17,599 research outputs found

    Survey: energy efficient protocols using radio scheduling in wireless sensor network

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    An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey

    An approach for efficient energy consumption and delay guarantee MAC protocol for wireless sensor networks

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    Wireless sensor networks is an emergent technology that open a world of environment controlling, helping the administrator to predict and anticipate for any possible action that the environment could produce.Unfortunately these energy constrained miniatures must operate in a way that keeps fair consuming between sensor nodes to reach efficient network productivity.In this paper we present a MAC protocol that offers an improved energy efficient consumption and efficient delay guarantee operation. Simulation results shows that the proposed scheme provided better operation than S-MAC protocol

    Energy Efficient Handover Management in Cluster Based Wireless Sensor Network

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    Wireless sensors are compact-size, low power, inexpensive devices which are capable to measure local environmental conditions or other parameters such as temperature, acceleration, and forward such information to a sink for proper processing. Wireless sensor networks (WSNs) have been under development by both academic and industrial societies for a while. By moving toward applications such as the area of medical care and disaster response mobility in wireless sensor networks has attracted a lot of attentions. In energy constraint sensor network, mobility handling introduces unique challenges in aspects like resource management, coverage, routing protocols, security, etc. This paper, proposes an energy-efficient mobility-aware MAC protocol to handle node handover among different clusters. The simulation-based experiments show that the proposed protocol has better performance compared to the existing S-MAC method

    Energy Efficient Handover Management in Cluster Based Wireless Sensor Network

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    Wireless sensors are compact-size, low power, inexpensive devices which are capable to measure local environmental conditions or other parameters such as temperature, acceleration, and forward such information to a sink for proper processing. Wireless sensor networks (WSNs) have been under development by both academic and industrial societies for a while. By moving toward applications such as the area of medical care and disaster response mobility in wireless sensor networks has attracted a lot of attentions. In energy constraint sensor network, mobility handling introduces unique challenges in aspects like resource management, coverage, routing protocols, security, etc. This paper, proposes an energy-efficient mobility-aware MAC protocol to handle node handover among different clusters. The simulation-based experiments show that the proposed protocol has better performance compared to the existing S-MAC method

    Energy-Efficient Multi-Level and Distance-Aware Clustering Mechanism for WSNs

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    [EN] Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energyefficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy-efficient multi-level and distance-aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop-count-based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches.This 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, and by the Polytechnic University of Valencia, through the PAID-15-11 multidisciplinary projectsMehmood, A.; Khan, S.; Shams, B.; Lloret, J. (2015). Energy-Efficient Multi-Level and Distance-Aware Clustering Mechanism for WSNs. International Journal of Communication Systems. 28(5):972-989. https://doi.org/10.1002/dac.2720S972989285Sendra, 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.6.6.439-459Bri D Garcia M Lloret J Dini P Real deployments of wireless sensor networks Third International Conference on Sensor Technologies and Applications (SENSORCOMM 2009) 2009 8 23GUI, L., VAL, T., & WEI, A. (2011). A Novel Two-Class Localization Algorithm in Wireless Sensor Networks. Network Protocols and Algorithms, 3(3). doi:10.5296/npa.v3i3.863Rajeswari, A., & P.T, K. (2011). A Novel Energy Efficient Routing Protocols for Wireless Sensor Networks Using Spatial Correlation Based Collaborative Medium Access Control Combined with Hybrid MAC. Network Protocols and Algorithms, 3(4). doi:10.5296/npa.v3i4.1296Lloret, 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/s11390-008-9147-6Lloret, 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/s91210513LEHSAINI, M., GUYENNET, H., & FEHAM, M. (2010). Cluster-based Energy-efficient k-Coverage for Wireless Sensor Networks. Network Protocols and Algorithms, 2(2). doi:10.5296/npa.v2i2.325Liu, G., Xu, B., & Chen, H. (2011). Decentralized estimation over noisy channels in cluster-based wireless sensor networks. International Journal of Communication Systems, 25(10), 1313-1329. doi:10.1002/dac.1308Cheng, L., Chen, C., Ma, J., & Shu, L. (2011). Contention-based geographic forwarding in asynchronous duty-cycled wireless sensor networks. International Journal of Communication Systems, 25(12), 1585-1602. doi:10.1002/dac.1325Wang, X., & Qian, H. (2011). Hierarchical and low-power IPv6 address configuration for wireless sensor networks. International Journal of Communication Systems, 25(12), 1513-1529. doi:10.1002/dac.1318Zhang, D., Yang, Z., Raychoudhury, V., Chen, Z., & Lloret, J. (2013). An Energy-Efficient Routing Protocol Using Movement Trends in Vehicular Ad hoc Networks. The Computer Journal, 56(8), 938-946. doi:10.1093/comjnl/bxt028Chen, J.-S., Hong, Z.-W., Wang, N.-C., & Jhuang, S.-H. (2010). Efficient Cluster Head Selection Methods for Wireless Sensor Networks. Journal of Networks, 5(8). doi:10.4304/jnw.5.8.964-970Peiravi, A., Mashhadi, H. R., & Hamed Javadi, S. (2011). An optimal energy-efficient clustering method in wireless sensor networks using multi-objective genetic algorithm. International Journal of Communication Systems, 26(1), 114-126. doi:10.1002/dac.1336Zeynali, M., Mollanejad, A., & Khanli, L. M. (2011). Novel hierarchical routing protocol in wireless sensor network. Procedia Computer Science, 3, 292-300. doi:10.1016/j.procs.2010.12.050Heinzelman W Chandrakasan A Balakrishnan H Energy-efficient communication protocol for wireless microsensor networks 33rd Hawaii International Conference on System Sciences (HICSS) 2000 3005 3014Wang, A., Yang, D., & Sun, D. (2012). A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks. Computers & Electrical Engineering, 38(3), 662-671. doi:10.1016/j.compeleceng.2011.11.017Gou H Yoo Y An energy balancing LEACH algorithm for wireless sensor networks Proceedings of the 7th International Conference on Information Technology: New Generations (ITNG) 2010Ding, P., Holliday, J., & Celik, A. (2005). Distributed Energy-Efficient Hierarchical Clustering for Wireless Sensor Networks. Lecture Notes in Computer Science, 322-339. doi:10.1007/11502593_25Bandyopadhyay S Coyle E An energy-efficient hierarchical clustering algorithm for wireless sensor networks The 32nd IEEE International Conference on Computer Communication (INFOCOM 2003) 2003Jarry, A., Leone, P., Nikoletseas, S., & Rolim, J. (2011). Optimal data gathering paths and energy-balance mechanisms in wireless networks. Ad Hoc Networks, 9(6), 1036-1048. doi:10.1016/j.adhoc.2010.11.003Zhu, Y., Wu, W., Pan, J., & Tang, Y. (2010). An energy-efficient data gathering algorithm to prolong lifetime of wireless sensor networks. Computer Communications, 33(5), 639-647. doi:10.1016/j.comcom.2009.11.008Khamfroush H Saadat R Khademzadeh A Khamfroush K Lifetime increase for wireless sensor networks using cluster-based routing International Association of Computer Science and Information Technology-Spring Conference (IACSIT-SC 2009) 2009Li, H., Liu, Y., Chen, W., Jia, W., Li, B., & Xiong, J. (2013). COCA: Constructing optimal clustering architecture to maximize sensor network lifetime. Computer Communications, 36(3), 256-268. doi:10.1016/j.comcom.2012.10.006Aslam N Phillips W Robertson W Sivakumar S A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networks 4th IEEE Consumer Communications and Networking Conference, (CCNC 2007) 2007 650 654Yi, S., Heo, J., Cho, Y., & Hong, J. (2007). PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. Computer Communications, 30(14-15), 2842-2852. doi:10.1016/j.comcom.2007.05.034Yong, Z., & Pei, Q. (2012). A Energy-Efficient Clustering Routing Algorithm Based on Distance and Residual Energy for Wireless Sensor Networks. Procedia Engineering, 29, 1882-1888. doi:10.1016/j.proeng.2012.01.231Chuan-Chi W A minimum transmission energy consumption routing protocol for user-centric wireless networks 2011 1143 1148Kumar, D., Aseri, T. C., & Patel, R. B. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 662-667. doi:10.1016/j.comcom.2008.11.025Kim KT Moon SS Tree-Based Clustering (TBC) for energy efficient wireless sensor networks IEEE 24th International Conference on Advanced Information Networking and Applications Workshops (WAINA) 2010 680 685Yu, J., Qi, Y., Wang, G., & Gu, X. (2012). A cluster-based routing protocol for wireless sensor networks with nonuniform node distribution. AEU - International Journal of Electronics and Communications, 66(1), 54-61. doi:10.1016/j.aeue.2011.05.002Ye M Li C Wu J EECS: an Energy Efficient Clustering Scheme in wireless sensor networks 24th IEEE International Performance on Computing, and Communications Conference 2005 535 540Gautama N Lee W Pyun J Dynamic clustering and distance aware routing protocol for wireless sensor networks PE-WASUN'09 2009Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660-670. doi:10.1109/twc.2002.804190Lai, W. K., Fan, C. S., & Lin, L. Y. (2012). Arranging cluster sizes and transmission ranges for wireless sensor networks. Information Sciences, 183(1), 117-131. doi:10.1016/j.ins.2011.08.029Pantazis, N. A., Vergados, D. J., Vergados, D. D., & Douligeris, C. (2009). Energy efficiency in wireless sensor networks using sleep mode TDMA scheduling. Ad Hoc Networks, 7(2), 322-343. doi:10.1016/j.adhoc.2008.03.006OMNeT++ Community Documentation and Tutorials of omnet++ http://www.omnetpp.org/Castallia Documentation and Tutorials of Castalia Simulator for WSN and BAN http://castalia.research.nicta.com.au/index.php/en/Research Group on Computer Networks and Multimedia Communication UFPA - Brazil Download-Leach-v2-for-Castalia http://www.gercom.ufpa.br/index.php?option=com_filecabinet&view=files&id=1&Itemid=31&lang=p

    Energy-Efficiency Analysis of a Distributed Queuing Medium Access Control Protocol for Biomedical Wireless Sensor Networks in Saturation Conditions

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    The aging population and the high quality of life expectations in our society lead to the need of more efficient and affordable healthcare solutions. For this reason, this paper aims for the optimization of Medium Access Control (MAC) protocols for biomedical wireless sensor networks or wireless Body Sensor Networks (BSNs). The hereby presented schemes always have in mind the efficient management of channel resources and the overall minimization of sensors’ energy consumption in order to prolong sensors’ battery life. The fact that the IEEE 802.15.4 MAC does not fully satisfy BSN requirements highlights the need for the design of new scalable MAC solutions, which guarantee low-power consumption to the maximum number of body sensors in high density areas (i.e., in saturation conditions). In order to emphasize IEEE 802.15.4 MAC limitations, this article presents a detailed overview of this de facto standard for Wireless Sensor Networks (WSNs), which serves as a link for the introduction and initial description of our here proposed Distributed Queuing (DQ) MAC protocol for BSN scenarios. Within this framework, an extensive DQ MAC energy-consumption analysis in saturation conditions is presented to be able to evaluate its performance in relation to IEEE 802.5.4 MAC in highly dense BSNs. The obtained results show that the proposed scheme outperforms IEEE 802.15.4 MAC in average energy consumption per information bit, thus providing a better overall performance that scales appropriately to BSNs under high traffic conditions. These benefits are obtained by eliminating back-off periods and collisions in data packet transmissions, while minimizing the control overhead

    HEH-BMAC: hybrid polling MAC protocol for WBANs operated by human energy harvesting

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    This paper introduces human energy harvesting medium access control (MAC) protocol (HEH-BMAC), a hybrid polling MAC suitable for wireless body area networks powered by human energy harvesting. The proposed protocol combines two different medium access methods, namely polling (ID-polling) and probabilistic contention access, to adapt its operation to the different energy and state (active/inactive) changes that the network nodes may experience due to their random nature and the time variation of the energy harvesting sources. HEH-BMAC exploits the packet inter-arrival time and the energy harvesting rate information of each node to implement an efficient access scheme with different priority levels. In addition, our protocol can be applied dynamically in realistic networks, since it is adaptive to the topology changes, allowing the insertion/removal of wireless sensor nodes. Extensive simulations have been conducted in order to evaluate the protocol performance and study the throughput and energy tradeoffs.Peer ReviewedPostprint (author's final draft

    Optimization and verification of the TR-MAC protocol for wireless sensor networks

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    Energy-efficiency is an important requirement in the design of communication protocols for wireless sensor networks (WSN). TR-MAC is an energy-efficient medium access control (MAC) layer protocol for low power WSN that exploits transmitted-reference (TR) modulation in the physical layer. The underlying TR modulation in TR-MAC provides faster synchronization and signal acquisition without requiring channel estimation and complex rake receiver in the receiver side. TR modulation also enables multiple access for a pair of nodes using different frequency offsets. This paper introduces an explicit expression that allows the TR-MAC protocol to minimize its energy consumption, depending on the experienced traffic load. Furthermore, an implementation of the protocol in the OMNeT++ simulator with MiXiM simulation framework is introduced, and analytical results introduced in [13] are verified by simulation results obtained using the simulator

    Y-MAC: An Energy-Efficient Multi-channel MAC Protocol for Dense Wireless Sensor Networks

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    As the use of wireless sensor networks (WSNs) becomes widespread, node density tends to increase. This poses a new challenge for Medium Access Control (MAC) protocol design. Although traditional MAC protocols achieve low-power operation, they use only a single channel which limits their performance. Several multi-channel MAC protocols for WSNs have been recently proposed. One of the key observations is that these protocols are less energy efficient than single-channel MAC protocols under light traffic conditions. In this paper, we propose an energy efficient multi-channel MAC protocol, Y-MAC, for WSNs. Our goal is to achieve both high performance and energy efficiency under diverse traffic conditions. In contrast to most of previous multi-channel MAC protocols for WSNs, we implemented Y-MAC on a real sensor node platform and conducted extensive experiments to evaluate its performance. Experimental results show that Y-MAC is energy efficient and maintains high performance under high-traffic conditions
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