25,970 research outputs found

    A QoS-Based Wireless Multimedia Sensor Cluster Protocol

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    Wireless Sensor Networks (WSNs) provide a wireless network infrastructure for sensed data transport in environments where wired or satellite technologies cannot be used. Because the embedded hardware of the sensor nodes has been improved very much in the last years and the number of real deployments is increasing considerably, they have become a reliable option for the transmission of any type of sensed data, from few sensed measures to multimedia data. This paper proposes a new protocol that uses an ad hoc cluster based architecture which is able to adapt the logical sensor network topology to the delivered multimedia stream features, guaranteeing the quality of the communications. The proposed protocol uses the quality of service (QoS) parameters, such as bandwidth, delay, jitter, and packet loss, of each type of multimedia stream as a basis for the sensor clusters creation and organization inside the WSN, providing end-to-end QoS for each multimedia stream. We present real experiments that show the performance of the protocol for several video and audio cases when it is runningThis work has been partially supported by the "Ministerio de Ciencia e Innovacion," through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental," Project TEC2011-27516. This work has also been partially supported by the Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, by the Government of Russian Federation, Grant 074-U01, and by National Funding from the Fundacao para a Ciencia e a Tecnologia (FCT) through the PEst-OE/EEI/LA0008/2013 Project.Díaz Santos, JR.; Lloret, J.; Jimenez, JM.; Rodrigues, JJPC. (2014). A QoS-Based Wireless Multimedia Sensor Cluster Protocol. International Journal of Distributed Sensor Networks. 2014:1-17. https://doi.org/10.1155/2014/480372S1172014Bri, D., Garcia, M., Lloret, J., & Dini, P. (2009). 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S., & Villalba, L. J. G. (2012). A distributed QoS mechanism for ad hoc network. International Journal of Ad Hoc and Ubiquitous Computing, 11(1), 25. doi:10.1504/ijahuc.2012.049282Çevik, T., & Zaim, A. H. (2013). A Multichannel Cross-Layer Architecture for Multimedia Sensor Networks. International Journal of Distributed Sensor Networks, 9(3), 457045. doi:10.1155/2013/457045Li, Z., Bi, J., & Chen, S. (2013). Traffic Prediction-Based Fast Rerouting Algorithm for Wireless Multimedia Sensor Networks. International Journal of Distributed Sensor Networks, 9(5), 176293. doi:10.1155/2013/176293Lloret, J., Palau, C., Boronat, F., & Tomas, J. (2008). Improving networks using group-based topologies. Computer Communications, 31(14), 3438-3450. doi:10.1016/j.comcom.2008.05.030Lloret, J., Garcia, M., Tomás, J., & Boronat, F. (2008). GBP-WAHSN: A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks. Journal of Computer Science and Technology, 23(3), 461-480. doi:10.1007/s11390-008-9147-6Lehsaini, M., Guyennet, H., & Feham, M. (2010). An efficient cluster-based self-organisation algorithm for wireless sensor networks. International Journal of Sensor Networks, 7(1/2), 85. doi:10.1504/ijsnet.2010.031852Lloret, J., Garcia, M., Bri, D., & Diaz, J. (2009). A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks. Sensors, 9(12), 10513-10544. doi:10.3390/s91210513Diaz, J. R., Lloret, J., Jimenez, J. M., & Sendra, S. (2014). MWAHCA: A Multimedia Wireless Ad Hoc Cluster Architecture. The Scientific World Journal, 2014, 1-14. doi:10.1155/2014/913046Wei, D., & Chan, H. (2006). Clustering Ad Hoc Networks: Schemes and Classifications. 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks. doi:10.1109/sahcn.2006.288583Yu, J. Y., & Chong, P. H. J. (2005). A survey of clustering schemes for mobile ad hoc networks. IEEE Communications Surveys & Tutorials, 7(1), 32-48. doi:10.1109/comst.2005.1423333Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14-15), 2826-2841. doi:10.1016/j.comcom.2007.05.024Boyinbode, O., Le, H., & Takizawa, M. (2011). A survey on clustering algorithms for wireless sensor networks. International Journal of Space-Based and Situated Computing, 1(2/3), 130. doi:10.1504/ijssc.2011.040339Ramachandran, L., Kapoor, M., Sarkar, A., & Aggarwal, A. (2000). Clustering algorithms for wireless ad hoc networks. Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications - DIALM ’00. doi:10.1145/345848.345860Chatterjee, M., Das, S. K., & Turgut, D. (2002). Cluster Computing, 5(2), 193-204. doi:10.1023/a:1013941929408Huang, Y.-M., Hsieh, M.-Y., & Wang, M.-S. (2007). Reliable transmission of multimedia streaming using a connection prediction scheme in cluster-based ad hoc networks. Computer Communications, 30(2), 440-452. doi:10.1016/j.comcom.2006.09.012Tang, S., & Li, W. (2006). QoS supporting and optimal energy allocation for a cluster based wireless sensor network. Computer Communications, 29(13-14), 2569-2577. doi:10.1016/j.comcom.2006.02.007Rosário, D., Costa, R., Paraense, H., Machado, K., Cerqueira, E., Braun, T., & Zhao, Z. (2012). A Hierarchical Multi-hop Multimedia Routing Protocol for Wireless Multimedia Sensor Networks. Network Protocols and Algorithms, 4(4). doi:10.5296/npa.v4i4.2121Diaz, J. R., Lloret, J., Jiménez, J. M., & Hammoumi, M. (2014). A new multimedia-oriented architecture and protocol for wireless ad hoc networks. International Journal of Ad Hoc and Ubiquitous Computing, 16(1), 14. doi:10.1504/ijahuc.2014.062486Meghanathan, N., & Mumford, P. (2013). Centralized and Distributed Algorithms for Stability-based Data Gathering in Mobile Sensor Networks. Network Protocols and Algorithms, 84. doi:10.5296/npa.v5i4.420

    Cross-layer Balanced and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

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    For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR, however, the computation complexity is not increased in CBRT.Comment: 14 pages, 17 figures, 31 formulas, IEEE Sensors Journal, 201

    Reliable routing scheme for indoor sensor networks

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    Indoor Wireless sensor networks require a highly dynamic, adaptive routing scheme to deal with the high rate of topology changes due to fading of indoor wireless channels. Besides that, energy consumption rate needs to be consistently distributed among sensor nodes and efficient utilization of battery power is essential. If only the link reliability metric is considered in the routing scheme, it may create long hops routes, and the high quality paths will be frequently used. This leads to shorter lifetime of such paths; thereby the entire network's lifetime will be significantly minimized. This paper briefly presents a reliable load-balanced routing (RLBR) scheme for indoor ad hoc wireless sensor networks, which integrates routing information from different layers. The proposed scheme aims to redistribute the relaying workload and the energy usage among relay sensor nodes to achieve balanced energy dissipation; thereby maximizing the functional network lifetime. RLBR scheme was tested and benchmarked against the TinyOS-2.x implementation of MintRoute on an indoor testbed comprising 20 Mica2 motes and low power listening (LPL) link layer provided by CC1000 radio. RLBR scheme consumes less energy for communications while reducing topology repair latency and achieves better connectivity and communication reliability in terms of end-to-end packets delivery performance

    Developing an Efficient DMCIS with Next-Generation Wireless Networks

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    The impact of extreme events across the globe is extraordinary which continues to handicap the advancement of the struggling developing societies and threatens most of the industrialized countries in the globe. Various fields of Information and Communication Technology have widely been used for efficient disaster management; but only to a limited extent though, there is a tremendous potential for increasing efficiency and effectiveness in coping with disasters with the utilization of emerging wireless network technologies. Early warning, response to the particular situation and proper recovery are among the main focuses of an efficient disaster management system today. Considering these aspects, in this paper we propose a framework for developing an efficient Disaster Management Communications and Information System (DMCIS) which is basically benefited by the exploitation of the emerging wireless network technologies combined with other networking and data processing technologies.Comment: 6 page

    A Secure Lightweight Approach of Node Membership Verification in Dense HDSN

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    In this paper, we consider a particular type of deployment scenario of a distributed sensor network (DSN), where sensors of different types and categories are densely deployed in the same target area. In this network, the sensors are associated with different groups, based on their functional types and after deployment they collaborate with one another in the same group for doing any assigned task for that particular group. We term this sort of DSN as a heterogeneous distributed sensor network (HDSN). Considering this scenario, we propose a secure membership verification mechanism using one-way accumulator (OWA) which ensures that, before collaborating for a particular task, any pair of nodes in the same deployment group can verify each other-s legitimacy of membership. Our scheme also supports addition and deletion of members (nodes) in a particular group in the HDSN. Our analysis shows that, the proposed scheme could work well in conjunction with other security mechanisms for sensor networks and is very effective to resist any adversary-s attempt to be included in a legitimate group in the network.Comment: 6 page

    GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

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    Wireless sensor networks (WSN) have recently received an increasing interest. They are now expected to be deployed for long periods of time, thus requiring software updates. Updating the software code automatically on a huge number of sensors is a tremendous task, as ''by hand'' updates can obviously not be considered, especially when all participating sensors are embedded on mobile entities. In this paper, we investigate an approach to automatically update software in mobile sensor-based application when no localization mechanism is available. We leverage the peer-to-peer cooperation paradigm to achieve a good trade-off between reliability and scalability of code propagation. More specifically, we present the design and evaluation of GCP ({\emph Gossip-based Code Propagation}), a distributed software update algorithm for mobile wireless sensor networks. GCP relies on two different mechanisms (piggy-backing and forwarding control) to improve significantly the load balance without sacrificing on the propagation speed. We compare GCP against traditional dissemination approaches. Simulation results based on both synthetic and realistic workloads show that GCP achieves a good convergence speed while balancing the load evenly between sensors
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