal of Distributed Sensor Networks, Vol 11, no. 6, June 2015. https://scite.ai/reports/10.1155/2015/794518
[8] Y. Yan, H. Wang, X. Shen and X. Zhong. "Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks". Sensors. vol. 15. no. 8. pp. 19157-19180. Aug. 2015. 10.3390/s150819157.
[9] Y. Yang, X. Zhang and X. Guo. "Study on Wireless Sensor Network Localization Technology Based on DV-Hop Algorithm". Jan. 2013. 10.2991/wiet-13.2013.42
[10] L. Jiang, X. Jin, Y. Xia, B. Ouyang, D. Wu and X. Chen. "A Scale-Free Topology Construction Model for Wireless Sensor Networks". Aug. 2014.
[11] Xi Ning, “Online Learning Platform for Air Environment Detection and Career Planning Based on 5G Networkâ€. Hindawi Mobile Information Systems, pp. 12. 2022. https://doi.org/10.1155/2022/9981624
[12] Feng, Yingying., Shasha Zhao and Hui Liu, (2020, 1 Januari). “Analysis of Network Coverage Optimization Based on Feedback K-Means Clustering and Artificial Fish Swarm Algorithm,†IEEE Access, vol. 8 pp. 42864 – 42876, January 2020. https://doi.org/10.1109/ACCESS.2020.2970208
Published
2023-07-29
How to Cite
SAFIUDDIN, Safiuddin; PUTRA, Fauzan Prasetyo Eka.
Strategi Efisiensi Wireless Sensor Network (WSN).
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics, [S.l.], v. 8, n. 1, p. 52-56, july 2023.
ISSN 2548-3412.
Available at: <https://460290.0x60nl4us.asia/index.php/ITBI/article/view/2441>. Date accessed: 28 nov. 2024.
doi: https://doi.org/10.51211/itbi.v8i1.2441.
