Abstract
The conflict-free data aggregation problem in an arbitrary wireless network is NP-hard, both in the case of a limited number of frequencies (channels) and with an unlimited number of channels. However, on graphs with a particular structure, this problem sometimes becomes polynomially solvable. For example, when the network is a square grid (lattice), at each node of which there is a sensor, and the transmission range does not exceed 2, the problem is polynomially solvable. In this paper, we consider the problem of conflict-free data aggregation in a square grid, when network elements use two frequencies, and the transmission range is at least 2. It consists in finding an energy-efficient conflict-free (we will give later the definition of a conflict) schedule of minimum length for the transfer of aggregated data from all vertices of the lattice to the center node (base station).
We find polynomially solvable cases, and also develop an efficient algorithm that builds a schedule with a guaranteed accuracy estimate. For example, when the transmission range is 2, the algorithm constructs either an optimal schedule or a schedule whose length exceeds the optimal latency by no more than 1. For a transmission range more than 2, an estimate of the reduction in the length of the schedule is obtained compared to the case when only one frequency is used.
The research is partly supported by the Russian Science Foundation (projects 18–71–00084, section 3 and 19–71–10012, sections 1, 2, 3.1, 4).
Submitted to Special Session 4 “Intractable Problems of Combinatorial Optimization, Computational Geometry, and Machine Learning: Algorithms and Theoretical Bounds”.
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References
Bagaa, M., et al.: Data aggregation scheduling algorithms in wireless sensor networks: solutions and challenges. IEE Commun. Surv. Tutor. 16(3), 1339–1368 (2014)
Bagaa, M., Younis, M., Badache, N.: Efficient data aggregation scheduling in wireless sensor networks with multi-channel links. In: MSWiM 2013, Barcelona, Spain, 3–8 November 2013 (2014). https://doi.org/10.1145/2507924.2507995
Chen, X., Hu, X., Zhu, J.: Minimum data aggregation time problem in wireless sensor networks. In: Jia, X., Wu, J., He, Y. (eds.) MSN 2005. LNCS, vol. 3794, pp. 133–142. Springer, Heidelberg (2005). https://doi.org/10.1007/11599463_14
Demirkol, I., Ersoy, C., Alagoz, F.: MAC protocols for wireless sensor networks: a survey. IEEE Commun. Mag. 44, 115–121 (2006)
Erzin, A., Pyatkin, A.: Convergecast scheduling problem in case of given aggregation tree. The complexity status and some special cases. In: 10th International Symposium on Communication Systems, Networks and Digital Signal Processing, Article 16, 6 p. IEEE-Xplore, Prague (2016)
Erzin, A.: Solution of the convergecast scheduling problem on a square unit grid when the transmission range is 2. In: Battiti, R., Kvasov, D.E., Sergeyev, Y.D. (eds.) LION 2017. LNCS, vol. 10556, pp. 50–63. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69404-7_4
Erzin, A., Plotnikov, R.: Conflict-free data aggregation on a square grid when transmission distance is not less than 3. In: Fernández Anta, A., Jurdzinski, T., Mosteiro, M.A., Zhang, Y. (eds.) ALGOSENSORS 2017. LNCS, vol. 10718, pp. 141–154. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-72751-6_11
Gagnon, J., Narayanan, L.: Minimum latency aggregation scheduling in wireless sensor networks. In: Gao, J., Efrat, A., Fekete, S.P., Zhang, Y. (eds.) ALGOSENSORS 2014. LNCS, vol. 8847, pp. 152–168. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46018-4_10
Ghods, F., et al.: MC-MLAS: multi-channel minimum latency aggregation scheduling in wireless sensor networks. Comput. Netw. 57, 3812–3825 (2013)
Guo, L., Li, Y., Cai, Z.: Minimum-latency aggregation scheduling in wireless sensor network. J. Comb. Optim. 31(1), 279–310 (2014). https://doi.org/10.1007/s10878-014-9748-7
Ha, N.P.K., Zalyubovskiy, V., Choo, H.: Delay-efficient data aggregation scheduling in duty-cycled wireless sensor networks. In Proceedings of ACM RACS, October 2012, pp. 203–208 (2012)
Incel, O.D., Ghosh, A., Krishnamachari, B., Chintalapudi, K.: Fast data collection in tree-based wireless sensor networks. IEEE Trans. Mob. Comput. 11(1), 86–99 (2012)
Li, J., et al.: Approximate holistic aggregation in wireless sensor networks. ACM Trans. Sensor Netw. 13(2), 1–24 (2017)
Malhotra, B., Nikolaidis, I., Nascimento, M.A.: Aggregation convergecast scheduling in wireless sensor networks. Wirel. Netw. 17, 319–335 (2011). https://doi.org/10.1007/s11276-010-0282-y
Plotnikov, R., Erzin, A., Zalyubovskiy, V.: Convergecast with unbounded number of channels. In: MATEC Web of Conferences, vol. 125, p. 03001 (2017). https://doi.org/10.1051/matecconf/20171250
de Souza, E., Nikolaidis, I.: An exploration of aggregation convergecast scheduling. Ad Hoc Netw. 11, 2391–2407 (2013)
Wan, P.-J. et al.: Minimum-latency aggregation scheduling in multihop wireless networks. In: Proceedings of ACM MOBIHOC, May 2009, pp. 185–194 (2009)
Wang, P., He, Y., Huang, L.: Near optimal scheduling of data aggregation in wireless sensor networks. Ad Hoc Netw. 11, 1287–1296 (2013)
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Erzin, A., Plotnikov, R. (2020). Two-Channel Conflict-Free Square Grid Aggregation. In: Kotsireas, I., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2020. Lecture Notes in Computer Science(), vol 12096. Springer, Cham. https://doi.org/10.1007/978-3-030-53552-0_18
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