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Energy capable protocol for heterogeneous blue brain network

Year 2024, Volume: 8 Issue: 1, 152 - 161, 19.01.2024
https://doi.org/10.31127/tuje.1346925

Abstract

The Blue Brain has a wide range of applications, which raises a number of challenging issues. Electronics may continuously monitor their surroundings depending on the real data that their Blue Brain nodes are acquiring by employing situational intelligence based on the Blue Brain environment. The Blue Brain does more than only monitor user behavior when utilizing this technology. Blue Brain is linked to a critical prerequisite for energy-efficient communication methodologies. Through the Blue Brain network, it utilizes the heterogeneity and variety of the interconnected components. Blue Brain nodes that are outsourced and have limited energy resources must utilize less energy. IoT nodes with differing energy levels are frequently dispersed across different geographic regions. The main goal of this work is to provide an energy-efficient Blue Brain framework capable of managing cluster head (CH) selection and Blue Brain node clustering. The appropriate CHs are selected, and an energetic cutoff concept is developed to guarantee that energy is shared equally among the CHs and participating Blue Brain nodes. The proposed concept envisions three different kinds of Blue Brain nodes for a Blue Brain infrastructure: expert, intermediary, and normal Blue Brain nodes. Level 1 Blue Brain nodes are regarded as normal nodes; level 2 nodes are regarded as intermediate Blue Brain nodes; and level 3 nodes are regarded as expert Blue Brain nodes. Level 1 Blue Brain nodes use the least amount of energy. The outcomes of the simulation demonstrate that the recommended strategy outperforms other existing methods.

References

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  • Huang, Y., Yu, W., Ding, E., & Garcia-Ortiz, A. (2019). EPKF: Energy efficient communication schemes based on Kalman filter for IoT. IEEE Internet of Things Journal, 6(4), 6201-6211. https://doi.org/10.1109/JIOT.2019.2900853
  • Kiruba, D. G., & Benitha, J. (2022). Fuzzy Based Energy Proficient Secure Clustered Routing (FEPSRC) for IOT-MWSN. Journal of Intelligent and Fuzzy Systems. 43(6),7633–7645. https://doi.org/10.3233/JIFS-212014
  • Alhakbani, N., Hassan, M. M., Ykhlef, M., & Fortino, G. (2019). An efficient event matching system for semantic smart data in the Internet of Things (IoT) environment. Future Generation Computer Systems, 95, 163-174. https://doi.org/10.1016/j.future.2018.12.064
  • Kiruba, D. G., & Benita, J. (2022). A survey of secured cluster head: SCH based routing scheme for IOT based mobile wireless sensor network. ECS Transactions, 107(1), 16725. https://doi.org/10.1149/10701.16725ecst
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  • Mitton, N., Costa, L. H. M., Krishnamachari, B., Pecorella, T., Tahiliani, M., & Puech, N. (2020). Green data collection and processing in smart cities. Annals of Telecommunications, 75, 269-270. https://doi.org/10.1007/s12243-020-00773-4
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  • Rajab, A. D. (2022). Energy-Efficient Static Data Collector-based Scheme in Smart Cities. Computers, Materials & Continua, 72, 2077-2092. https://doi.org/10.32604/cmc.2022.025736
  • Al-Kaseem, B. R., Taha, Z. K., Abdulmajeed, S. W., & Al-Raweshidy, H. S. (2021). Optimized energy–efficient path planning strategy in WSN with multiple mobile sinks. IEEE Access, 9, 82833-82847. https://doi.org/10.1109/ACCESS.2021.3087086
  • Justus, J. J. & Thirunavukkarasan, M., Dhayalini, K., Visalaxi, G., Khelifi, A., Elhoseny, M. (2022). Type ii fuzzy logic based cluster head selection for wireless sensor network. Computers, Materials & Continua, 70(1), 801–816. https://doi.org/10.32604/cmc.2022.019122
  • Xie, Q., Li, K., Tan, X., Han, L., Tang, W., & Hu, B. (2021). A secure and privacy-preserving authentication protocol for wireless sensor networks in smart city. EURASIP Journal on Wireless Communications and Networking, 2021(1), 1-17. https://doi.org/10.1186/s13638-021-02000-7
  • Sivaram, M., Porkodi, V., Mohammed, A. S., & Karuppusamy, S. A. (2021). Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm. Recent Patents on Engineering, 15(2), 161-168. https://doi.org/10.2174/1872212114999200616164642
  • Gupta, P., Tripathi, S., & Singh, S. (2021). RDA-BWO: hybrid energy efficient data transfer and mobile sink location prediction in heterogeneous WSN. Wireless Networks, 27, 4421-4440. https://doi.org/10.1007/s11276-021-02678-z
  • Kamarei, M., Patooghy, A., Shahsavari, Z., & Salehi, M. J. (2020). Lifetime expansion in WSNs using mobile data collector: A learning automata approach. Journal of King Saud University-Computer and Information Sciences, 32(1), 65-72. https://doi.org/10.1016/j.jksuci.2018.03.006
  • Osamy, W., Khedr, A. M., El-Sawy, A. A., Salim, A., & Vijayan, D. (2021). IPDCA: intelligent proficient data collection approach for IoT-enabled wireless sensor networks in smart environments. Electronics, 10(9), 997. https://doi.org/10.3390/electronics10090997
  • Dande, B., Chen, S. Y., Keh, H. C., Yang, S. J., & Roy, D. S. (2021). Coverage-aware recharging scheduling using mobile charger in wireless sensor networks. IEEE Access, 9, 87318-87331. https://doi.org/10.1109/ACCESS.2021.3088524
  • Gharaei, N., Al-Otaibi, Y. D., Butt, S. A., Malebary, S. J., Rahim, S., & Sahar, G. (2020). Energy-efficient tour optimization of wireless mobile chargers for rechargeable sensor networks. IEEE Systems Journal, 15(1), 27-36. https://do.org/10.1109/JSYST.2020.2968968
  • Choi, H. H., & Lee, K. (2021). Cooperative wireless power transfer for lifetime maximization in wireless multihop networks. IEEE Transactions on Vehicular Technology, 70(4), 3984-3989. https://doi.org/10.1109/TVT.2021.3068345
Year 2024, Volume: 8 Issue: 1, 152 - 161, 19.01.2024
https://doi.org/10.31127/tuje.1346925

Abstract

References

  • Rajesh, D., & Kiruba, D. G. (2021). A probability based energy competent cluster based secured ch selection routing EC2SR protocol for smart dust. Peer-to-Peer Networking and Applications, 14(4), 1976-1987. https://doi.org/10.1007/s12083-021-01144-z
  • Škulj, G., Sluga, A., Bračun, D., & Butala, P. (2019). Energy efficient communication based on self-organisation of IoT devices for material flow tracking. CIRP annals, 68(1), 495-498. https://doi.org/10.1016/j.cirp.2019.03.012
  • Huang, Y., Yu, W., Ding, E., & Garcia-Ortiz, A. (2019). EPKF: Energy efficient communication schemes based on Kalman filter for IoT. IEEE Internet of Things Journal, 6(4), 6201-6211. https://doi.org/10.1109/JIOT.2019.2900853
  • Kiruba, D. G., & Benitha, J. (2022). Fuzzy Based Energy Proficient Secure Clustered Routing (FEPSRC) for IOT-MWSN. Journal of Intelligent and Fuzzy Systems. 43(6),7633–7645. https://doi.org/10.3233/JIFS-212014
  • Alhakbani, N., Hassan, M. M., Ykhlef, M., & Fortino, G. (2019). An efficient event matching system for semantic smart data in the Internet of Things (IoT) environment. Future Generation Computer Systems, 95, 163-174. https://doi.org/10.1016/j.future.2018.12.064
  • Kiruba, D. G., & Benita, J. (2022). A survey of secured cluster head: SCH based routing scheme for IOT based mobile wireless sensor network. ECS Transactions, 107(1), 16725. https://doi.org/10.1149/10701.16725ecst
  • Vankadara, S., & Dasari, N. (2020). Energy‐aware dynamic task offloading and collective task execution in mobile cloud computing. International Journal of Communication Systems, 33(13), e3914. https://doi.org/10.1002/dac.3914
  • Kiruba, G. (2022). A comparative study on energy efficient secured clustered approaches for IOT based MWSN. Suranaree Journal of Science & Technology, 29(4), 010151
  • Mitton, N., Costa, L. H. M., Krishnamachari, B., Pecorella, T., Tahiliani, M., & Puech, N. (2020). Green data collection and processing in smart cities. Annals of Telecommunications, 75, 269-270. https://doi.org/10.1007/s12243-020-00773-4
  • Kiruba, G. B. (2021). Energy capable clustering method for extend the duration of IoT based mobile wireless sensor network with remote nodes. Energy Harvesting and Systems, 8(1), 55-61. https://doi.org/10.1515/ehs-2021-0006
  • Rajab, A. D. (2022). Energy-Efficient Static Data Collector-based Scheme in Smart Cities. Computers, Materials & Continua, 72, 2077-2092. https://doi.org/10.32604/cmc.2022.025736
  • Al-Kaseem, B. R., Taha, Z. K., Abdulmajeed, S. W., & Al-Raweshidy, H. S. (2021). Optimized energy–efficient path planning strategy in WSN with multiple mobile sinks. IEEE Access, 9, 82833-82847. https://doi.org/10.1109/ACCESS.2021.3087086
  • Justus, J. J. & Thirunavukkarasan, M., Dhayalini, K., Visalaxi, G., Khelifi, A., Elhoseny, M. (2022). Type ii fuzzy logic based cluster head selection for wireless sensor network. Computers, Materials & Continua, 70(1), 801–816. https://doi.org/10.32604/cmc.2022.019122
  • Xie, Q., Li, K., Tan, X., Han, L., Tang, W., & Hu, B. (2021). A secure and privacy-preserving authentication protocol for wireless sensor networks in smart city. EURASIP Journal on Wireless Communications and Networking, 2021(1), 1-17. https://doi.org/10.1186/s13638-021-02000-7
  • Sivaram, M., Porkodi, V., Mohammed, A. S., & Karuppusamy, S. A. (2021). Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm. Recent Patents on Engineering, 15(2), 161-168. https://doi.org/10.2174/1872212114999200616164642
  • Gupta, P., Tripathi, S., & Singh, S. (2021). RDA-BWO: hybrid energy efficient data transfer and mobile sink location prediction in heterogeneous WSN. Wireless Networks, 27, 4421-4440. https://doi.org/10.1007/s11276-021-02678-z
  • Kamarei, M., Patooghy, A., Shahsavari, Z., & Salehi, M. J. (2020). Lifetime expansion in WSNs using mobile data collector: A learning automata approach. Journal of King Saud University-Computer and Information Sciences, 32(1), 65-72. https://doi.org/10.1016/j.jksuci.2018.03.006
  • Osamy, W., Khedr, A. M., El-Sawy, A. A., Salim, A., & Vijayan, D. (2021). IPDCA: intelligent proficient data collection approach for IoT-enabled wireless sensor networks in smart environments. Electronics, 10(9), 997. https://doi.org/10.3390/electronics10090997
  • Dande, B., Chen, S. Y., Keh, H. C., Yang, S. J., & Roy, D. S. (2021). Coverage-aware recharging scheduling using mobile charger in wireless sensor networks. IEEE Access, 9, 87318-87331. https://doi.org/10.1109/ACCESS.2021.3088524
  • Gharaei, N., Al-Otaibi, Y. D., Butt, S. A., Malebary, S. J., Rahim, S., & Sahar, G. (2020). Energy-efficient tour optimization of wireless mobile chargers for rechargeable sensor networks. IEEE Systems Journal, 15(1), 27-36. https://do.org/10.1109/JSYST.2020.2968968
  • Choi, H. H., & Lee, K. (2021). Cooperative wireless power transfer for lifetime maximization in wireless multihop networks. IEEE Transactions on Vehicular Technology, 70(4), 3984-3989. https://doi.org/10.1109/TVT.2021.3068345
There are 21 citations in total.

Details

Primary Language English
Subjects Network Engineering
Journal Section Articles
Authors

Rajesh Dennison 0000-0002-2079-4472

Giji Kiruba Dasebenezer 0000-0001-9705-5099

Ramesh Dennison 0000-0002-2079-4472

Early Pub Date January 15, 2024
Publication Date January 19, 2024
Published in Issue Year 2024 Volume: 8 Issue: 1

Cite

APA Dennison, R., Dasebenezer, G. K., & Dennison, R. (2024). Energy capable protocol for heterogeneous blue brain network. Turkish Journal of Engineering, 8(1), 152-161. https://doi.org/10.31127/tuje.1346925
AMA Dennison R, Dasebenezer GK, Dennison R. Energy capable protocol for heterogeneous blue brain network. TUJE. January 2024;8(1):152-161. doi:10.31127/tuje.1346925
Chicago Dennison, Rajesh, Giji Kiruba Dasebenezer, and Ramesh Dennison. “Energy Capable Protocol for Heterogeneous Blue Brain Network”. Turkish Journal of Engineering 8, no. 1 (January 2024): 152-61. https://doi.org/10.31127/tuje.1346925.
EndNote Dennison R, Dasebenezer GK, Dennison R (January 1, 2024) Energy capable protocol for heterogeneous blue brain network. Turkish Journal of Engineering 8 1 152–161.
IEEE R. Dennison, G. K. Dasebenezer, and R. Dennison, “Energy capable protocol for heterogeneous blue brain network”, TUJE, vol. 8, no. 1, pp. 152–161, 2024, doi: 10.31127/tuje.1346925.
ISNAD Dennison, Rajesh et al. “Energy Capable Protocol for Heterogeneous Blue Brain Network”. Turkish Journal of Engineering 8/1 (January 2024), 152-161. https://doi.org/10.31127/tuje.1346925.
JAMA Dennison R, Dasebenezer GK, Dennison R. Energy capable protocol for heterogeneous blue brain network. TUJE. 2024;8:152–161.
MLA Dennison, Rajesh et al. “Energy Capable Protocol for Heterogeneous Blue Brain Network”. Turkish Journal of Engineering, vol. 8, no. 1, 2024, pp. 152-61, doi:10.31127/tuje.1346925.
Vancouver Dennison R, Dasebenezer GK, Dennison R. Energy capable protocol for heterogeneous blue brain network. TUJE. 2024;8(1):152-61.
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