- -

Systems and algorithms for wireless sensor networks based on animal and natural behavior

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Systems and algorithms for wireless sensor networks based on animal and natural behavior

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Sendra, Sandra es_ES
dc.contributor.author Parra Boronat, Lorena es_ES
dc.contributor.author Lloret, Jaime es_ES
dc.contributor.author Khan, Shafiullah es_ES
dc.date.accessioned 2016-05-26T17:12:02Z
dc.date.available 2016-05-26T17:12:02Z
dc.date.issued 2015
dc.identifier.issn 1550-1329
dc.identifier.uri http://hdl.handle.net/10251/64820
dc.description.abstract In last decade, there have been many research works about wireless sensor networks (WSNs) focused on improving the network performance as well as increasing the energy efficiency and communications effectiveness. Many of these new mechanisms have been implemented using the behaviors of certain animals, such as ants, bees, or schools of fish.These systems are called bioinspired systems and are used to improve aspects such as handling large-scale networks, provide dynamic nature, and avoid resource constraints, heterogeneity, unattended operation, or robustness, amongmanyothers.Therefore, thispaper aims to studybioinspired mechanisms in the field ofWSN, providing the concepts of these behavior patterns in which these new approaches are based. The paper will explain existing bioinspired systems in WSNs and analyze their impact on WSNs and their evolution. In addition, we will conduct a comprehensive review of recently proposed bioinspired systems, protocols, and mechanisms. Finally, this paper will try to analyze the applications of each bioinspired mechanism as a function of the imitated animal and the deployed application. Although this research area is considered an area with highly theoretical content, we intend to show the great impact that it is generating from the practical perspective. es_ES
dc.language Inglés es_ES
dc.publisher Hindawi Publishing Corporation es_ES
dc.relation.ispartof International Journal of Distributed Sensor Networks es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Wireless sensor networks es_ES
dc.subject Animal behavior es_ES
dc.subject Natural behavior es_ES
dc.subject Bioinspired systems es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Systems and algorithms for wireless sensor networks based on animal and natural behavior es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1155/2015/625972
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres es_ES
dc.description.bibliographicCitation Sendra, S.; Parra Boronat, L.; Lloret, J.; Khan, S. (2015). Systems and algorithms for wireless sensor networks based on animal and natural behavior. International Journal of Distributed Sensor Networks. 2015:1-19. doi:10.1155/2015/625972 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1155/2015/625972 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2015 es_ES
dc.relation.senia 309997 es_ES
dc.description.references Iram, R., Sheikh, M. I., Jabbar, S., & Minhas, A. A. (2011). Computational intelligence based optimization in wireless sensor network. 2011 International Conference on Information and Communication Technologies. doi:10.1109/icict.2011.5983561 es_ES
dc.description.references Lloret, J., Bosch, I., Sendra, S., & Serrano, A. (2011). A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing. Sensors, 11(6), 6165-6196. doi:10.3390/s110606165 es_ES
dc.description.references Lloret, J., Garcia, M., Bri, D., & Sendra, S. (2009). A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification. Sensors, 9(11), 8722-8747. doi:10.3390/s91108722 es_ES
dc.description.references Dasgupta, P. (2008). A Multiagent Swarming System for Distributed Automatic Target Recognition Using Unmanned Aerial Vehicles. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 38(3), 549-563. doi:10.1109/tsmca.2008.918619 es_ES
dc.description.references Quwaider, M., & Biswas, S. (2012). Delay Tolerant Routing Protocol Modeling for Low Power Wearable Wireless Sensor Networks. Network Protocols and Algorithms, 4(3). doi:10.5296/npa.v4i3.2054 es_ES
dc.description.references Sendra, S., Lloret, J., Garcia, M., & Toledo, J. F. (2011). Power Saving and Energy Optimization Techniques for Wireless Sensor Neworks (Invited Paper). Journal of Communications, 6(6). doi:10.4304/jcm.6.6.439-459 es_ES
dc.description.references Liu, M., & Song, C. (2012). Ant-Based Transmission Range Assignment Scheme for Energy Hole Problem in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 8(12), 290717. doi:10.1155/2012/290717 es_ES
dc.description.references Riva, G., & Finochietto, J. M. (2012). Pheromone-based In-Network Processing for Wireless Sensor Network Monitoring Systems. Network Protocols and Algorithms, 4(4). doi:10.5296/npa.v4i4.2206 es_ES
dc.description.references Garcia, M., Sendra, S., Lloret, J., & Canovas, A. (2011). Saving energy and improving communications using cooperative group-based Wireless Sensor Networks. Telecommunication Systems, 52(4), 2489-2502. doi:10.1007/s11235-011-9568-3 es_ES
dc.description.references Kim, J.-Y., Sharma, T., Kumar, B., Tomar, G. S., Berry, K., & Lee, W.-H. (2014). Intercluster Ant Colony Optimization Algorithm for Wireless Sensor Network in Dense Environment. International Journal of Distributed Sensor Networks, 10(4), 457402. doi:10.1155/2014/457402 es_ES
dc.description.references Dressler, F., & Akan, O. B. (2010). A survey on bio-inspired networking. Computer Networks, 54(6), 881-900. doi:10.1016/j.comnet.2009.10.024 es_ES
dc.description.references Atakan, B., & Akan, O. B. (2006). Immune System Based Distributed Node and Rate Selection in Wireless Sensor Networks. 2006 1st Bio-Inspired Models of Network, Information and Computing Systems. doi:10.1109/bimnics.2006.361806 es_ES
dc.description.references Di Pietro, R., & Verde, N. V. (2011). Introducing epidemic models for data survivability in Unattended Wireless Sensor Networks. 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks. doi:10.1109/wowmom.2011.5986165 es_ES
dc.description.references Marwaha, S., Indulska, J., & Portmann, M. (2009). Biologically Inspired Ant-Based Routing in Mobile Ad hoc Networks (MANET): A Survey. 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing. doi:10.1109/uic-atc.2009.95 es_ES
dc.description.references Jha, V., Khetarpal, K., & Sharma, M. (2011). A survey of nature inspired routing algorithms for MANETs. 2011 3rd International Conference on Electronics Computer Technology. doi:10.1109/icectech.2011.5942042 es_ES
dc.description.references Fernandez-Marquez, J. L., Di Marzo Serugendo, G., Montagna, S., Viroli, M., & Arcos, J. L. (2012). Description and composition of bio-inspired design patterns: a complete overview. Natural Computing, 12(1), 43-67. doi:10.1007/s11047-012-9324-y es_ES
dc.description.references Camilo, T., Carreto, C., Silva, J. S., & Boavida, F. (2006). An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks. Lecture Notes in Computer Science, 49-59. doi:10.1007/11839088_5 es_ES
dc.description.references Selvakennedy, S., Sinnappan, S., & Shang, Y. (2006). T-ANT: A Nature-Inspired Data Gathering Protocol for Wireless Sensor Networks. Journal of Communications, 1(2). doi:10.4304/jcm.1.2.22-29 es_ES
dc.description.references Almshreqi, A. M. S., Ali, B. M., Rasid, M. F. A., Ismail, A., & Varahram, P. (2012). An improved routing mechanism using bio-inspired for energy balancing in wireless sensor networks. The International Conference on Information Network 2012. doi:10.1109/icoin.2012.6164367 es_ES
dc.description.references Chen, G., Guo, T.-D., Yang, W.-G., & Zhao, T. (2006). An improved ant-based routing protocol in Wireless Sensor Networks. 2006 International Conference on Collaborative Computing: Networking, Applications and Worksharing. doi:10.1109/colcom.2006.361893 es_ES
dc.description.references Okdem, S., & Karaboga, D. (2006). Routing in Wireless Sensor Networks Using Ant Colony Optimization. First NASA/ESA Conference on Adaptive Hardware and Systems (AHS’06). doi:10.1109/ahs.2006.63 es_ES
dc.description.references Salehpour, A.-A., Mirmobin, B., Afzali-Kusha, A., & Mohammadi, S. (2008). An energy efficient routing protocol for cluster-based wireless sensor networks using ant colony optimization. 2008 International Conference on Innovations in Information Technology. doi:10.1109/innovations.2008.4781748 es_ES
dc.description.references Wen, Y., Chen, Y., & Pan, M. (2008). Adaptive ant-based routing in wireless sensor networks using Energy*Delay metrics. Journal of Zhejiang University-SCIENCE A, 9(4), 531-538. doi:10.1631/jzus.a071382 es_ES
dc.description.references Liao, W.-H., Kao, Y., & Wu, R.-T. (2011). Ant colony optimization based sensor deployment protocol for wireless sensor networks. Expert Systems with Applications, 38(6), 6599-6605. doi:10.1016/j.eswa.2010.11.079 es_ES
dc.description.references Pavai, K., Sivagami, A., & Sridharan, D. (2009). Study of Routing Protocols in Wireless Sensor Networks. 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies. doi:10.1109/act.2009.133 es_ES
dc.description.references Juan, L., Chen, S., & Chao, Z. (2007). Ant System Based Anycast Routing in Wireless Sensor Networks. 2007 International Conference on Wireless Communications, Networking and Mobile Computing. doi:10.1109/wicom.2007.603 es_ES
dc.description.references Wang, C., & Lin, Q. (2008). Swarm intelligence optimization based routing algorithm for Wireless Sensor Networks. 2008 International Conference on Neural Networks and Signal Processing. doi:10.1109/icnnsp.2008.4590326 es_ES
dc.description.references Jiang, H., Wang, M., Liu, M., & Yan, J. (2012). A quantum-inspired ant-based routing algorithm for WSNs. Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD). doi:10.1109/cscwd.2012.6221881 es_ES
dc.description.references Okazaki, A. M., & Frohlich, A. A. (2011). Ant-based Dynamic Hop Optimization Protocol: A routing algorithm for Mobile Wireless Sensor Networks. 2011 IEEE GLOBECOM Workshops (GC Wkshps). doi:10.1109/glocomw.2011.6162356 es_ES
dc.description.references Hui, X., Zhigang, Z., & Xueguang, Z. (2009). A Novel Routing Protocol in Wireless Sensor Networks Based on Ant Colony Optimization. 2009 International Conference on Environmental Science and Information Application Technology. doi:10.1109/esiat.2009.460 es_ES
dc.description.references AbdelSalam, H. S., & Olariu, S. (2012). BEES: BioinspirEd backbonE Selection in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 23(1), 44-51. doi:10.1109/tpds.2011.100 es_ES
dc.description.references Da Silva Rego, A., Celestino, J., dos Santos, A., Cerqueira, E. C., Patel, A., & Taghavi, M. (2012). BEE-C: A bio-inspired energy efficient cluster-based algorithm for data continuous dissemination in Wireless Sensor Networks. 2012 18th IEEE International Conference on Networks (ICON). doi:10.1109/icon.2012.6506592 es_ES
dc.description.references Neshat, M., Sepidnam, G., Sargolzaei, M., & Toosi, A. N. (2012). Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artificial Intelligence Review, 42(4), 965-997. doi:10.1007/s10462-012-9342-2 es_ES
dc.description.references Antoniou, P., Pitsillides, A., Blackwell, T., & Engelbrecht, A. (2009). Employing the flocking behavior of birds for controlling congestion in autonomous decentralized networks. 2009 IEEE Congress on Evolutionary Computation. doi:10.1109/cec.2009.4983153 es_ES
dc.description.references Ruihua, Z., Zhiping, J., Xin, L., & Dongxue, H. (2011). Double cluster-heads clustering algorithm for wireless sensor networks using PSO. 2011 6th IEEE Conference on Industrial Electronics and Applications. doi:10.1109/iciea.2011.5975688 es_ES
dc.description.references Kulkarni, R. V., Venayagamoorthy, G. K., & Cheng, M. X. (2009). Bio-inspired node localization in wireless sensor networks. 2009 IEEE International Conference on Systems, Man and Cybernetics. doi:10.1109/icsmc.2009.5346107 es_ES
dc.description.references Kulkarni, R. V., & Venayagamoorthy, G. K. (2010). Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(6), 663-675. doi:10.1109/tsmcc.2010.2049649 es_ES
dc.description.references Xin Song, Cuirong Wang, Wang, J., & Bin Zhang. (2010). A hierarchical routing protocol based on AFSO algorithm for WSN. 2010 International Conference On Computer Design and Applications. doi:10.1109/iccda.2010.5541265 es_ES
dc.description.references Gao, X. Z., Wu, Y., Zenger, K., & Huang, X. (2010). A Knowledge-Based Artificial Fish-Swarm Algorithm. 2010 13th IEEE International Conference on Computational Science and Engineering. doi:10.1109/cse.2010.49 es_ES
dc.description.references Wang, L., & Ma, L. (2011). A hybrid artificial fish swarm algorithm for Bin-packing problem. Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology. doi:10.1109/emeit.2011.6022829 es_ES
dc.description.references Yiyue, W., Hongmei, L., & Hengyang, H. (2012). Wireless Sensor Network Deployment Using an Optimized Artificial Fish Swarm Algorithm. 2012 International Conference on Computer Science and Electronics Engineering. doi:10.1109/iccsee.2012.453 es_ES
dc.description.references Yang, X.-S. (2010). A New Metaheuristic Bat-Inspired Algorithm. Studies in Computational Intelligence, 65-74. doi:10.1007/978-3-642-12538-6_6 es_ES
dc.description.references Goyal, S., & Patterh, M. S. (2013). Performance of BAT Algorithm on Localization of Wireless Sensor Network. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 6(3), 351-358. doi:10.24297/ijct.v6i3.4481 es_ES
dc.description.references Krishnanand, K. N., & Ghose, D. (2006). Glowworm swarm based optimization algorithm for multimodal functions with collective robotics applications. Multiagent and Grid Systems, 2(3), 209-222. doi:10.3233/mgs-2006-2301 es_ES
dc.description.references Apostolopoulos, T., & Vlachos, A. (2011). Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem. International Journal of Combinatorics, 2011, 1-23. doi:10.1155/2011/523806 es_ES
dc.description.references Liao, W.-H., Kao, Y., & Li, Y.-S. (2011). A sensor deployment approach using glowworm swarm optimization algorithm in wireless sensor networks. Expert Systems with Applications, 38(10), 12180-12188. doi:10.1016/j.eswa.2011.03.053 es_ES
dc.description.references Sun, Y., Jiang, Q., & Zhang, K. (2012). A clustering scheme for Reachback Firefly Synchronicity in wireless sensor networks. 2012 3rd IEEE International Conference on Network Infrastructure and Digital Content. doi:10.1109/icnidc.2012.6418705 es_ES
dc.description.references Zungeru, A. M., Ang, L.-M., & Seng, K. P. (2012). Termite-Hill. International Journal of Swarm Intelligence Research, 3(4), 1-22. doi:10.4018/jsir.2012100101 es_ES
dc.description.references KumarE, S., S. M., K., & Kumar B. P., V. (2014). Clustering Protocol for Wireless Sensor Networks based on Rhesus Macaque (Macaca mulatta) Animal's Social Behavior. International Journal of Computer Applications, 87(8), 20-27. doi:10.5120/15229-3754 es_ES
dc.description.references Breza, M., & McCann, J. A. (2008). Lessons in Implementing Bio-inspired Algorithms on Wireless Sensor Networks. 2008 NASA/ESA Conference on Adaptive Hardware and Systems. doi:10.1109/ahs.2008.72 es_ES
dc.description.references Aziz, N. A. B. A., Mohemmed, A. W., & Sagar, B. S. D. (2007). Particle Swarm Optimization and Voronoi diagram for Wireless Sensor Networks coverage optimization. 2007 International Conference on Intelligent and Advanced Systems. doi:10.1109/icias.2007.4658528 es_ES
dc.description.references Falcon, R., Li, X., Nayak, A., & Stojmenovic, I. (2012). A harmony-seeking firefly swarm to the periodic replacement of damaged sensors by a team of mobile robots. 2012 IEEE International Conference on Communications (ICC). doi:10.1109/icc.2012.6363859 es_ES
dc.description.references Antoniou, P., & Pitsillides, A. (2010). A bio-inspired approach for streaming applications in wireless sensor networks based on the Lotka–Volterra competition model. Computer Communications, 33(17), 2039-2047. doi:10.1016/j.comcom.2010.07.020 es_ES
dc.description.references Benahmed, K., Merabti, M., & Haffaf, H. (2012). Inspired Social Spider Behavior for Secure Wireless Sensor Networks. International Journal of Mobile Computing and Multimedia Communications, 4(4), 1-10. doi:10.4018/jmcmc.2012100101 es_ES
dc.description.references Alrajeh, N. A., & Lloret, J. (2013). Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 9(10), 351047. doi:10.1155/2013/351047 es_ES
dc.description.references Hussain, S., Matin, A. W., & Islam, O. (2007). Genetic Algorithm for Hierarchical Wireless Sensor Networks. Journal of Networks, 2(5). doi:10.4304/jnw.2.5.87-97 es_ES
dc.description.references Hussain, S., Matin, A. W., & Islam, O. (2007). Genetic Algorithm for Energy Efficient Clusters in Wireless Sensor Networks. Fourth International Conference on Information Technology (ITNG’07). doi:10.1109/itng.2007.97 es_ES
dc.description.references Ferentinos, K. P., & Tsiligiridis, T. A. (2007). Adaptive design optimization of wireless sensor networks using genetic algorithms. Computer Networks, 51(4), 1031-1051. doi:10.1016/j.comnet.2006.06.013 es_ES
dc.description.references Jia, J., Chen, J., Chang, G., & Tan, Z. (2009). Energy efficient coverage control in wireless sensor networks based on multi-objective genetic algorithm. Computers & Mathematics with Applications, 57(11-12), 1756-1766. doi:10.1016/j.camwa.2008.10.036 es_ES
dc.description.references Nan, G.-F., Li, M.-Q., & Li, J. (2007). Estimation of Node Localization with a Real-Coded Genetic Algorithm in WSNs. 2007 International Conference on Machine Learning and Cybernetics. doi:10.1109/icmlc.2007.4370265 es_ES
dc.description.references Saleem, K., Fisal, N., Abdullah, M. S., Zulkarmwan, A. B., Hafizah, S., & Kamilah, S. (2009). Proposed Nature Inspired Self-Organized Secure Autonomous Mechanism for WSNs. 2009 First Asian Conference on Intelligent Information and Database Systems. doi:10.1109/aciids.2009.75 es_ES
dc.description.references Jabbari, A., & Lang, W. (2010). Advanced Bio-inspired Plausibility Checking in a Wireless Sensor Network Using Neuro-immune Systems: Autonomous Fault Diagnosis in an Intelligent Transportation System. 2010 Fourth International Conference on Sensor Technologies and Applications. doi:10.1109/sensorcomm.2010.24 es_ES
dc.description.references Ponnusamy, V., & Abdullah, A. (2010). Biologically Inspired (Botany) Mobile Agent Based Self-Healing Wireless Sensor Network. 2010 Sixth International Conference on Intelligent Environments. doi:10.1109/ie.2010.46 es_ES
dc.description.references Li, J., Cui, Z., & Shi, Z. (2012). An Improved Artificial Plant Optimization Algorithm for Coverage Problem in WSN. Sensor Letters, 10(8), 1874-1878. doi:10.1166/sl.2012.2627 es_ES
dc.description.references Sendra, S., Llario, F., Parra, L., & Lloret, J. (2014). Smart Wireless Sensor Network to Detect and Protect Sheep and Goats to Wolf Attacks. Recent Advances in Communications and Networking Technology, 2(2), 91-101. doi:10.2174/22117407112016660012 es_ES
dc.description.references Sendra, S., Granell, E., Lloret, J., & Rodrigues, J. J. P. C. (2013). Smart Collaborative Mobile System for Taking Care of Disabled and Elderly People. Mobile Networks and Applications, 19(3), 287-302. doi:10.1007/s11036-013-0445-z es_ES
dc.description.references Garcia, M., Sendra, S., Lloret, G., & Lloret, J. (2011). Monitoring and control sensor system for fish feeding in marine fish farms. IET Communications, 5(12), 1682-1690. doi:10.1049/iet-com.2010.0654 es_ES
dc.description.references Sendra, S., Lloret, J., Rodrigues, J. J. P. C., & Aguiar, J. M. (2013). Underwater Wireless Communications in Freshwater at 2.4 GHz. IEEE Communications Letters, 17(9), 1794-1797. doi:10.1109/lcomm.2013.072313.131214 es_ES
dc.description.references Lloret, J., Sendra, S., Ardid, M., & Rodrigues, J. J. P. C. (2012). Underwater Wireless Sensor Communications in the 2.4 GHz ISM Frequency Band. Sensors, 12(4), 4237-4264. doi:10.3390/s120404237 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem