Abstract
In recent years, the Internet of Things (IoT) has been introduced to offer promising solutions in many areas. A big challenge faced by the IoT is to integrate heterogeneous information sources and process information effectively. As an important element in information integration, temporal reasoning is highly related to the dynamic, sequential aspect of both the information integration and the decision making process. Focusing on temporal reasoning, this paper introduces a method to represent both qualitative and quantitative temporal constraints in a 2-dimensional (2-D) space. Meanwhile, an efficient constraint-based geometric (CG) algorithm for propagating constraints (including inherent constraints and constraint pairs) on events in a 2-D space is proposed. A geometric recombination and intersection (GRI) method, a part of the CG algorithm, is presented to propagate one constraint pair from a geometric point. The experimental results show that in terms of both constructed and realistic benchmarks, the CG algorithm outperforms the existing Floyd-Warshall’s algorithm with the time complexity of O(n 3), especially for benchmarks with a large number of events.
Similar content being viewed by others
References
Aigner, W., & Miksch, S. (2006). CareVis: integrated visualization of computerized protocols and temporal patient data. Artificial Intelligence in Medicine, 37(3), 203–218.
Allen, J. F. (1983). Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11), 832–843.
Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: a survey. Computer Networks, 54(15), 2787–2805. doi:10.1016/j.comnet.2010.05.010.
Barnaghi, P., Wang, W., Henson, C., & Taylor, K. (2012). Semantics for the internet of things: early progress and back to the future. International Journal on Semantic Web and Information Systems (IJSWIS), 8(1), 1–21.
Barreiro, J., Boyce, M., Frank, J., Iatauro, M., Kichkaylo, T., Morris, P., et al. (2012). EUROPA: A Platform for AI Planning, Scheduling, Constraint Programming, and Optimization. Paper presented at the In Proc. of 4th International Competition on Knowledge Engineering for Planning and Scheduling (ICKEPS).
Belhadji, S., & Isli, A. (1998). Temporal constraint satisfaction techniques in job shop scheduling problem solving. Constraints, 3(2–3), 203–211.
Bi, Z., & Cochran, D. (2014). Big data analytics with applications. Journal of Management Analytics, 1(4), 249–265.
Cai, H., Xu, L., Xu, B., & Cheng, X. (2014). IoT-based configurable information service platform for product lifecycle management. IEEE Transactions on Industrial Informatics, 10(2), 1558–1567.
Chen, S.-s. (1990). Advances in spatial reasoning (Vol. 2): Intellect Books.
Cooper, M. C., Maris, F., & Régnier, P. (2013). Managing temporal cycles in planning problems requiring concurrency. Computational Intelligence, 29(1), 111–128.
Cushing, W.A. (2012). When is temporal planning really temporal? Arizona State University.
Cushing, W., Kambhampati, S., & Weld, D.S. (2007) When is temporal planning really temporal? In Proceedings of the 20th international joint conference on Artifical intelligence (pp. 1852–1859): Morgan Kaufmann Publishers Inc.
Dechter, R., Meiri, I., & Pearl, J. (1991). Temporal constraint networks. Artificial Intelligence, 49(1), 61–95.
Duftschmid, G., Miksch, S., & Gall, W. (2002). Verification of temporal scheduling constraints in clinical practice guidelines. Artificial Intelligence in Medicine, 25(2), 93–121.
Gayraud, T., & Authie, G. (1992) A parallel algorithm for the all pairs shortest path problem. In Proceedings of the International Conference on Parallel Computing.
Ghallab, M., Nau, D., & Traverso, P. (2004). Automated planning: theory & practice: Elsevier.
Giannadakis, N., Rowe, A., Ghanem, M., & Guo, Y.-k. (2003). InfoGrid: providing information integration for knowledge discovery. Information Sciences, 155(3), 199–226.
Li, S., Xu, L. D., & Zhao, S. (2015). The internet of things: a survey. Information Systems Frontiers, 17(2), 243–259.
Ma, H.-D. (2011). Internet of things: objectives and scientific challenges. Journal of Computer Science and Technology, 26(6), 919–924.
Mackworth, A. K. (1977). Consistency in networks of relations. Artificial Intelligence, 8(1), 99–118.
Mackworth, A. K., & Freuder, E. C. (1985). The complexity of some polynomial network consistency algorithms for constraint satisfaction problems. Artificial Intelligence, 25(1), 65–74.
Ning, P., Jajodia, S., & Wang, X. S. (2001). Abstraction-based intrusion detection in distributed environments. ACM Transactions on Information and System Security (TISSEC), 4(4), 407–452.
Planken, L., De Weerdt, M., & Van Der Krogt, R. (2012). Computing all-pairs shortest paths by leveraging low treewidth. Journal Artificial Intelligence Research (JAIR), 43, 353–388.
Pujari, A.K., Kumari, G.V., & Sattar, A. (1999). INDU: An interval & duration network. In Advanced topics in artificial intelligence (pp. 291–303): Springer.
Ranise, S., & Tinelli, C. (2003) The SMT-LIB format: An initial proposal. In Proceedings of the 1st International Workshop on Pragmatics of Decision Procedures in Automated Reasoning (PDPAR’03), Miami, Florida (pp. 94–111).
Rit, J.-F. (1986) Propagating temporal constraints for scheduling. In AAAI (Vol. 86, pp. 383–388)
Tan, W., Chen, S., Li, J., Li, L., Wang, T., & Hu, X. (2014). A trust evaluation model for e-learning. Systems Research and Behavioral Science, 31(3), 353–365.
Tsang, E. (2014). Foundations of constraint satisfaction: the classic text: BoD–Books on Demand.
Ullberg, J., & Pecora, F. (2012) Propagating temporal constraints on sets of intervals. In Proceedings of ICAPS Workshop on Planning and Scheduling with Timelines (PSTL), Atibaia, Brazil (pp. 25–29)
Vermesan, O., & Friess, P. (2014). Internet of things-from research and innovation to market deployment: River Publishers.
Whitmore, A., Agarwal, A., & Xu, L. (2015). The Internet of things-a survey of topics and trends. Information Systems Frontiers, 17(2), 261–274.
Xu, R. (2004). Dynamic planning and scheduling algorithm based on temporal constraint network. Computer Integrated Manufacturing Systems, 10, 188–194.
Xu, L. (2014). Engineering informatics: state of the art and future trends. Frontiers of Engineering Management, 1(3), 276–288.
Xu, B., Xu, L., Cai, H., & Xie, C. (2014a). Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Transactions on Industrial Informatics, 10(2), 1578–1586.
Xu, L., He, W., & Li, S. (2014b). Internet of things in industries: a survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243.
Yan, H., Xu, L., Bi, Z., Pang, Z., Zhang, J., & Chen, Y. (2015). An emerging technology – wearable wireless sensor networks with applications in human health condition monitoring. Journal of Management Analytics, 2(2), 121–137.
Yu, X., Nguyen, B., Han, S., Chen, H., & Li, F. (2015). Electronic CRM and perceptions of unfairness. Information Technology & Management, 16, 351–362.
Acknowledgments
The authors gratefully acknowledge the support of the Civil Aerospace Research Project of China, National Basic Research Program of China (973 Program) (2012CB720000), the project of the National Natural Science Foundation of China (60803051, 60874094), and the Research Fund for the Doctoral Program of Higher Education (20111101110001).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, Z., Xu, R., Cui, P. et al. Geometry-based propagation of temporal constraints. Inf Syst Front 19, 855–868 (2017). https://doi.org/10.1007/s10796-016-9635-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10796-016-9635-0