• International Journal of Technology (IJTech)
  • Vol 10, No 7 (2019)

Adaptive Redundancy-Based Transmission for Wireless Sensor Networks

Adaptive Redundancy-Based Transmission for Wireless Sensor Networks

Title: Adaptive Redundancy-Based Transmission for Wireless Sensor Networks
JIN REN NG, Vik Tor Goh, Timothy Tzen Vun Yap, Mustaffa Kamal Shuib

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Cite this article as:
NG, J.R., Goh, V.T., Yap, T.T.V., Shuib, M.K., 2019. Adaptive Redundancy-Based Transmission for Wireless Sensor Networks. International Journal of Technology. Volume 10(7), pp. 1355-1364

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JIN REN NG Faculty of Engineering, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Vik Tor Goh Faculty of Engineering, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Timothy Tzen Vun Yap Faculty of Computing & Informatics, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Mustaffa Kamal Shuib Department of Geology, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
Email to Corresponding Author

Abstract
Adaptive Redundancy-Based Transmission for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are built upon tens to thousands of sensor nodes dispersed across a geographical area. Most sensor nodes have limited on-board resources, such as limited computing capabilities and limited power. These issues can reduce the reliability of the sensor nodes, which, in turn, affects the robustness of the WSN as a whole. One of the components that can be affected is the data transmission system of the sensor nodes. We propose a reliable transport layer protocol that uses a combination of redundant packets and probabilistic transmission to ensure reliable transmission of data while maintaining the efficiency of the network. The proposed protocol does not require acknowledgement packets, such as the transmission control protocol (TCP) and yet its efficiency is similar to that of the user datagram protocol (UDP). In this paper, we explain the proposed protocol and demonstrate how it can achieve 7% improvements in reliability while maintaining 77% efficiency compared to UDP.

Efficiency; Redundancy-based; Reliability; Wireless sensor network

Introduction

A Wireless Sensor Network (WSN) is a network system consisting of tens to thousands of wirelessly connected sensor nodes. These nodes collect data from the environment and send them to the receiver nodes. A receiver node is also known as a sink. It is used to receive and store the data collected from the sensor nodes. A typical WSN consists of multiple sensor nodes and one sink. The sensor nodes are dispersed across an area of interest, where the nodes will self-organize to form a wireless communication network. Since a single sensor node only contributes information about its immediate surroundings, multiple nodes collaborate with one another to provide better coverage over a large area.

Although WSNs can consist of only a few nodes (e.g., less than 10), their potential lies in scenarios where many nodes are deployed to monitor a large geographical area. This type of network is deployed to minimize manpower in monitoring a specific area. In certain cases, WSNs are deployed at ecologically sensitive or geographically restricted areas that are difficult for humans to access. For example, sensor nodes are deployed deep in forests, on top of mountains, and even on the slopes of hills. The remote locations and difficult operating conditions affect the reliability of the sensor nodes. Ultimately, the reliability of the sensor nodes decreases, which, in turn, affects the effectiveness of the monitoring process.  Thus, reliability is one of the main challenges faced by WSNs (Ali et al., 2018; Sumaryo et al., 2019). In this work, we look at how data transmission is affected and propose a transport layer protocol to mitigate the problem.


Conclusion

We have proposed a probabilistic redundancy-based protocol (Redundant-Probabilistic-Optimized) that is adaptive to one of the dynamic behaviors of WSN: varying noise levels. The proposed protocol would be able to choose the proper probability of sending duplicate copies of each packet according to the surrounding noise level. The usage of redundant packets would eventually improve the reliability, but it also reduces the overall efficiency of the protocol. In our proposed Redundant-Probabilistic-Optimized protocol, we can achieve the optimum result for both reliability and efficiency as compared to other protocols. In addition, our proposed Redundant-Probabilistic-Optimized protocol has been proven to be adaptable to the variation of noise levels in terms of energy consumption. In the future, we plan to study other dynamic behaviors of WSN and include more parameters in the creation of the probabilistic redundancy-based protocol, such as the surrounding temperature. Additionally, we will also evaluate the protocol in a larger network and consider sending more than two copies of a packet for increased reliability

Acknowledgement

Financial support from the Ministry of Higher Education, Malaysia, under the Fundamental Research Grant Scheme with grant number FRGS/1/2015/SG07/MMU/02/1 is gratefully acknowledged.

References

Al-Awami, L., Hassanein, H., 2012. Energy Efficient Data Survivability for WSNs via Decentralized Erasure Codes. In: Proceedings of 37th Annual IEEE Conference on Local Computer Networks, pp. 577–584

Ali, S., Al-Balushi, T., Nadir, Z., Hussain, O.K., 2018. Improving the Resilience of Wireless Sensor Networks Against Security Threats: A Survey and Open Research Issues. International Journal of Technology, Volume 9(4), pp. 828–839

Berawi, M.A., Suwartha, N., Kusrini, E., Kartohardjono, S., Suryanegara, M., Putra, N., Zagloel, T.Y., 2016. Accelerating Technology Development: Engaging Stakeholders and International Networking. International Journal of Technology, Volume 7(7), pp. 1128–1131

Bhisham, S., Trilok, C.A., 2012. A Comparative Analysis of Reliable and Congestion-aware Transport Layer Protocols for Wireless Sensor Networks. ISRN Sensor Networks, Volume 2012, pp. 52–57

Budhaditya, D., Sudeept, B., Badri, N., 2003. ReInForM: Reliable Information Forwarding using Multiple Paths in Sensor Networks. In: Proceedings of 28th Annual IEEE International Conference on Local Computer Networks, pp. 406–415

Celimuge, W., Satoshi, O., Toshihiko, K., 2012. An Adaptive Redundancy-based Mechanism for Fast and Reliable Data Collection in WSNs. In: Proceedings of 8th IEEE International Conference on Distributed Computing in Sensor Systems, pp. 347–352

Chonggang, W., Kazem, S., Bo, L., Mahmoud, D., Yueming, H., 2006. A Survey of Transport Protocols for Wireless Sensor Networks. IEEE Network, Volume 20(3), pp. 34–40

Kazem, S., Daniel, M., Taieb, Z., 2007. Wireless Sensor Networks Technology, Protocols and Applications. USA:John Wiley & Sons, Hoboken, NJ

Marchi, B., Grilo, A., Munes, M., 2007. DTSN: Distributed Transport for Sensor Networks. In: Proceedings of 12th IEEE Symposium on Computers and Communications, pp. 165–172

Meng, Y.S., Lee, Y.H., 2010. Investigations of Foliage Effect on Modern Wireless Communication Systems: A Review. Progress in Electromagnetics Research, Volume 105, pp. 313–332

Muhammad, A.M., Winston, K.G.S., Ian, W., 2015. Reliability in Wireless Sensor Networks: A Survey and Challenges Ahead. Computer Networks, Volume 79, pp. 166–187

Raghavendra, C.S., Krishna, M.S., Taieb, Z., 2004. Wireless Sensor Network. Springer, United States of America. Switzerland: Springer

Srouji, M.S., Zhonglei, W., Jorg, H., 2011. RDTS: A Reliable Erasure Coding Based Data Transfer Scheme for Wireless Sensor Networks. In: Proceedings of 17th International Conference on Parallel and Distributed Systems, pp. 481–488

Sumaryo, S., Halim, A., Ramli, K., Joelianto, E., 2019. A Model for Accelerating Discharge of Lane Traffic to Facilitate Intersection Access by EVs. International Journal of Technology, Volume 10(1), pp. 116–125

Sunil, K., Zhenhua, F., Yang, X., 2009. E2SRT: Enhanced Event-to-Sink Reliable Transport for Wireless Sensor Networks. Wireless Communications and Mobile Computing, Volume 9(10), pp. 1301–1311

Varga, A., 2010. Modeling and Tools for Network Simulation. Berlin, Heidelberg: Springer

Winston, K.G.S., Hwee, X.T., 2006. Multipath Virtual Sink Architecture for Wireless Sensor Networks in Harsh Environments. In: Proceedings of the 1st International Conference on Integrated Internet Ad-hoc and Sensor Networks, p. 19

Yogesh, S., Ozgur, B.A., Ian, F.A., 2003. ESRT: Event-to-Sink Reliable Transport in Wireless Sensor Networks. In: Proceedings of the 4th ACM International Symposium on Mobile Ad-hoc Networking & Computing, pp. 177–188