On the Use of Graphs for Node Connectivity in Wireless Sensor Networks for Hostile Environments

[EN] Wireless sensor networks (WSNs) have been extensively studied in the literature. However, in hostile environments where node connectivity is severely compromised, the system performance can be greatly affected. In this work, we consider such a hostile environment where sensor nodes cannot directly communicate to some neighboring nodes. Building on this, we propose a distributed data gathering scheme where data packets are stored in different nodes throughout the network instead to considering a single sink node. As such, if nodes are destroyed or damaged, some information can still be retrieved. To evaluate the performance of the system, we consider the properties of different graphs that describe the connections among nodes. It is shown that the degree distribution of the graph has an important impact on the performance of the system. A teletraffic analysis is developed to study the average buffer size and average packet delay. To this end, we propose a reference node approach, which entails an approximation for the mathematical modeling of these networks that effectively simplifies the analysis and approximates the overall performance of the system.The authors wish to thank the Consejo Nacional de Ciencia y Tecnologia (CONACyT), the Comision de Operacion y Fomento de Actividades Academicas, Instituto Politecnico Nacional (COFAA-IPN, project numbers 20196225 and 20196678), and the Estimulos al Desempeno de los Investigadores del Instituto Politecnico Nacional (EDI-IPN) for the support given for this work. The work of V. Pla was supported by Grant PGC2018-094151-B-I00 (MCIU/AEI/FEDER, UE).García-González, E.; Chimal-Eguía, JC.; Rivero-Angeles, ME.; Pla, V. (2019). On the Use of Graphs for Node Connectivity in Wireless Sensor Networks for Hostile Environments. Journal of Sensors. 2019:1-22. https://doi.org/10.1155/2019/7409329S1222019Eren, T. (2017). The effects of random geometric graph structure and clustering on localizability of sensor networks. International Journal of Distributed Sensor Networks, 13(12), 155014771774889. doi:10.1177/1550147717748898Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009). Power-Law Distributions in Empirical Data. SIAM Review, 51(4), 661-703. doi:10.1137/070710111Hakimi, S. L. (1962). On Realizability of a Set of Integers as Degrees of the Vertices of a Linear Graph. I. Journal of the Society for Industrial and Applied Mathematics, 10(3), 496-506. doi:10.1137/011003

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