The wireless sensor networking (WSN) systems have been used for several applications from target tracking to environment monitoring. Recently, there has been increased interest in the design of WSN protocols for delay-sensitive applications, such as military surveillance, health monitoring, and infrastructure security. In this paper, we apply gene regulatory networks (GRN) principles to the WSN system and analyze a reaction-diffusion mechanisms for decentralized node scheduling design. Using control theory, we verify that the proposed scheme guarantees system stability. Also, we provide conditions of system parameters to ensure system convergence and stability. Simulation results indicate that the proposed scheme achieves superior performance with energy balancing as well as desirable delay compared with other well-known schemes.
T.Bokareva, N.Bulusu and S.Jha, SASHA: Toward a self-healing hybrid sensor network architecture, in: Proc. 2nd IEEE Workshop Embed. Netw. Sens, 2005, pp. 71–78.
2.
H.Byun and J.Park, A gene regulatory network-inspired self-organizing control for wireless sensor networks, International Journal of Distributed Sensor Networks11 (2015), 789434.
3.
H.Byun and J.So, Node scheduling control inspired by epidemic theory for data dissemination in wireless sensor–actuator networks with delay constraints, IEEE Trans. on Wireless Communications15(3) (2016), 1794–1807. doi:10.1109/TWC.2015.2496596.
4.
C.Charalambous and S.Cui, A biologically inspired networking model for wireless sensor networks, IEEE Netw.24(3) (2010), 6–13. doi:10.1109/MNET.2010.5464221.
5.
S.Das, P.Koduru, X.Cai, S.Welch and V.Sarangan, The gene regulatory network: An application to optimal coverage in sensor networks, in: 10th Annual Conf. on Genetic and Evolutionary Computation, 2008, pp. 1461–1468.
6.
J.Degesys, I.Rose, A.Patel and R.Nagpal, DESYNC: Self-organizing desynchronization and TDMA on wireless sensor networks, in: Proc. 6th Int. Conf. Inform. Process. Sens. Netw, 2007, pp. 11–20.
7.
F.Dressler, Self-organized event detection in sensor networks using bio-inspired promoters and inhibitors, in: ACM/ICST International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2008), 2008.
8.
F.Dressler and O.B.Akan, A survey on bio-inspired networking, Computer Networks54(6) (2010), 881–900. doi:10.1016/j.comnet.2009.10.024.
9.
P.Ghosh, M.Mayo, V.Chaitankar, T.Habib and S.Das, Principles of genomic robustness inspire fault-tolerant WSN topologies: A network science based case study, in: 7th IEEE International Workshop on Sensor Networks and Systems for Pervasive Computing, 2011, pp. 160–165.
10.
H.Guo, Y.Meng and Y.Jin, A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network, BioSytems98(3) (2009), 193–203. doi:10.1016/j.biosystems.2009.05.003.
11.
Y.Jin, H.Guo and Y.Meng, Robustness analysis and failure recovery of a bio-inspired self-organizing multi-robot system, in: The 3rd IEEE International Conference on Self-Adaptive and Self-organizing Systems, 2009, pp. 154–164.
12.
Y.Jin and B.Sendhoff, Evolving in silico bistable and oscillaory dynamics for gene regulatory network motifs, in: IEEE/CEC Congress on Evolutionary Computation, 2008, 386–391.
13.
L.T.Macneil and A.J.Walhout, Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression, Genome Research21(5) (2011), 645–657. doi:10.1101/gr.097378.109.
14.
A.Markham and N.Trigoni, Discrete gene regulatory networks (dgrns): A novel approach to configuring sensor networks, in: Proc. of the 29th Conference on Information Communications (INFOCOM’10), 2010, pp. 641–649.
15.
A.Markham and N.Trigoni, The automatic evolution of distributed controller to configure sensor networks, Oxford Computer Journal54(3) (2011), 421–438. doi:10.1093/comjnl/bxq016.
16.
E.Mojlsness, D.H.Sharp and J.Reinitz, A connectionist model fo development, Journal of Theoretical Biology52 (1991), 429–453. doi:10.1016/S0022-5193(05)80391-1.
17.
N.A.Monk, J.A.Sherratt and M.R.Owen, Spatiotemporal patterning in models of juxtacrine intercellular signaling with feedback, Institute for Mathematics and Its Applications121 (2001), 165–193.
18.
A.Nazi, M.Raj, M.D.Francesco, G.Preetan and S.K.Das, Robust deployment of wireless sensor networks using gene regulatory networks, in: Distributed Computing and Networking, Lecture Notes in Computer Science, Vol. 7730, 2013, pp. 192–207. doi:10.1007/978-3-642-35668-1_14.
19.
S.Nolfi and D.Floreano, Evolutionary Robotics: The Biology, Intelligence and Technology of Self-Organizing Machine, MIT Press, 2000.
20.
T.Taylor, A genetic regulatory network-inspired real-time controller for a group of underwater robots, in: Proc. of the 8th Conference on Intelligent Autonomous System, 2014.
21.
X.Wang, G.Xing and Y.Yao, Dynamic duty cycle control for end-to-end delay guarantees in wireless sensor networks, in: International Workshop on Quality of Service (IWQoS), 2010, pp. 1–9.
