453 research outputs found

    A hop-count based positioning algorithm for wireless ad-hoc networks

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    We propose a range-free localization algorithm for a wireless ad-hoc network utilizing the hop-count metric’s ability to indicate proximity to anchors (i.e., nodes with known positions). In traditional sense, hop-count generally means the number of intermediate routers a datagram has to go through between its source and the destination node. We analytically show that hop-count could be used to indicate proximity relative to an anchor node. Our proposed algorithm is computationally feasible for resource constrained wireless ad-hoc nodes, and gives reasonable accuracy. We perform both real experiments and simulations to evaluate the algorithm’s performance. Experimental results show that our algorithm outperforms similar proximity based algorithms utilizing received signal strength and expected transmission count. We also analyze the impact of various parameters like the number of anchor nodes, placements of anchor nodes and varying transmission powers of the nodes on the hop-count based localization algorithm’s performance through simulation

    mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

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    Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de AndalucĂ­a P07-TIC-02476Junta de AndalucĂ­a TIC-570

    Not All Wireless Sensor Networks Are Created Equal: A Comparative Study On Tunnels

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    Wireless sensor networks (WSNs) are envisioned for a number of application scenarios. Nevertheless, the few in-the-field experiences typically focus on the features of a specific system, and rarely report about the characteristics of the target environment, especially w.r.t. the behavior and performance of low-power wireless communication. The TRITon project, funded by our local administration, aims to improve safety and reduce maintenance costs of road tunnels, using a WSN-based control infrastructure. The access to real tunnels within TRITon gives us the opportunity to experimentally assess the peculiarities of this environment, hitherto not investigated in the WSN field. We report about three deployments: i) an operational road tunnel, enabling us to assess the impact of vehicular traffic; ii) a non-operational tunnel, providing insights into analogous scenarios (e.g., underground mines) without vehicles; iii) a vineyard, serving as a baseline representative of the existing literature. Our setup, replicated in each deployment, uses mainstream WSN hardware, and popular MAC and routing protocols. We analyze and compare the deployments w.r.t. reliability, stability, and asymmetry of links, the accuracy of link quality estimators, and the impact of these aspects on MAC and routing layers. Our analysis shows that a number of criteria commonly used in the design of WSN protocols do not hold in tunnels. Therefore, our results are useful for designing networking solutions operating efficiently in similar environments

    Entropy based routing for mobile, low power and lossy wireless sensors networks

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    [EN] Routing protocol for low-power and lossy networks is a routing solution specifically developed for wireless sensor networks, which does not quickly rebuild topology of mobile networks. In this article, we propose a mechanism based on mobility entropy and integrate it into the corona RPL (CoRPL) mechanism, which is an extension of the IPv6 routing protocol for low-power and lossy networks (RPL). We extensively evaluated our proposal with a simulator for Internet of Things and wireless sensor networks. The mobility entropy-based mechanism, called CoRPL+E, considers the displacement of nodes as a deciding factor to define the links through which nodes communicate. Simulation results show that the proposed mechanism, when compared to CoRPL mechanism, is effective in reducing packet loss and latency in simulated mobile routing protocol for low-power and lossy networks. From the simulation results, one can see that the CoRPL+E proposal mechanism provides a packet loss reduction rate of up to 50% and delays reduction by up to 25% when compared to CoRPL mechanism.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by SIDIA Institute of Science and Technology, by Coordenacao de Aperfeicxoamento de Pessoal de Nivel Superior (CAPES), by Fundacao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM)-support programs (Programa Primeiros Projetos (PPP) and Programa de Tecnologia da Informacao na Amazonia (PROTI)-Amazonia-Mobilidade), by Camara Tecnica de Reconstrucao e Recuperacao de Infraestrutura (CT-INFRA) of Ministerio da Ciencia, Tecnologia, Inovacoes e Comunicacoes(MCTI)/Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), and by Secretaria de Estado de Ciencia, Tecnologia e Inovacao Amazonas (SECTI-AM) and Government of Amazon State, Brazil.Carvalho, C.; Mota, E.; Ferraz, E.; Seixas, P.; Souza, P.; Tavares, V.; Lucena Filho, W.... (2019). Entropy based routing for mobile, low power and lossy wireless sensors networks. International Journal of Distributed Sensor Networks (Online). 15(7):1-19. https://doi.org/10.1177/1550147719866134S119157Blanco-Novoa, O., Fernández-Caramés, T., Fraga-Lamas, P., & Castedo, L. (2018). A Cost-Effective IoT System for Monitoring Indoor Radon Gas Concentration. Sensors, 18(7), 2198. doi:10.3390/s18072198Ding, X., Tian, Y., & Yu, Y. (2016). A Real-Time Big Data Gathering Algorithm Based on Indoor Wireless Sensor Networks for Risk Analysis of Industrial Operations. IEEE Transactions on Industrial Informatics, 12(3), 1232-1242. doi:10.1109/tii.2015.2436337Rashid, B., & Rehmani, M. H. (2016). Applications of wireless sensor networks for urban areas: A survey. Journal of Network and Computer Applications, 60, 192-219. doi:10.1016/j.jnca.2015.09.008Laurindo, S., Moraes, R., Nassiffe, R., Montez, C., & Vasques, F. (2018). An Optimized Relay Selection Technique to Improve the Communication Reliability in Wireless Sensor Networks. Sensors, 18(10), 3263. doi:10.3390/s18103263Airehrour, D., Gutierrez, J., & Ray, S. K. (2016). Secure routing for internet of things: A survey. Journal of Network and Computer Applications, 66, 198-213. doi:10.1016/j.jnca.2016.03.006Mesodiakaki, A., Zola, E., Santos, R., & Kassler, A. (2018). Optimal user association, backhaul routing and switching off in 5G heterogeneous networks with mesh millimeter wave backhaul links. Ad Hoc Networks, 78, 99-114. doi:10.1016/j.adhoc.2018.05.008Marszałek, Z., Woźniak, M., & Połap, D. (2018). Fully Flexible Parallel Merge Sort for Multicore Architectures. Complexity, 2018, 1-19. doi:10.1155/2018/8679579Fotouhi, H., Moreira, D., & Alves, M. (2015). mRPL: Boosting mobility in the Internet of Things. Ad Hoc Networks, 26, 17-35. doi:10.1016/j.adhoc.2014.10.009Barcelo, M., Correa, A., Vicario, J. L., Morell, A., & Vilajosana, X. (2016). Addressing Mobility in RPL With Position Assisted Metrics. IEEE Sensors Journal, 16(7), 2151-2161. doi:10.1109/jsen.2015.2500916Bouaziz, M., Rachedi, A., & Belghith, A. (2019). EKF-MRPL: Advanced mobility support routing protocol for internet of mobile things: Movement prediction approach. Future Generation Computer Systems, 93, 822-832. doi:10.1016/j.future.2017.12.015Fotouhi, H., Moreira, D., Alves, M., & Yomsi, P. M. (2017). mRPL+: A mobility management framework in RPL/6LoWPAN. Computer Communications, 104, 34-54. doi:10.1016/j.comcom.2017.01.020Iova, O., Picco, P., Istomin, T., & Kiraly, C. (2016). RPL: The Routing Standard for the Internet of Things... Or Is It? IEEE Communications Magazine, 54(12), 16-22. doi:10.1109/mcom.2016.1600397cmFotouhi, H., Alves, M., Zamalloa, M. Z., & Koubaa, A. (2014). Reliable and Fast Hand-Offs in Low-Power Wireless Networks. IEEE Transactions on Mobile Computing, 13(11), 2620-2633. doi:10.1109/tmc.2014.2307867Kamgueu, P. O., Nataf, E., & Ndie, T. D. (2018). Survey on RPL enhancements: A focus on topology, security and mobility. Computer Communications, 120, 10-21. doi:10.1016/j.comcom.2018.02.011Park, J., Kim, K.-H., & Kim, K. (2017). An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility. Sensors, 17(4), 899. doi:10.3390/s17040899Stanoev, A., Filiposka, S., In, V., & Kocarev, L. (2016). Cooperative method for wireless sensor network localization. Ad Hoc Networks, 40, 61-72. doi:10.1016/j.adhoc.2016.01.003Wallgren, L., Raza, S., & Voigt, T. (2013). Routing Attacks and Countermeasures in the RPL-Based Internet of Things. International Journal of Distributed Sensor Networks, 9(8), 794326. doi:10.1155/2013/794326Raza, S., Wallgren, L., & Voigt, T. (2013). SVELTE: Real-time intrusion detection in the Internet of Things. Ad Hoc Networks, 11(8), 2661-2674. doi:10.1016/j.adhoc.2013.04.014Zhang, K., Liang, X., Lu, R., & Shen, X. (2014). Sybil Attacks and Their Defenses in the Internet of Things. IEEE Internet of Things Journal, 1(5), 372-383. doi:10.1109/jiot.2014.2344013Mayzaud, A., Sehgal, A., Badonnel, R., Chrisment, I., & Schönwälder, J. (2015). Mitigation of topological inconsistency attacks in RPL-based low-power lossy networks. International Journal of Network Management, 25(5), 320-339. doi:10.1002/nem.1898Navidi, W., & Camp, T. (2004). Stationary distributions for the random waypoint mobility model. IEEE Transactions on Mobile Computing, 3(1), 99-108. doi:10.1109/tmc.2004.126182

    Electronically-switched Directional Antennas for Low-power Wireless Networks: A Prototype-driven Evaluation

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    We study the benefits of electronically-switched directional antennas in low-power wireless networks. This antenna technology may improve energy efficiency by increasing the communication range and by alleviating contention in directions other than the destination, but in principle requires a dedicated network stack. Unlike most existing works, we start by characterizing a real-world antenna prototype, and apply this to an existing low-power wireless stack, which we adapt with minimal changes. Our results show that: i) the combination of a low-cost directional antenna and a conventional network stack already brings significant performance improvements, e.g., nearly halving the radio-on time per delivered packet; ii) the margin of improvement available to alternative clean-slate protocol designs is similarly large and concentrated in the control rather than the data plane; iii) by artificially modifying our antenna's link-layer model, we can point at further potential benefits opened by different antenna designs
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