Abstract
We investigate the interesting impact of mobility on the problem of efficient wireless power transfer in ad hoc networks. We consider a set of mobile agents (consuming energy to perform certain sensing and communication tasks), and a single static charger (with finite energy) which can recharge the agents when they get in its range. In particular, we focus on the problem of efficiently computing the appropriate range of the charger with the goal of prolonging the network lifetime. We first demonstrate (under the realistic assumption of fixed energy supplies) the limitations of any fixed charging range and, therefore, the need for (and power of) a dynamic selection of the charging range, by adapting to the behavior of the mobile agents which is revealed in an online manner. We investigate the complexity of optimizing the selection of such an adaptive charging range, by showing that two simplified offline optimization problems (closely related to the online one) are NP-hard. To effectively address the involved performance trade-offs, we finally present a variety of adaptive heuristics, assuming different levels of agent information regarding their mobility and energy.
This work was supported by the Greek State Scholarships Foundation (IKY), and by a PhD scholarship from the Onassis Foundation. The third author would like to thank Ioannis Caragiannis for fruitful discussions at early stages of this work.
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Notes
- 1.
Notice that the mobility model we consider here is similar to the random way-point model, but we also allow for special restrictions in the movements of the agents that give birth to many interesting and extreme scenarios. We identify such worst-case scenarios in Sect. 3 and utilize them in our experimental evaluation in Sect. 5, where we consider probability distributions over both general and special mobility scenarios to test our algorithms in highly heterogeneous settings.
- 2.
We remark that the setup that we present here is only indicative. Actually, we have experimented with many different setups that differ on the number of agents and their battery capacity, the network size, and the initial energy of the charger. For all such setups, the relative performance of our algorithms is similar.
References
Angelopoulos, C.M., Buwaya, J., Evangelatos, O., Rolim, J.D.P.: Traversal strategies for wireless power transfer in mobile ad-hoc networks. In: Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), pp. 31–40 (2015)
Bettstetter, C., Resta, G., Santi, P.: The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Trans. Mob. Comput. 2(3), 257–269 (2003)
Bi, Z., Kan, T., Mi, C.C., Zhang, Y., Zhao, Z., Keoleian, G.A.: A review of wireless power transfer for electric vehicles: prospects to enhance sustainable mobility. Appl. Energy 179, 413–425 (2016)
Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wirel. Commun. Mob. Comput. 2(5), 483–502 (2002)
Dai, H., Chen, G., Wang, C., Wang, S., Wu, X., Wu, F.: Quality of energy provisioning for wireless power transfer. IEEE Trans. Parallel Distrib. Syst. 26(2), 527–537 (2015)
Dai, H., et al.: Safe charging for wireless power transfer. IEEE/ACM Trans. Netw. 25(6), 3531–3544 (2017)
Dai, H., et al.: SCAPE: safe charging with adjustable power. IEEE/ACM Trans. Netw. 26(1), 520–533 (2018)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman, San Francisco (1979)
He, S., Chen, J., Jiang, F., Yau, D.K.Y., Xing, G., Sun, Y.: Energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 12(10), 1931–1942 (2013)
Hrabcák, D., Matis, M., Dobos, L., Papaj, J.: Students social based mobility model for MANET-DTN networks. Mob. Inf. Syst. 2017, 2714595:1–2714595:13 (2017)
Kurs, A., Karalis, A., Moffatt, R., Joannopoulos, J.D., Fisher, P., Soljačić, M.: Wireless power transfer via strongly coupled magnetic resonances. Science 317(5834), 83–86 (2007)
Li, S., Mi, C.: Wireless power transfer for electric vehicle applications. IEEE J. Emerg. Sel. Top. Power Electron. 3, 4–17 (2015)
Lin, M., et al.: An ultrafast rechargeable aluminium-ion battery. Nature 520, 324 (2015)
Madhja, A., Nikoletseas, S.E., Raptis, T.P.: Hierarchical, collaborative wireless energy transfer in sensor networks with multiple mobile chargers. Comput. Netw. 97, 98–112 (2016)
Madhja, A., Nikoletseas, S.E., Raptopoulos, C., Tsolovos, D.: Energy aware network formation in peer-to-peer wireless power transfer. In: Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), pp. 43–50 (2016)
Musolesi, M., Hailes, S., Mascolo, C.: An ad hoc mobility model founded on social network theory. In: Proceedings of the 7th International Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems (MSWiM), pp. 20–24 (2004)
Nikoletseas, S.E., Raptis, T.P., Raptopoulos, C.: Radiation-constrained algorithms for wireless energy transfer in ad hoc networks. Comput. Netw. 124, 1–10 (2017)
Nikoletseas, S.E., Raptis, T.P., Raptopoulos, C.: Wireless charging for weighted energy balance in populations of mobile peers. Ad Hoc Netw. 60, 1–10 (2017)
Nikoletseas, S.E., Raptis, T.P., Souroulagkas, A., Tsolovos, D.: Wireless power transfer protocols in sensor networks: experiments and simulations. J. Sens. Actuator Netw. 6(2), 4 (2017)
Nikoletseas, S.E., Yang, Y., Georgiadis, A. (eds.): Wireless Power Transfer Algorithms, Technologies and Applications in Ad Hoc Communication Networks. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-319-46810-5
Vastardis, N., Yang, K.: An enhanced community-based mobility model for distributed mobile social networks. J. Ambient Intell. Humaniz. Comput. 5(1), 65–75 (2014)
Zhang, S., Wu, J., Lu, S.: Collaborative mobile charging. IEEE Trans. Comput. 64(3), 654–667 (2015)
Zhao, M., Li, J., Yang, Y.: Joint mobile energy replenishment with wireless power transfer and mobile data gathering in wireless rechargeable sensor networks. In: Nikoletseas, S., Yang, Y., Georgiadis, A. (eds.) Wireless Power Transfer Algorithms, Technologies and Applications in Ad Hoc Communication Networks, pp. 667–700. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46810-5_25
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Madhja, A., Nikoletseas, S., Voudouris, A.A. (2019). Mobility-Aware, Adaptive Algorithms for Wireless Power Transfer in Ad Hoc Networks. In: Gilbert, S., Hughes, D., Krishnamachari, B. (eds) Algorithms for Sensor Systems. ALGOSENSORS 2018. Lecture Notes in Computer Science(), vol 11410. Springer, Cham. https://doi.org/10.1007/978-3-030-14094-6_10
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