TY  - JOUR
T1  - Energy capable protocol for heterogeneous blue brain network
AU  - Dennison, Rajesh
AU  - Dasebenezer, Giji Kiruba
AU  - Dennison, Ramesh
PY  - 2024
DA  - January
DO  - 10.31127/tuje.1346925
JF  - Turkish Journal of Engineering
JO  - TUJE
PB  - Murat YAKAR
WT  - DergiPark
SN  - 2587-1366
SP  - 152
EP  - 161
VL  - 8
IS  - 1
LA  - en
AB  - 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.
KW  - Blue Brain
KW  - Broadcasting
KW  - Energy
KW  - Cutoff
KW  - Heterogeneous network
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - Kiruba, G. (2022). A comparative study on energy efficient secured clustered approaches for IOT based MWSN. Suranaree Journal of Science & Technology, 29(4), 010151
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
CR  - 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
UR  - https://doi.org/10.31127/tuje.1346925
L1  - https://dergipark.org.tr/en/download/article-file/3349117
ER  -