The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

• Autorzy: Raina V. , Jha M. K. , Bhattacharya P. P.

Identyfikatory

DOI

10.26636/jtit.2017.112317

• Języki publikacji: EN

Abstrakty

EN

Time synchronization between sensor nodes to reduce the end-to-end delay for critical and real time data monitoring can be achieved by cautiously monitoring the mobility of the mobile sink node in underwater wireless sensor networks. The Alive-in-Range Medium Access Control (ARMAC) protocol monitors the delay of sensitive, critical and real-time data. The idea evolves as it involves reduction in duty cycle, precise time scheduling of active/sleep cycles of the sensors, monitoring the mobility of the sink node with the selection of appropriate queues and schedulers. The model for the path loss due to attenuation of electromagnetic wave propagation in the sea water is explained. The three-path reflection model evaluating reflection loss from the air-water and watersand interfaces as a function of distance between sensors and water depth is introduced. The algorithms for effective path determination and optimum throughput path determination are elaborated. The results verify that implementation of the Alive-in-Range MAC protocol has reduced the total number of packets dropped, the average queue length, the longest time in queue, the peak queue length and the average time in queue significantly, making it relevant for critical and real-time data monitoring.

Słowa kluczowe

EN

Alive-in-Range MAC; effective path determination; mobile sink; optimum throughput path determination; underwater wireless sensor network

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2017
• Tom: nr 4
• Strony: 31--46
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Raina V.

• Department of ECE, CET, Mody University of Science and Technology, Lakshmangarh, India

autor

Jha M. K.

• ABES Engineering College, Ghaziabad, India

autor

Bhattacharya P. P.

• Department of ECE, CET, Mody University of Science and Technology, Lakshmangarh, India

Bibliografia

• [1] I. F. Akyildiz, D. Pompili, and T. Melodia, “Underwater acoustic sensor networks: research challenges”, Ad Hoc Networks, vol. 3, no. 3, pp. 257–279, 2005.
• [2] I. F. Akyildiz, D. Pompili, and T. Melodia, “State of the art in protocol research in underwater acoustic sensor networks”, ACM Mob. Comput. Commun. Rev., vol. 11, no. 4, pp. 11–22, 2007.
• [3] L. Weifa, L. Jun, and X. Xu, “Prolonging network lifetime via a controlled mobile sink in wireless sensor networks”, in Proc. of IEEE Global Telecommun. Conf. GLOBECOM 2010, Miami, FL, USA, 2010 (doi: 10.1109/GLOCOM.2010.5683095).
• [4] J. K. Jalaja and J. Lillykutty, “Delay and lifetime performance of underwater wireless sensor networks with mobile element based data collection”, Int. J. of Distrib. Sensor Netw., vol. 8, no. 1, pp. 1–22, 2015.
• [5] S. Sendra, J. Lloret, J. J. P. C. Rodrigues, and J. M. Aguiar, “Underwater wireless communications in freshwater at 2.4 GHz”, IEEE Commun. Lett., vol. 17, no. 9, pp. 1794–1797, 2013.
• [6] E. Ali, E. Abdelrahman, A. Majed, and E. Khaled, “Underwater wireless sensor network communication using electromagnetic waves at resonance frequency 2.4 GHz”, in Proc. of of the ACM 15th Commun. and Netw. Simulation Symp. CNS’12, Orlando, FL, USA, 2012.
• [7] B. Latré, P. De Mil, I. Moerman, B. Dhoedt, and P. Demeester, “Throughput and delay analysis of unslotted IEEE 802.15.4”, J. of Networks, vol. 1, no. 1, pp. 20–28, 2006.
• [8] K. Yu, M. Gidlind, J. Akerberg, and M. Bjorkman, “Low jitter scheduling for industrial wireless sensor and actuator networks”, in Proc. of the 39th Ann. Conf. of the IEEE Industrial Electron. Soc. IECON 2013, Vienna, Austria, 2013, pp. 5594–5599.
• [9] M. Aoun and A. Argyriou, “Queueing model and optimization of packet dropping in real-time wireless sensor networks”, in Proc. of the IEEE Global Commun. Conf. GLOBECOM 2012 – Commun. QoS, Reliab. and Model. Symp., Anaheim, CA, USA, 2012, pp. 1687–1691.
• [10] J. Liu et al., “DA-Sync: A Doppler-Assisted time synchronization scheme for mobile underwater sensor networks”, IEEE Trans. on Mob. Comput., vol. 13, no. 3, pp. 582–595, 2014.
• [11] H. Yang and B. Sikdar, “A mobility based architecture for underwater acoustic sensor networks”, in Proc. IEEE Global Telecommun. Conf. GLOBECOM 2008, New Orleans, LA, USA, 2008.
• [12] N. Tuan Le, S. Woong Choi, and Y. Min Jang, “Approximate queuing analysis for IEEE 802.15.4 sensor network”, in Proc. 2nd Int. Conf. on Ubiquit. and Future Netw. ICUFN 2010, Jeju Island, Korea (South), 2010, pp. 193–198.
• [13] S. Charalambos, V. Vasos, and P. Aristodemos, “Estimating queue formation rate in Wireless Sensor Networks using a fluid dynamic model”, in Proc. 20th IEEE Symp. on Comp. and Commun. ISCC 2015, Larnaca, Cyprus, 2015, pp. 544–548.
• [14] N. Van Mao and V. Que Son, “Applying queuing theory to evaluate performance of cluster wireless sensor networks”, in Proc. Int. Conf. on Adv. Technol. for Commun. ATC 2015, Ho Chi Minh City, Vietnam, 2015.
• [15] J.-F. Ke, W.-J. Chen, and D.-C. Huang, “Life extend approach based on priority Queue N strategy for wireless sensor network”, in Proc. 11th In. Conf. on Heterogen. Netw. for Qual., Reliabil., Secur. and Robustness QSHINE 2015, Taipei, Taiwan, 2015.
• [16] S. Vanithamani and N. Mahendran, “Performance analysis of queue based scheduling schemes in wireless sensor networks”, in Int. Conf. on Electron. and Commun. Syst. ICECS 2014, Coimbatore, India, 2014.
• [17] H. Byun and J. Yu, “Adaptive duty cycle control with queue management in wireless sensor networks”, IEEE Trans. on Mob. Comput., vol. 12, no. 6, pp. 1214–1224, 2013.
• [18] E. G. W. Peters, D. E. Quevedo, and M. Fu, “Controller and scheduler codesign for feedback control over IEEE 802.15.4 networks”, IEEE Trans. on Control Syst. Technol., vol. 1, no. 99, pp. 2459–2464, 2016.
• [19] B. Pati, J. L. Sarkar, C. R. Panigrahi, and R. K. Verma, “CQS: A Conflict-free query scheduling approach in wireless sensor networks”, in Proc. 3rd Int. Conf. on Recent Adv. in Inform. Technol. RAIT 2016, Dhanbad, India, 2016, pp. 13–18.
• [20] H. Zhang et al., “Scheduling with predictable link reliability for wireless networked control”, in Proc. 23rd Int. Symp. on Quality of Service IWQoS 2015, Portland, OR, USA, 2015.
• [21] B. Pati, J. L. Sarkar, C. R. Panigrahi, and M. Tiwary, “ARTQS: An advanced real-time query scheduling approach in wireless sensor networks”, in Proc. Int. Conf. on Green Comput. and Internet of Things ICGCIoT 2015, Delhi, India, 2015, pp. 219–224.
• [22] E. G. W. Peters, D. E. Quevedo, and M. Fu, “Co-design for control and scheduling over wireless industrial control networks”, in Proc. 54th IEEE Conf. on Decision and Control CDC 2015, Osaka, Japan, 2015, pp. 2016–2030.
• [23] M. H. Shahid and Sh. Masud, “Improved low power scheduler for OSS-7: An open source DASH7 stack”, in Proc. IEEE Int. Conf. on Electron., Circuits, and Syst. ICECS 2015, Cairo, Egypt, 2015, pp. 645–648.
• [24] M. Chovanec and P. Sarafin, “Real-time schedule for mobile robotics and WSN applications”, in Proc. Federated Conf. on Comp. Sci. and Inform. Syst. FedCSIS 2015, Lodz, Poland, pp. 1199–1202.
• [25] M. A. Jamshed et al., “An energy efficient priority based wireless multimedia sensor node dynamic scheduler”, in Proc. 12th Int. Conf. on High-capacity Opt. Netw. and Enabling/Emerging Technol. HONET 2015, Islamabad, Pakistan, 2015, pp. 147–150.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).