Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks

Majlesi Journal of Electrical Engineering

مقاله 3، دوره 14، شماره 3، آذر 2020، صفحه 23-38   

نوع مقاله: Review Article

شناسه دیجیتال (DOI): 10.29252/mjee.14.3.3

نویسنده

Ehsan Kharati

Department of Computer Engineering, Qom Branch, Islamic Azad University, Qom, Iran,

چکیده

In recent years, Network Coding (NC) has been used to increase performance and efficiency in Wireless Sensor Networks (WSNs). In NC, Sensor Nodes (SNs) of network first store the received data as a packet, then process and combine them and eventually send them. Since the bandwidth of edges between SNs is limited, management and balancing bandwidth should be used for NS. In this paper, we present an optimization model for routing and balancing bandwidth consumption using NC and multicast flows in WSNs. This model minimizes the ratio of the total maximum bandwidth to the available bandwidth in network's edges and we use the dual method to solve this model. We also use the Karush–Kuhn–Tucker conditions (KKT) to calculate a lower bound and find the optimal solution and point in optimization model. For this purpose, we need to calculate the derivative of the Lagrangian function relative to its variables, in order to determine the condition as a multi-excited multi-equation device. But since the solution of equations KKT is centralized and for WSNs with a large number of SNs, it is very difficult and time consuming and almost impractical, we provide a distributed and repeatable algorithm for solving proposed model in which instead of deriving derivatives, combination Sub-gradient method and network flow separation method are used, thus allow each SN locally and based on the information of its neighboring nodes performs optimal routing and balances bandwidth consumption in the network. The effectiveness of the proposed optimization model and the proposed distributed algorithm with multiple runs of simulation in terms of the number of Source SNs (SSNs) and Lagrange coefficient and step size have been investigated. The results show that the proposed model and algorithm, due to informed routing and NC, can improve the parameters of the average required time to find the route optimal, the total amount of virtual flow in network’s edges, the average latency end-to-end of the network, the consumed bandwidth, the average lifetime of the network and the consumed energy, or not very weak compared to other models. The proposed algorithm also has great scalability, because computations are done distributed and decentralized, and there is an insignificant dependence between the SNs.

کلیدواژه‌ها

Wireless Sensor Networks؛ Consumption bandwidth؛ Network coding؛ Virtual multicast flow؛ Optimization model

مراجع

[1] M. Khalily-Dermany, M. Shamsi, M. J. Najafi-Arani, "A convex optimization model for topology control in network-coding-based wireless-sensor networks," Ad Hoc Networks, Vol. 59, pp. 1-11, 2017.

[2] C. Fragouli and E. Soljanin, “NC Applications,” Now Publishers, 2008.

[3] T. Ho and D. S. Lun, “NC: an introduction,” Cambridge University Press, 2008.

[4] Y. Fan, "NC based information security in multi-hop wireless networks," Doctor of Philosophy Electrical and Computer Engineering University of Waterloo Waterloo, Ontario, Canada, 2010.

[5] V. Pandit, J. H. Jun, D. P. Agrawal, "Inherent security benefits of analog NC for the detection of byzantine attacks in multi-hop wireless networks," In IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS), pp. 697-702, 2011.

[6] Z. Ding, Z. Ma, and K. K. Leung, "Impact of NC on system delay for multisource-multi destination scenarios," IEEE Transactions on Vehicular Technology, Vol. 59, No. 2, pp. 831-841, 2010.

[7] M. Xiao and T. Aulin, "Optimal decoding and performance analysis of a noisy channel network with NC," IEEE Transactions on Communications, Vol. 57, No. 5, pp. 1402-1412, 2009.

[8] P. Gjanci, C. Petrioli, S. Basagni, C. A. Phillips, L. Bölöni, and D. Turgut, “Path finding for maximum value of information in multi-modal underwater WSNs,” IEEE Transactions on Mobile Computing, vol. 17, no. 2, pp. 404-418, 2018.

[9] S. Jaggi, P. A. Chou, and K. Jain, "Low complexity algebraic multicast network codes," In IEEE International Symposium on Information Theory, pp. 368-368, 2003.

[10] R. S. Youail, C. Wenqing, and T. Shaoguo, "Cost minimization for multi-source multi-sink NC," Zhang Jia Jie, Hunan, pp. 253- 258, 2008.

[11] M. Khalily-Dermany, M. Sabaei, and M. Shamsi. "Topology control in network–coding–based–multicast WSNs," International Journal of Sensor Networks, Vol. 17, No. 2, pp. 93-104, 2015.

[12] M. Khalily-Dermany, and M. Nadjafi-Arani, “Itinerary planning for mobile sinks in network-coding-based WSNs,” Computer Communications, vol. 111, pp. 1-13, 2017.

[13] S. Katti, H. Rahul, W. Hu, D. Katabi, M. Medard, and J. Crowcroft, "XORs in the air: practical wireless NC," IEEE/ACM Transaction on Networking, Vol. 16, No. 3, pp. 497-510, 2008.

[14] S. Y. R. Li, R. W. Yeung, and C. Ning, "Linear NC," IEEE Transactions on Information Theory, Vol. 49, No. 2, pp. 371-381, 2003.

[15] Z. Yang, M. Li, and W. Lou, "A NC approach to reliable broadcast in wireless mesh networks," In 4th International Conference on Wireless Algorithms, Systems, and Applications, WASA, Boston, MA, 2009.

[16] K. Fan, L. X. Li, and D. Y. Long, "Study of on-demand COPE-aware routing protocol in wireless mesh networks," Tongxin Xuebao/Journal on Communications, Vol. 30, No. 1, pp. 128-134, 2009.

[17] K. Chi, X. Jiang, and S. Horiguchi, "A more efficient COPE architecture for NC in multihop wireless networks," IEICE Transactions on Communications, Vol. E92-B, No. 3, pp. 766-775, 2009.

[18] M. Khalily-Dermany, and M. J. Nadjafi-Arani, “Itinerary planning for mobile sinks in network-coding-based WSNs,” Computer Communications, Vol. 111, pp. 1-13, 2017.

[19] D. S. Lun, "Minimum-cost multicast over coded packet networks," IEEE Transactions on Information Theory, Vol. 52, No. 6, pp. 2608-2623, 2006.

[20] V. Shah-Mansouri, and V. W. S. Wong, "Maximum-lifetime coding subgraph for multicast traffic in WSNs," In IEEE GLOBECOM Global Telecommunications Conference, New Orleans, pp. 497-502, 2008.

[21] S. Boyd and L. Vandenberghe, “Convex Optimization,” Cambridge University Press, 2004.

[22] E. Kharati, M. Khalily-D, and H. Kermajani, “Optimized sink control to increase the lifetime of ‎underwater ‎wireless sensor networks”. Computer and Knowledge Engineering‎, 2019. 9.‎

[23] M. Khalily-Dermany, “A convex programming for range assignment to optimize lifetime in network-coding-based-wireless-sensor networks,” International Journal of Wireless Information Networks, pp. 1-6, 2017.

[24] E. Kharati, , M. Khalily-D, and H. Kermajani, “Increasing the Value of Collected Data and Reducing Energy ‎Consumption by Using Network Coding and Mobile Sinks in Wireless Sensor Networks”. AUT Journal of Modeling and ‎Simulation, 2019.‎

[25] E. Kharati, , M. Khalily-D, and H. Kermajani, “Increasing the Amount of Collected Data using Network Coding and Continuous Movement of Mobile Sinks in Wireless Sensor Networks” , IET Networks, 12pp. DOI: 10.1049/iet-net.2019.0031.