Abstract
In this paper, we investigate the impacts of mobility on the characterization of energy consumption in wireless networks. Considering a linear wireless network deployed for an information-collecting purpose, which includes a fixed sink node and a number of mobile nodes, the analytical expressions of the energy consumption are derived for each mobile node, which either adopts multi-hop or opportunistic routing for packet transmission to the sink node. The derived expressions are applied to analyze the network lifetime. We also compare the multi-hop routing and the opportunistic routing in terms of energy consumption and network lifetime. Our results provide several insights into the interplay between mobility, routing strategy and energy consumption. Specifically, we find that a certain degree of mobility has a significant benefit to the efficient and balanced energy usage, and consequently improving the network lifetime.
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Notes
Note that the periodical signaling exchange is referred as proactive protocol. There also exists another paradigm, called reactive protocol, in which a node collects the neighboring information to find its next relay when a message is to be delivered to the sink. A comprehensive comparison of these two protocols in energy dissipation could be found in [4].
References
Azad, A., & Kamruzzaman, J. (2011). Energy-balanced transmission policies for wireless sensor networks. IEEE Transactions Mobile Computing, 10(7), 927–940.
Cassandras, C. G., Wang, T., & Pourazarm, S. (2014). Optimal routing and energy allocation for lifetime maximization of wirless sensor networks with nonideal batteries. IEEE Transactions Control of Network Systems, 1(1), 86–98.
Zuo, J., Dong, C., Ng, S., et al. (2015). Cross-layer aided energy-efficient routing design for ad hoc networks. IEEE Communications Surveys and Tutorials, 17(3), 1214–1238.
Zhao, Q., & Tong, L. (2005). Energy efficiency of large-scale wireless networks: Proactive versus reactive networking. IEEE Jounal Selected Areas in Communications, 23(5), 1100–1112.
Halder, S., & Bit, S. D. (2014). Enhancement of wireless sensor network lifetime by deploying heterogeneous nodes. Journal Network and Computer Applications, 38(1), 106–123.
Fan, T., Teng, G., & Huo, L. (2014). Deployment strategy of WSN based on mininmizing cost per unit area. Computer Communications, 38(1), 26–35.
Grossglauser, M., & Tse, D. (2002). Mobility increases the capacity of ad hoc wireless networks. IEEE/ACM Transactions Networking, 10(4), 477–486.
Sharma, G., Mazumdar, R., & Shroff, N. (2007). Delay and capacity tradeoffs in mobile ad hoc networks: A global perspective. IEEE/ACM Transactios on Networking, 15(5), 981–992.
Liu, B., Brass, P., et al. (2005). Mobility improves coverage of sensor networks. In Proceedings of ACM MobiHoc (pp. 300–308 ).
Wang, X., Lin, X., Wang, Q., & Luan, W. (2013). Mobility increases the connectivity of wireless networks. IEEE/ACM Transactions Networking, 21(2), 440–454.
Wang, D., & Abouzeid, A. A. (2012). On the cost of knowledge of mobility in dynamic networks: An information-theoretic approach. IEEE Transactions Mobile Computing, 11(6), 995–1006.
Cong, Y., Zhou, X., & Kennedy, R. (2015). Interference prediction in mobile ad hoc networks with a general mobility model. IEEE Transactions on Wireless Communications, 14(8), 4277–4290.
Wang, W., Srinivasan, V., & Chua, K. (2008). Extending the lifetime of wireless sensor networks through mobile relays. IEEE/ACM Transactions Networking, 16(5), 1108–1120.
Tashtarian, F., Moghaddam, M., et al. (2015). On maximizing the lifetime of wireless sensor networks in event-driven applications with mobile sinks. IEEE Transactions Vehicular Technology, 64(7), 3177–3189.
Cavirpunar, O., Kadioglu-Urtis, E., & Tavli, B. (2015). Optimal base station mobility patterns for wireless sensor network lifetime maximization. IEEE Sensors Journal, 15(11), 6592–6603.
Wang, C., Guo, S., & Yang, Y. (2016). An optimization framework for mobile data collection in energy-harvesting wireless sensor networks. IEEE Transactions Mobile Computing, 15(12), 2969–2986.
Pala, Z., Bicakci, K., & Tavli, B. (2013). Mobility helps energy balancing in wireless networks. In IEEE Military Communications Conference (pp. 293–298).
Shen, C., Tekin, C., & Schaar, M. (2016). A non-stochastic learning approach to energy efficient mobility management. IEEE Journal Selected Areas in Communications, 34(12), 3854–3868.
Qiao, G., Leng, S., Zhang, K., & Yang, K. (2016). Joint deployment and mobility management of energy harvesting small celles in heterogeneous networks. IEEE Access, 5, 183–196.
Mahboubi, H., Masoudimansour, W., et al. (2016). Maximum lifetime strategy for target monitoring with controlled node mobility in sensor networks with obstacles. IEEE Transactions Automatic Control, 61(11), 3493–3508.
Nain, P., Towsley, D., Liu, B., & Liu, Z. (2005). Properties of random direction models. In Proceedings of INFOCOM (pp. 1897–1907).
Samar, P., & Wicker, S. B. (2006). Link dynamics and protocol design in a multihop mobile environment. IEEE Transactions Mobile Computing, 5(9), 1156–1172.
Acknowledgements
This research was supported in part by NSF China (61471287), in part by the Key Scientific Research Projects of Henan Educational Committee (18B510022), and in part by the Development Project of Henan Provincial Department of Science and Technology (172102310124). The authors sincerely appreciate the editor's and reviewers' insightful and helpful comments.
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Xu, M., Yang, Q., Kwak, K.S. et al. Impact of mobility on energy consumption in wireless networks. Wireless Netw 25, 2249–2258 (2019). https://doi.org/10.1007/s11276-017-1646-3
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DOI: https://doi.org/10.1007/s11276-017-1646-3