In an underwater wireless sensor networks, it is very difficult to communicate data over the 3-D underwater acoustic signal. In acoustic communication, there is no proper transmission between a source node to sink node. In existing work, single-hop clustering protocols were used for direct communication from cluster head to base station. Since direct communication is involved, the transmission range is very large and hence the data communication becomes difficult. In proposed work, additional leverage is achieved by introducing multi-hop clustering for speedy data transmission by selecting Relay Autonomous Underwater Vehicles (Relay-AUV) without delay and maximum channel capacity in acoustic wireless communication. The proposed scheme presents Relay-AUV selection algorithm using Contextual Bandit Bi-partite Graph (CB-BG) formulated by multi-hop data transmission, which provides maximum leverage for energy saving in cluster networks. Theoretical analysis and experimental simulation results are evaluated based on performance metrics such as successive transmission rate, throughput, cost of execution time and packet delivery ratio. The results shows that the proposed CB-BG system has maximum increase in data transmission rate of 58.33%, maximum increase in throughput and network throughput of 54.95%, maximum increase in operational time cost of 27.77% and high packet delivery ratio of 66.66%. The results are encouraging and our proposed method is found to be more efficient than the weight matching algorithms and minimum distances relay policies. The proposed CB-BG mechanism performs faster and reliable communication.
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Tan, D. D., Le, T. T., & Kim, D.-S. (2013). Distributed cooperative transmission for underwater acoustic sensor networks. In 2013 IEEE wireless communications and networking conference workshops (WCNCW) (pp. 205–210). IEEE.
Vincent, M., Babu, K. V., Arthi, M., & Arulmozhivarman, P. (2016). A novel fuzzy based relay node deployment scheme for multi-hop relay network. Procedia Technology, 24, 842–853.
Wang, M., Liu, D., Zhu, L., Xu, Y., & Wang, F. (2016). Lespp: lightweight and efficient strong privacy preserving authentication scheme for secure vanet communication. Computing, 98(7), 685–708.
Xie, G., Liu, Y., Gao, J., & Li, X.-Z. (2013). Sort-based relay selection algorithm for decode-and-forward relay system. Science China Information Sciences, 56(2), 3–10.
Katrenič, J., & Semanišin, G. (2013). Maximum semi-matching problem in bipartite graphs. Discussiones Mathematicae Graph Theory, 33(3), 559–569.
Alizadeh, A., Forouzan, N., Ghorashi, S. A., & Sadough, S. M.-S. (2011). A graph-based approach for relay selection and resource allocation in cognitive two-way relay networks. In 2011 Wireless advanced (WiAd) (pp. 101–105). IEEE.
Doosti-Aref, A., & Ebrahimzadeh, A. (2017). Adaptive relay selection and power allocation for ofdm cooperative underwater acoustic systems. IEEE Transactions on Mobile Computing, 17, 1–15.
Aslam, N., Robertson, W., & Phillips, W. J. (2009). Algorithms for relay node selection in randomly deployed homogenous cluster-based wireless sensor networks. Ad Hoc and Sensor Wireless Networks, 8(1–2), 5–20.
Gu, Y., Shao, Y., Han, H., & Yi, T. (2011). A clustering routing algorithm of wsn based on uneven nodes deployment. In 2011 International conference on wireless communications and signal processing (WCSP) (pp. 1–6). IEEE.
Dan, C., Hong, J., & Xi, L. (2011). Energy-efficient joint relay node selection and power allocation over multihop relaying cellular networks toward lte-advanced. The Journal of China Universities of Posts and Telecommunications, 18(3), 1–7.
Yang, C.-H., Ssu, K.-F., & Lin, Y. Y. (2013). “A delay-awareness routing protocol in intermittently connected underwater acoustic sensor networks,” in Dependable Computing (PRDC), 2013 IEEE 19th Pacific Rim International Symposium on, pp. 138–139, IEEE.
Su, R., Venkatesan, R., & Li, C. (2015). An energy-efficient relay node selection scheme for underwater acoustic sensor networks. Cyber-Physical Systems, 1(2–4), 160–179.
Li, S., Zhou, Y., Peng, D., Dou, Z., & Zhou, Y. (2016). Analysis of dual-hop and multiple relays cooperative truncated arq with relay selection in wsns. Acta Informatica, 53(1), 1–22.
Lv, X., Li, H., & Li, H. (2017). A node coverage algorithm for a wireless-sensor-network-based water resources monitoring system. Cluster Computing, 20(4), 3061–3070.
Khan, S., Parkinson, S., & Qin, Y. (2017). Fog computing security: A review of current applications and security solutions. Journal of Cloud Computing, 6(1), 19.
Bouallegue, T., & Sethom, K. (2017). New threshold-based relay selection algorithm in dual hop cooperative network. Procedia Computer Science, 109, 273–280.
Geng, K., Gao, Q., Fei, L., & Xiong, H. (2017). Relay selection in cooperative communication systems over continuous time-varying fading channel. Chinese Journal of Aeronautics, 30(1), 391–398.
Li, X., Liu, J., Yan, L., Han, S., & Guan, X. (2017). Relay selection in underwater acoustic cooperative networks: A contextual bandit approach. IEEE Communications Letters, 21(2), 382–385.
Tuna, G., Gungor, V. C. (2017). A survey on deployment techniques, localization algorithms, and research challenges for underwater acoustic sensor networks. International Journal of Communication Systems, 30(17), e3350.
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Priyadarshini, R.R., Sivakumar, N. Relay Selection Approach in Underwater Acoustic WSNs Using Bi-Partite Graph. Wireless Pers Commun 111, 643–660 (2020). https://doi.org/10.1007/s11277-019-06877-y
- Bi-partite graph
- Cluster head