Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abstract
How to choose the optimal route path finding, enhance the communication capacity of the whole network for wireless sensor networks (WSNs), and prolong the lifetime of the network is a basic problem of WSNs. We draw an inspiration from the single-celled organism-Slime Mold physarum polycephalum of foraging process in this paper, combined with the traditional clustering algorithm to design routing scheme. The application of traditional clustering algorithm and mobile sink technology in WSNs is the basis of this scheme design. The simulation results show that compared with the existing routing protocol, the new scheme can effectively improve the self-adaptation of the network, reduce the energy consumption and improve the overall performance of the network under the complicated network environment.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Cao N, Liu P, Li G et al (2018) Evaluation models for the nearest closer routing protocol in wireless sensor networks. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2825441
Fan L, Lei X, Yang N, Duong TQ, Karagiannidis GK (2016) Secure multiple amplify-and-forward relaying with cochannel interference. IEEE J Sel Top Signal Process 10(8):1494–1505
CrossRef
Fan L, Lei X, Yang N, Duong TQ, Karagiannidis GK (2017) Secrecy cooperative networks with outdated relay selection over correlated fading channels. IEEE Trans Veh Technol 66(8):7599–7603
CrossRef
Gupta B, Agrawal DP, Yamaguchi S (2016) Handbook of research on modern cryptographic solutions for computer and cyber security. IGI Global, Hershey
CrossRef
He P, Deng Z, Gao C, Wang X, Li J (2017) Model approach to grammatical evolution: deep-structured analyzing of model and representation. Soft Comput 21(18):5413–5423
CrossRef
Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670
CrossRef
Houbraken M, Demeyer S (2013) Fault tolerant network design inspired by Physarum polycephalum. Nat Comput 12(2):277–289
MathSciNetCrossRef
Konstantopoulos C, Pantziou G (2012) A rendezvous-based approach enabling energy-efficient sensory data collection with mobile sinks. IEEE Trans Parallel Distrib Syst 23(5):809–817
CrossRef
Kropat E, Meyernieberg S (2014). Slime mold inspired evolving networks under uncertainty (SLIMO). In: Hawaii international conference on system sciences, pp 1153–1161
Kropat E, Meyernieberg S (2016) A multi-layered adaptive network approach for shortest path planning during critical operations in dynamically changing and uncertain environments, pp 1369–1378
Li K, Thomas K (2010) Slime mold inspired path formation protocol for wireless sensor networks. Lect Notes Comput Sci 6234:299–311
CrossRef
Li K, Thomas K, et al. (2008) Slime mold inspired protocol for wireless sensor networks. In: IEEE international conference on self-adaptive and self-organizing systems, pp 319–328
Nakayama H, Fadlullah ZM, Ansari N (2011) A novel scheme for WSAN sink mobility based on clustering and set packing techniques. IEEE Trans Autom Control 56(10):2381–2389
MathSciNetCrossRef
Nakagaki T, Tero A, Kobayashi R (2008) Computational ability of cells based on cell dynamics and adaptability. New Gener Comput 27(1):57–81
CrossRef
Nakagaki T, Yamada H, Tóth A (2000) Maze-solving by an amoeboid organism. Nature 407(6803):470
CrossRef
Plageras AP, Stergiou C, Psannis KE (2017) Efficient IoT-based sensor BIG data collection-processing and analysis in smart buildings. Future Gener Comput Syst 82:349–357
CrossRef
Rappaport TS (1996) Wireless communications: principles & practice. DBLP, New Jersey
MATH
Sarma HKD, Rai P, Deka B (2014) Energy efficient communication protocol for wireless sensor networks with mobile node. In: Recent advances and innovations in engineering, pp 1–6
Shah RC, Roy S, Jain S, Brunette W (2003) Data MULEs: modeling a three-tier architecture for sparse sensor networks. Ad Hoc Netw 1(2–3):215–233
CrossRef
Song Y, Liu L, Ma H (2012) A physarum-inspired algorithm for minimal exposure problem in wireless sensor networks. In: Wireless communications and networking conference, pp 2151–2156
Tero A, Kobayashi R, Nakagaki T (2007) A mathematical model for adaptive transport network in path finding by true slime mold. J Theoret Biol 244(4):553
MathSciNetCrossRef
Tero A, Takagi S, Saigusa T (2010) Rules for biologically inspired adaptive network design. Science 327(5964):439–42
MathSciNetCrossRef
Die B2B-Firmensuche für Industrie und Wirtschaft: Kostenfrei in Firmenprofilen nach Lieferanten, Herstellern, Dienstleistern und Händlern recherchieren.
Unternehmen haben das Innovationspotenzial der eigenen Mitarbeiter auch außerhalb der F&E-Abteilung erkannt. Viele Initiativen zur Partizipation scheitern in der Praxis jedoch häufig. Lesen Sie hier - basierend auf einer qualitativ-explorativen Expertenstudie - mehr über die wesentlichen Problemfelder der mitarbeiterzentrierten Produktentwicklung und profitieren Sie von konkreten Handlungsempfehlungen aus der Praxis. Jetzt gratis downloaden!
