Abstract
The power issue in wireless sensor network (WSN) stays one of the real barriers keeping the complete abuse of this technology. The WSN is a dense network of sensors which sense the environmental conditions, process and propagate that data towards sink node. Limited battery life of sensor node and unbalanced utilization of that energy can affect the lifetime of the entire sensor network. In proposed work, mobile nodes are used to transmit the data nearby the area where the power consumption of the nodes is more. The mobile node reduces the workload and congestion of the nodes which is controlled by adjusting the reporting rate (RR) according to the buffer occupancy level. In this paper, we have correlated the existing Ad hoc on demand vector (AODV) routing protocol with our new approach to the delivery of power consumption. The proposed work evaluate the performance of the lifetime and energy consumption of the WSN with and without mobile nodes and results achieved by adjusting the number of mobile nodes, location and the speed of mobile node. The RR is also adjusted to control the buffer occupancy of each node and mitigate the congestion that occurs in the sensor network. Based on this simulation results, this proposed work increases the lifetime of the nodes whose power consumption speed is high and enhances the life of the entire network. The use of a dual threshold for buffer and mobile node can reduce the congestion and the waiting time for data reducing the delay.
References
Azad, A.K.M., Kamruzzaman, J.: Energy-balanced transmission policies for wireless sensor networks. IEEE Trans. Mob. Comput. 10(7), 927–940 (2011)
Alippi, C., Anastasi, G., Di Francesco, M., Roveri, M.: Energy management in wireless sensor networks with energy-hungry sensors. IEEE Instrum. Measur. Mag. 12(2), 16–23 (2009)
GowriDurga, A., Prakash, B.: A zigbee sms alert system with trust mechanism in wireless sensor networks. In: 2013 International Conference on Information Communication and Embedded Systems (ICICES), pp. 1010–1014. IEEE (2013)
Tubaishat, M., Madria, S.: Sensor networks: an overview. IEEE Potentials 22(2), 20–23 (2003)
Suraiya, Ta, et al.: Energy conservation challenges in wireless sensor networks: a comprehensive study. Wireless Sens. Netw. 2(06), 483 (2010)
Hefeeda, M., Bagheri, M.: Wireless sensor networks for early detection of forest fires. In: IEEE International Conference on Mobile Adhoc and Sensor Systems, 2007. MASS 2007, pp. 1–6. IEEE (2007)
Opasjumruskit, K., Thanthipwan, T., Sathusen, O., Sirinamarattana, P., Gadmanee, P., Pootarapan, E., Wongkomet, N., Thanachayanont, A., Thamsirianunt, M.: Self-powered wireless temperature sensors exploit RFID technology. IEEE Pervasive comput. 5(1), 54–61 (2006)
Reindl, L., Shrena, I., Kenshil, S., Peter, R.: Wireless measurement of temperature using surface acoustic waves sensors. In: Proceedings of the 2003 IEEE International Frequency control symposium and PDA exhibition jointly with the 17th European Frequency And Time Forum, 2003, pp. 935–941. IEEE (2003)
Garzón, C.A.L., Riveros, O.J.R.: Temperature, humidity and luminescence monitoring system using wireless sensor networks (wsn) in flowers growing. In 2010 IEEE ANDESCON, pp. 1–4. IEEE (2010)
Luomala, J., Hakala, I.: Effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks. In: 2015 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 1247–1255. IEEE (2015)
Umit Bas, C., Coleri Ergen, S.: Ultra-wideband channel model for intra-vehicular wireless sensor networks beneath the chassis: from statistical model to simulations. IEEE Trans. Veh. Technol. 62(1), 14–25 (2013)
Hung, C.-C., Peng, W.-C.: Model-driven traffic data acquisition in vehicular sensor networks. In: 2010 39th International Conference on Parallel Processing (ICPP), pp. 424–432. IEEE (2010)
Segura-Garcia, J., Felici-Castell, S., Perez-Solano, J.J., Cobos, M., Navarro, J.M.: Low-cost alternatives for urban noise nuisance monitoring using wireless sensor networks. IEEE Sens. J. 15(2), 836–844 (2015)
Bekmezci, I., Alagöz, F.: Energy efficient, delay sensitive, fault tolerant wireless sensor network for military monitoring. Int. J. Distrib. Sens. Netw. 5(6), 729–747 (2009)
Mascareñas, D., Flynn, E., Farrar, C., Park, G., Todd, M.: A mobile host approach for wireless powering and interrogation of structural health monitoring sensor networks. IEEE Sens. J. 9(12), 1719–1726 (2009)
Bhuiyan, M.Z.A., Wang, G., Cao, J., Wu, J.: Deploying wireless sensor networks with fault-tolerance for structural health monitoring. IEEE Trans. Comput. 64(2), 382–395 (2015)
Mendis, C., Skvortsov, A., Gunatilaka, A., Karunasekera, S.: Performance of wireless chemical sensor network with dynamic collaboration. IEEE Sens. J. 12(8), 2630–2637 (2012)
Pattnaik, P.K., Mall, R.: Fundamentals of Mobile Computing. PHI Learning Pvt. Ltd., (2015)
Kilts, S.: Advanced FPGA design: Architecture, Implementation, and Optimization. Wiley (2007)
Madurawe, R.U.: Alterable application specific integrated circuit (asic), June 20 2006. US Patent 7,064,579
Tao, L.Q., Yu, F.Q.: Ecoda: enhanced congestion detection and avoidance for multiple class of traffic in sensor networks. IEEE Trans. Consum. Electron. 56(3), 1387–1394 (2010)
Wang, G., Liu, K.: Upstream hop-by-hop congestion control in wireless sensor networks. In: 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1406–1410. IEEE (2009)
Kafi, M.A., Ben-Othman, J., Ouadjaout, A., Bagaa, M., Badache, N.: REFIACC: reliable, efficient, fair and interference-aware congestion control protocol for wireless sensor networks. Comput. Commun. (2016)
Kafi, M.A., Djenouri, D., Othman, J.B., Ouadjaout, A., Bagaa, M., Lasla, N., Badache, N.: Interference-aware congestion control protocol for wireless sensor networks. Procedia Comput. Sci. 37, 181–188 (2014)
Esmaeelzadeh, V., Hosseini, E.S., Berangi, R., Akan, O.B.: Modeling of rate-based congestion control schemes in cognitive radio sensor networks. Ad Hoc Netw. 36, 177–188 (2016)
Ghaffari, A.: Congestion control mechanisms in wireless sensor networks: a survey. J. Netw. Comput. Appl. 52, 101–115 (2015)
Heikalabad, S.R., Ghaffari, A., Hadian, M.A., Rasouli, H.: Dpcc: dynamic predictive congestion control in wireless sensor networks. IJCSI Int. J. Comput. Sci. Issues 8(1) (2011)
Shih, H.-C., Ho, J.-H., Liao, B.-Y., Pan, J.-S.: Fault node recovery algorithm for a wireless sensor network. IEEE Sens. J. 13(7), 2683–2689 (2013)
Zou, Z., Bao, Y., Li, H., Spencer, B.F., Ou, J.: Embedding compressive sensing-based data loss recovery algorithm into wireless smart sensors for structural health monitoring. IEEE Sens. J. 15(2), 797–808 (2015)
Sobrinho, J.L., Krishnakumar, A.S.: Quality-of-service in ad hoc carrier sense multiple access wireless networks. IEEE J. Sel. Areas Commun. 17(8), 1353–1368 (1999)
Tati, R., Ahmadi, F., Rashidy, R., Ashkoti, F.: Designing and simulation of a distributed algorithm for quality of service in wireless sensor networks. In: International Conference on Application of Information and Communication Technologies, pp. 1–5. IEEE (2009)
Xiaoyan, Y., Xingshe, Z., Rongsheng, H., Yuguang, F., Shining, L.: A fairness-aware congestion control scheme in wireless sensor networks. IEEE Trans. Veh. Technol. 58(9), 5225–5234 (2009)
Emad, F., Chang-Gun, L., Eylem, E.: Mmspeed: multipath multi-speed protocol for qos guarantee of reliability and timeliness in wireless sensor networks. IEEE Trans. Mob. Comput. 6, 738–754 (2006)
Mukhopadhyay, S., Schurgers, C., Panigrahi, D., Dey, S.: Model-based techniques for data reliability in wireless sensor networks. IEEE Trans. Mob. Comput. 8(4), 528–543 (2009)
Ghaffari, A.: An energy efficient routing protocol for wireless sensor networks using a-star algorithm. J. Appl. Res. Technol. 12(4), 815–822 (2014)
Wei, D., Jin, Y., Vural, S., Moessner, K., Tafazolli, R.: An energy-efficient clustering solution for wireless sensor networks. IEEE Trans. Wirel. Commun. 10(11), 3973–3983 (2011)
Fang, W., Liu, F., Yang, F., Shu, L., Nishio, S.: Energy-efficient cooperative communication for data transmission in wireless sensor networks. IEEE Trans. Consum. Electron. 56(4), 2185–2192 (2010)
Abusaimeh, H., Yang, S.-H.: Balancing the power consumption speed in flat and hierarchical wsn. Int. J. Autom. Comput. 5(4), 366–375 (2008)
Park, S., Lee, E., Jin, M.-S., Kim, S.-H.: Novel strategy for data dissemination to mobile sink groups in wireless sensor networks. IEEE Commun. Lett. 14(3), 202–204 (2010)
Fahmy, H.M.A.: Protocol stack of WSNs. In: Wireless Sensor Networks, pp. 55–68. Springer (2016)
Ye, W., Heidemann, J.: Medium access control in wireless sensor networks. In: Wireless Sensor Networks, pp. 73–91. Springer (2004)
Ahammed, G.F., Banu, R.: Analyzing the performance of active queue management algorithms. arXiv:1003.3909 (2010)
Karenos, K., Kalogeraki, V.: Traffic management in sensor networks with a mobile sink. IEEE Trans. Parallel Distrib. Syst. 21(10), 1515–1530 (2010)
Cheng, Z., Perillo, M., Heinzelman, W.B.: General network lifetime and cost models for evaluating sensor network deployment strategies. IEEE Trans. Mob. Comput. 7(4), 484–497 (2008)
Ren, F., Zhang, J., He, T., Lin, C., Ren, S.K.D.: Ebrp: energy-balanced routing protocol for data gathering in wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 22(12), 2108–2125 (2011)
Park, S., Lee, W., Cho, D.: Fair clustering for energy efficiency in a cooperative wireless sensor network. In: 2012 IEEE 75th Vehicular Technology Conference (VTC Spring), pp. 1–5. IEEE (2012)
Mhatre, V., Rosenberg, C.: Design guidelines for wireless sensor networks: communication, clustering and aggregation. Ad Hoc Netw. 2(1), 45–63 (2004)
Tambe, S.B., Thool, R.C., Thool,V.R.: Power consumption and congestion control of rendezvous node for wireless biosensor network. In: Proceedings of International Conference on ICT for Sustainable Development, pp. 647–655. Springer (2016)
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Tambe, S.B., Gajre, S.S. (2018). Novel Strategy for Fairness-Aware Congestion Control and Power Consumption Speed with Mobile Node in Wireless Sensor Networks. In: Yang, XS., Nagar, A., Joshi, A. (eds) Smart Trends in Systems, Security and Sustainability. Lecture Notes in Networks and Systems, vol 18. Springer, Singapore. https://doi.org/10.1007/978-981-10-6916-1_9
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