Abstract
Sensor network lifetime maximization can be solved using heuristic methods, but they produce only suboptimal sensor activity schedules. However, knowing the quality of these solutions, we can use methods for solving decision problems to find better solutions than these suboptimal ones. We apply an answer set programming (ASP) system to answer the question, “Is there a schedule of length k?” where k is at least one unit higher than the best schedule returned by the heuristic method. First, we convert the problem’s constraints and a particular data instance into a high-level constraint language theory. Then we use a grounder for this language and a solver for the language of grounder’s output to find a more extended schedule or determine that no such schedule exists. The paper presents the conversion rules and the experiments’ results with one of the ASP tools for selected classes of the SCP1 benchmark.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cardei, M.: Coverage problems in sensor networks. In: Pardalos, P.M., Du, D.-Z., Graham, R.L. (eds.) Handbook of Combinatorial Optimization, pp. 899–927. Springer, New York (2013). https://doi.org/10.1007/978-1-4419-7997-1_72
Dargie, W., Poellabauer, C.: Fundamentals of Wireless Sensor Networks: Theory and Practice. Wiley Series on Wireless Communications and Mobile Computing. Wiley (2010). https://doi.org/10.1002/9780470666388
Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Clingo = ASP + control: preliminary report. CoRR abs/1405.3694 (2014)
Luo, C., Hong, Y., Li, D., Wang, Y., Chen, W., Hu, Q.: Maximizing network lifetime using coverage sets scheduling in wireless sensor networks. Ad Hoc Netw. 98, 102037 (2020). https://doi.org/10.1016/j.adhoc.2019.102037
Mikitiuk, A., Trojanowski, K.: Maximization of the sensor network lifetime by activity schedule heuristic optimization. Ad Hoc Netw. 96, 101994 (2020). https://doi.org/10.1016/j.adhoc.2019.101994
Trojanowski, K., Mikitiuk, A., Kowalczyk, M.: Sensor network coverage problem: a hypergraph model approach. In: Nguyen, N.T., Papadopoulos, G.A., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds.) ICCCI 2017. LNCS (LNAI), vol. 10448, pp. 411–421. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67074-4_40
Wang, B.: Coverage Control in Sensor Networks. Computer Communications and Networks, Springer, Cham (2010). https://doi.org/10.1007/978-1-84800-328-6
Yetgin, H., Cheung, K.T.K., El-Hajjar, M., Hanzo, L.H.: A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Commun. Surv. Tutor. 19(2), 828–854 (2017). https://doi.org/10.1109/COMST.2017.2650979
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Mikitiuk, A., Trojanowski, K., Grzeszczak, J.A. (2023). Using Answer Set Programming to Improve Sensor Network Lifetime. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13588. Springer, Cham. https://doi.org/10.1007/978-3-031-23492-7_34
Download citation
DOI: https://doi.org/10.1007/978-3-031-23492-7_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-23491-0
Online ISBN: 978-3-031-23492-7
eBook Packages: Computer ScienceComputer Science (R0)