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IET Wireless Sensor Systems

Volume 1, Issue 1, March 2011

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Volume 1, Issue 1

March 2011

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    • Relay node placement based on balancing power consumption in wireless sensor networks
      • Author(s): K. Lu ; G. Liu ; R. Mao ; Y. Feng
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 1 –6
      • DOI:  10.1049/iet-wss.2010.0004
      • Type: Article
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      • p. 1 –6 (6)
        To alleviate the traffic burden of sensor nodes and extend the network lifetime in wireless sensor networks, one approach is to deploy a large number of low-cost micro-relay nodes for routing data. The question is how to deploy a minimum number of relay nodes in the sensing field with network lifetime constraint. If relay nodes are uniformly placed, the issue of uneven power consumption arises as relay nodes closer to the sink are required to relay more data and thus will deplete their energy more quickly. Here, the authors study the relay node deployment problem under the assumption that the relay node has the same energy supply as the sensor node. Based on balancing power consumption among all sensor nodes and relay nodes, the authors deduce a relay node density function according to which relay nodes are placed in the sensing field. Simulation results show that the approach can achieve high energy utilisation and the network lifetime is significantly extended compared with uniformly placing relay nodes.
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      Channel estimation and multiple target tracking in wireless sensor networks based on quantised proximity sensors
      • Author(s): M. Mansouri ; H. Snoussi ; C. Richard
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 7 –14
      • DOI:  10.1049/iet-wss.2010.0008
      • Type: Article
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      • p. 7 –14 (8)
        This study presents a hybrid quantised variational/sequential Monte Carlo (SMC) method for multiple target tracking in quantised sensor networks, by considering channel estimation problem. SMC scheme is employed to attribute ambiguous observations to specific targets based on association probabilities. The associated measurements are then incorporated by the quantised variational filter (QVF), where the distribution of involved particles is approximated by a Gaussian distribution for each target. In the current work, the authors propose to jointly estimate the multiple target positions, the channel attenuation between one sensor and the cluster head, and optimise the number of quantisation bits used by the candidate sensor to quantise its measurement. The multiple target positions are estimated by using the hybrid quantised variational filtering/sequential Monte Carlo-based approach to data association. The channel attenuation is estimated by maximising the a posterior distribution and the quantisation is optimised by maximising the Fisher information. The computation of these criteria is based on the target position predictive distribution provided by the QVF algorithm. Numerical examples show that the quantisation combined with channel estimation improve the estimation performances and minimise the error estimation.
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      Adaptive sampling for energy-efficient collaborative multi-target tracking in wireless sensor networks
      • Author(s): Y.E.M. Hamouda  and  C. Phillips
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 15 –25
      • DOI:  10.1049/iet-wss.2010.0059
      • Type: Article
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      • p. 15 –25 (11)
        The problem of energy-efficient multi-target tracking (MTT) in wireless sensor networks is considered for sensor nodes with limited energy resources and sharp manoeuvring targets of different classes. A distributed multi-sensor multi-target tracking scheme is proposed for energy-efficient MTT with adaptive sampling. Behavioural data obtained while tracking the target including the target's previous locations are recorded as metadata to compute the sampling interval so that the tracking continuity and energy efficiency are improved. Following this, the next tasking sensors group is selected proactively according to the predicted target location probability distribution. A ‘main node’ is elected from the selected tasking sensors so that the energy efficiency is improved. Sensor nodes that detect more than one target at the same time determine their preferred target according to the target importance and the distance to the target. Simulation results show that compared to other well-known target tracking schemes, the proposed scheme can provide a significant improvement in energy efficiency while maintaining acceptable accuracy and seamless tracking, even with sharp manoeuvring targets. Additionally, more important targets experience better tracking accuracy.
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      Distributed photon network sensors via a wavelength router
      • Author(s): K. Tamee ; S. Mitatha ; P.P. Yupapin
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 26 –30
      • DOI:  10.1049/iet-wss.2010.0046
      • Type: Article
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      • p. 26 –30 (5)
        This study proposes a novel system of multi-photons generation and networking using an optical add/drop filter incorporating two nanoring resonators and the wavelength routers. By using some suitable parameters of the input and the control signals via an input and add ports, the intense optical fields can form and propagate within the system. Simulation results obtained have shown that multi-photons/atoms trapping pulses can be generated by using dark solitons and Gaussian pulses into the system, which can be used to form the multi-variable network for photons/atoms trapping and transportation via the wavelength routers. In application, the proposed system can be fabricated on a chip, in which the use for network sensors (communications) can be realised.
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      Piezoelectric-powered wireless sensor system with regenerative transmit mode
      • Author(s): S. Barker ; D. Brennan ; N.G. Wright ; A.B. Horsfall
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 31 –38
      • DOI:  10.1049/iet-wss.2010.0053
      • Type: Article
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      • p. 31 –38 (8)
        This work shows the first, piezoelectric energy harvester powered wireless sensor system, made using commercial off the shelf components, which is capable of continuous operation at an acceleration of 120 mg (1.17 m/s2) at 77 Hz, which is comparable to a small microwave oven. The authors' results show that a highly deployable system can be realised without the need for custom electronics or devices. By using different operating parameters of the onboard peripheral interface controller (PIC) processor and selectively activating components only when they are required, the system awake time can be increased by over 49 times from that of an unoptimised system. This method also allows the onboard storage to recharge during the awake period and, above a certain acceleration, can lead to continuous operation without the need for a charging sleep period. It can also operate at an acceleration of only 40 mg with a system duty cycle of 5%.
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      Mobility-based clustering protocol for wireless sensor networks with mobile nodes
      • Author(s): S. Deng ; J. Li ; L. Shen
      • Source: IET Wireless Sensor Systems, Volume 1, Issue 1, p. 39 –47
      • DOI:  10.1049/iet-wss.2010.0084
      • Type: Article
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      • p. 39 –47 (9)
        In this study, the authors propose a mobility-based clustering (MBC) protocol for wireless sensor networks with mobile nodes. In the proposed clustering protocol, a sensor node elects itself as a cluster-head based on its residual energy and mobility. A non-cluster-head node aims at its link stability with a cluster head during clustering according to the estimated connection time. Each non-cluster-head node is allocated a timeslot for data transmission in ascending order in a time division multiple address (TDMA) schedule based on the estimated connection time. In the steady-state phase, a sensor node transmits its sensed data in its timeslot and broadcasts a joint request message to join in a new cluster and avoid more packet loss when it has lost or is going to lose its connection with its cluster head. Simulation results show that the MBC protocol can reduce the packet loss by 25% compared with the cluster-based routing (CBR) protocol and 50% compared with the low-energy adaptive clustering hierarchy-mobile (LEACH-mobile) protocol. Moreover, it outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.
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      Signal detection in passive wireless sensor networks based on back-propagation neural networks - RETRACTED

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