ارائه یک الگوریتم مبتنی بر رایانش مه جهت مسیریابی شبکه‌های حسگر بی‌سیم
محورهای موضوعی : مهندسی برق و کامپیوترالهام میرزاوند بروجنی 1 , دادمهر رهبری 2 , محسن نیک‌رای 3 *
1 - دانشگاه قم
2 - دانشگاه قم
3 - دانشگاه قم
کلید واژه: شبکه‌های حسگر بی‌سیمطول عمر شبکهکارامدی انرژیمحاسبات مه,
چکیده مقاله :
شبکه‌های حسگر بی‌سیم از هزاران گره کوچک تشکیل شده‌اند که کوچکی و ارزانی این گره‌ها موجب استفاده گسترده آنها در زمینه‌های مختلف شده است. در کنار مزیت‌های این شبکه‌ها، محدودیت در مصرف انرژی، منابع پردازشی و ذخیره‌سازی موجب شده مطالعات بسیاری به‌منظور کاهش این محدودیت‌ها ارائه شود. در سال‌های اخیر با ظهور مفهوم محاسبات مه، راهکارهای جدید و مؤثری در زمینه مسیریابی شبکه‌های حسگر بی‌سیم مطرح شده است. از آنجایی که در این شبکه‌ها، حفظ گره‌های زنده و کاهش انرژی مصرفی گره‌ها حایز اهمیت است لذا محاسبات مه در راستای این هدف به کار گرفته می‌شود. در پروتکل‌های مطرح مسیریابی در شبکه‌های حسگر بی‌سیم، بهترین راه جهت ارسال داده‌ها به سرخوشه‌ها و همچنین ایستگاه اصلی مورد بررسی قرارگرفته است. در مطالعات جدید از محاسبات مه، جهت یافتن بهترین روش مسیریابی بهره برده شده که در این روش‌ها کاهش انرژی مصرفی و افزایش طول عمر شبکه را شاهد بوده‌ایم. ما نیز در این مقاله یک معماری مبتنی بر رایانش مه جهت مسیریابی شبکه‌های حسگر بی‌سیم را ارائه داده‌ایم. مطابق نتایج شبیه‌سازی، این پروتکل، انرژی مصرفی را 9% و همچنین تعداد گره‌های زنده را 74% در مقایسه با روش مورد بررسی بهبود بخشیده است.
Wireless sensor networks (WSNs) consist of thousands of small nodes. The small and inexpensive parts of these nodes have led to their widespread use in various fields. However, these networks have constraints on energy consumption, processing resources, and storage which have caused many studies to find solutions to reduce these constraints. In recent years, with the advent of the concept of Fog computing, many new and effective solutions are represented for routing in wireless sensor networks. Since in WSNs it is important to save alive nodes and reduce the energy consumption of nodes, fog computing is useful for this purpose. In most WSN routing protocols, the best way to send data to cluster heads and the base station is the major part of their studies. In the new protocols, the Fog computing have been used to find the best way. In these methods, we have seen decreasing energy consumption and increasing network lifetime. In this paper, we represent a fog-based algorithm for routing in WSNs. According to the simulation results, the proposed protocol improved energy consumption by 9% meanwhile the number of alive nodes is increased by 74%, compared to the reviewed method.
[1] A. V. Dastjerdi and R. Buyya, "Fog computing: helping the internet of things realize its potential," Computer, vol. 49, no. 8, pp. 112-116, Aug. 2016.
[2] S. Tomovic, K. Yoshigoe, I. Maljevic, and I. Radusinovic, "Software defined fog network architecture for iot," Wireless Personal Communications, vol. 92, no. 1, pp. 181-196, Jan. 2017.
[3] X. Sun and N. Ansari, "Edgeiot: mobile edge computing for the internet of things," IEEE Communications Magazine, vol. 54, no. 12, pp. 22-29, Dec. 2016.
[4] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, "Internet of things (iot): a vision, architectural elements, and future directions," Future Generation Computer Systems, vol. 29, no. 7, pp. 1645-1660, Sep. 2013.
[5] H. Xia, R. H. Zhang, J. Yu, and Z. K. Pan, "Energy-efficient routing algorithm based on unequal clustering and connected graph in wireless sensor networks," International J. of Wireless Information Networks, vol. 23, no. 2, pp. 141-150, Jun. 2016.
[6] S. Ivanov, S. Balasubramaniam, D. Botvich, and O. B. Akan, "Gravity gradient routing for information delivery in fog wireless sensor networks," Ad Hoc Networks, vol. 46, pp. 61-74, Aug. 2016.
[7] M. Firdhous, O. Ghazali, and S. Hassan, "Fog computing: will it be the future of cloud computing," in Proc. 3rd Int. Conf. on Informatics & Application,s ICIA’14, pp. 8-15, Kuala Terengganu, Malaysia, Oct. 2014.
[8] S. Lindsey and C. S. Raghavendra, "Pegasis: power-efficient gathering in sensor information systems," in Proc. Aerospace Conf. IEEE, vol. 3, pp. 1125-1130, Big Sky, MT, USA, Mar. 2002.
[9] P. G. V. Naranjo, M. Shojafar, H. Mostafaei, Z. Pooranian, and E. Baccarelli, "P-sep: a prolong stable election routing algorithm for energylimited heterogeneous fog-supported wireless sensor networks," the J. of Supercomputing, vol. 73, no. 2, pp. 733-755, Feb. 2017.
[10] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy- efficient communication protocol for wireless microsensor networks," in Proc. 33rd Annual Hawaii Int. Conf. on System Sciences, 10 pp., Maui, HI, USA, 7-7 Jan. 2000.
[11] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks," IEEE Trans. on Wireless Communications, vol. 1, no. 4, pp. 660-670, Dec. 2002.
[12] W. B. Heinzelman, Application-Specific Protocol Architectures for Wireless Networks, Ph.D Thesis, Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science, 2000.
[13] Y. Liu, J. Gao, Y. Jia, and L. Zhu, "A cluster maintenance algorithm based on leach-dchs protoclol," in Proc. IEEE Int. Conf. Networking, Architecture, and Storage, NAS'08, pp. 165-166, Chongqing, China, 12-14 Jun. 2008.
[14] G. Smaragdakis, I. Matta, and A. Bestavros, Sep: A Stable Election Protocol for Clustered Heterogeneous Wireless Sensor Networks, Tech. Rep., Boston University Computer Science Department, pp. 1-11, May 2004.
[15] D. Singh and C. K. Panda, "Performance analysis of modified stable election protocol in heterogeneous WSN," in Proc. Int. Conf. on Electrical, Electronics, Signals, Communication and Optimization, EESCO’15, 5 pp., Visakhapatnam, India, 24-25 Jan. 2015.
[16] A. A. Malluh, K. M. Elleithy, Z. Qawaqneh, R. J. Mstafa, and A. Alanazi, "Em-sep: an efficient modified stable election protocol," in Proc. the IEEE Zone 1 Conf. of the American Society for Engineering Education, 7 pp., Bridgeport, CT, USA, 3-5 Apr. 2014.
[17] J. Wang, X. Yang, T. Ma, M. Wu, and J. U. Kim, "An energy-efficient competitive clustering algorithm for wireless sensor networks using mobile sink," International J. of Grid and Distributed Computing, vol. 5, no. 4, pp. 79-92, Dec. 2012.
[18] D. Karaboga, S. Okdem, and C. Ozturk, "Cluster based wireless sensor network routing using artificial bee colony algorithm," Wireless Networks, vol. 18, no. 7, pp. 847-860, Oct. 2012.
[19] E. Baccarelli, N. Cordeschi, and V. Polli, "Optimal self-adaptive qos resource management in interference-affected multicast wireless networks," IEEE/ACM Trans. on Networking, vol. 21, no. 6, pp. 1750-1759, Jan. 2013.
[20] C. Petrioli, M. Nati, P. Casari, M. Zorzi, and S. Basagni, "Alba-r: loadbalancing geographic routing around connectivity holes in wireless sensor networks," IEEE Trans. on Parallel and Distributed Systems, vol. 25, no. 3, pp. 529-539, Mar. 2014.
[21] S. Tanwar, N. Kumar, and J. W. Niu, "Eemhr: energy-efficient multilevel heterogeneous routing protocol for wireless sensor networks," International J. of Communication Systems, vol. 27, no. 9, pp. 1289-1318, Mar. 2014.
[22] D. Jiang, Z. Xu, W. Li, and Z. Chen, "Topology control-based collaborative multicast routing algorithm with minimum energy consumption," International J. of Communication Systems, vol. 30, no. 1, Article No. e2905, 10 Jan. 2017.
[23] H. Orojloo and A. T. Haghighat, "A tabu search based routing algorithm for wireless sensor networks," Wireless Networks, vol. 22, no. 5, pp. 1711-1724, Jul. 2016.
[24] D. R. Chen, "An energy-efficient qos routing for wireless sensor networks using self-stabilizing algorithm," Ad Hoc Networks, vol. 37, no. 2, pp. 240-255, Feb. 2016.
[25] P. Kar and S. Misra, "Detouring dynamic routing holes in stationary wireless sensor networks in the presence of temporarily misbehaving nodes," International J. of Communication Systems, vol. 30, no. 4, pp. 1-17, Jun. 2017.
[26] A. A. Rahat, R. M. Everson, and J. E. Fieldsend, "Evolutionary multipath routing for network lifetime and robustness in wireless sensor networks," Ad Hoc Networks, vol. 52, pp. 130-145, 29-29 Apr. 2016.
[27] A. Razaque, et al., "H-LEACH: hybrid-low energy adaptive clustering hierarchy for wireless sensor networks," in Proc. IEEE Long Island Systems, Applications and Technology Conf., LISAT’16, 4 pp., Farmingdale, NY, USA, 29-29 Apr. 2016.
[28] G. Xie, K. Ota, M. Dong, F. Pan, and A. Liu, "Energy-efficient routing for mobile data collectors in wireless sensor networks with obstacles," Peer-to-Peer Networking and Applications, vol. 10, no. 3, pp. 472-483, May 2017.
[29] M. Aslam, E. U. Munir, M. M. Rafique, and X. Hu, "Adaptive energy efficient clustering path planning routing protocols for heterogeneous wireless sensor networks," Sustainable Computing: Informatics and Systems, vol. 12, pp. 57-71, Dec. 2016.
[30] S. Alam and D. De, "Cloud smoke sensing using iarp, ierp and zrp routing protocols for wireless senor network," CSI Trans. on ICT, vol. 5, no. 1, pp. 119-124, Mar. 2017.
[31] R. Moreno-Vozmediano, R. S. Montero, E. Huedo, and I. M. Llorente, "Cross-site virtual network in cloud and fog computing," IEEE Cloud Computing, vol. 4, no. 2, pp. 46-53, Apr. 2017.
[32] J. Wang, J. Cao, S. Ji, and J. H. Park, "Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks," The J. of Supercomputing, vol. 73, no. 7, pp. 3277-3290, Jul. 2017.
[33] T. H. Luan, L. Gao, Z. Li, Y. Xiang, G. Wei, and L. Sun, "Fog computing: focusing on mobile users at the edge," arXiv preprint arXiv:1502.01815,11 pp., Mar. 2016.
[34] F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, "Fog computing and its role in the internet of things," in Proc. the 1st Edition of the MCC Workshop on Mobile Cloud Computing, ACM, pp. 13-15, Helsinki, Finland, 13-17 Aug. 2012.
[35] J. Yang, X. Shi, M. Marchese, and Y. Liang, "An ant colony optimization method for generalized TSP problem," Progress in Natural Science, vol. 18, no. 11, pp. 1417-1422, Nov. 2008.
[36] F. Karatas and I. Korpeoglu, "Fog-based data distribution service (F-DAD) for internet of things (IoT) applications," Future Generation Computer Systems, vol. 93, pp. 156-169, Apr. 2019.