１周波ＧＰＳ受信機と無線ＬＡＮを用いた多点変位計測システムの開発

In underwater sensor networks (UWSNs), it is important to know the position of each sensor node to identify the place of event in the target ocean field. Ling et al. proposed a localization method that estimates the positions of sensor nodes based on trilateration from distances to anchors with accurate positions and the sensor nodes whose positions have already been estimated [1]. This method lacks the accuracy of estimated positions, since the estimation error is accumulated while new anchors are generated one after another. Erol et al. proposed the localization method using special buoys that can dive and surface in water[2]. Each buoy gets the location information by GPS while it is on the water surface. It can also dive and send the information to the neighboring underwater sensor node by the acoustic beacon to measure the distance. This method achieves accurate position estimation, but takes high cost because many buoys need to be deployed.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

SUMMARYLocation estimation of sensor nodes is an essential part of most applications for wireless sensor and actor networks. The ambiguous location information often makes the collected data useless in these applications. Environmental monitoring relies on an accurate position estimation to process or evaluate the collected data. In this paper, we present a novel and scalable approach for positioning of mobile sensor nodes with the goal of monitoring the Amazon river. The actors in the scenario are stationary and positioned at reachable spots on the land alongside the river whereas sensor nodes are thrown into the river to collect data such as water temperature, depth, and geographical features. The actors are not equipped with positioning adaptors, and they are only aware of their distances from the other actors. The sensor nodes collect data and forward it to the actors. While floating in the river, sensor nodes are often multiple hops away from the actors, which makes it challenging to apply traditional positioning techniques. Through extensive simulations, we show that the nodes can be efficiently positioned using a multi‐hop approach with local information exchange only. The introduced approach is also applied to a scenario, where monkey swarm monitoring is simulated, to test the generalizability of the algorithm. Copyright © 2011 John Wiley & Sons, Ltd.

Abilities in sensing, storing data, processing data and transmitting data has made Wireless Sensor Networks (WSN) to be applied in providing effective surveillance. Optimum sensor nodes placement in the surveillance area is needed since the number of sensor nodes that can be deployed are limited. The positions of sensor nodes must be able to provide maximum coverage. This paper describes an initial progress of an ongoing project. A sensor nodes placement technique which is based on minimax algorithm is proposed where surveillance locations will be monitored by the closest sensor nodes. Performance study has been carried out by comparing the performance of minimax and ideal value in terms of coverage ratio. Coverage ratio indicates the number of surveillance locations that received effective coverage. Simulation results obtained shows that coverage ratio produced by minimax technique is directly proportional to the number of sensor nodes and can be considered acceptable.

For wireless sensor networks, pairwise key establishment is a fundamental security service. However, establishing pairwise keys in wireless sensor networks is not a trivial thing, particularly due to the resource constraints on sensor nodes, and the nodes capture attack. In this paper, we propose a new efficient pairwise key management scheme based on the work of Liu et al. (Liu et. al., 2006). In our scheme, after deployment, a few sensor nodes are self-elected to become service nodes, which are responsible for key generation and distribution. The majority of the nodes are worker nodes, which are responsible for sensing and reporting data, and the keys shared by the nodes are distributed by service nodes. Compared with the scheme(LKE) provided by Liu et. al., our scheme does not need to learn the accurate locations of nodes. In addition, our scheme needs no computational overhead and requires less memory; the resilience against nodes capture attack is perfect. Simulation analysis is also provided.

The processing of kinematic GPS phase measurements calls for suitable methods to deal with the carrier-phase ambiguities. Resolving the integer ambiguities 'on the fly' is the key to centimetre navigation. Specialized search strategies are used to select the correct combination of integer ambiguities. These techniques are successful provided that non-biased measurements are available. The influence of systematic biases-such as ionosphere and multipath-can be minimized by applying certain restrictions (e.g., the maximum length of a baseline). Such restrictions may, however, reduce the number of potential applications. This paper presents an alternative approach. Although this approach cannot match ambiguity resolution 'on the fly' in terms of absolute position, it produces very high relative-position results (centimetre accuracy) within the trajectory itself. High-accuracy results are also achievable when ambiguity resolution is impossible e.g., at distances over 20 kilometres. Based upon the results of our tests, the paper discusses the limitations of ambiguity resolution 'on the fly' and the circumstances under which it might be preferable to choose alternative techniques-such as the one proposed in this paper-in order to obtain reliable, high-accuracy results. >

Gradient-based Routing for Energy Consumption Balance in Multiple Sinks-based Wireless Sensor Networks

In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to locate sensor nodes' positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. We do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. We show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity. The more the non-linearity, the better the localization. The localization for our network design proves better when we place anchor nodes to form right angles.

ODT: Optimal deadline-based trajectory for mobile sinks in WSN: A decision tree and dynamic programming approach

There are many researches on the mobile network based on IEEE 802.11 wireless devices. While wireless LAN devices are commonly used, they have been originally designed for office use and have no support for high mobility. Hence, the association establishment (the channel scanning of mobile nodes and the auth/association frame exchange between mobile nodes and access points) and the handoff often fails when we try to utilize the device for the communication between high speed vehicles and infrastructures. We proposed the method that realizes rapid association establishment and optimized handoffs to solve the problems in a compatible form with 802.11 protocol. We realized the proposed method by modifying the standard 802.11 specification of client side. On the evaluation in the actual environment, we showed better thoroughput with the proposed method than the one with the standard 802.11 specification.

Time of arrival (ToA) method is the most simple and intuitive algorithm and can be applicable for USNs. In case of ToA, the distance between two nodes is directly proportional to the time the acoustic signal takes to propagate from one sensor node to another sensor node. In this paper, ToA-based sensor localization system in USNs is proposed, which consists of ToA-based distance estimation, position computation using trilateration, and localization algorithm using recursive position estimation (RPE). For the performance evaluation of the proposed sensor localization system, various computer simulations are conducted according to the reference node's position, reference node's communication area, detecting area of sensor node, and the number of sensor node.

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Accurate localization of nodes in a sensor network is a crucial step before the sensor network can be utilized for various applications. This paper proposes a successive estimation method to self-localize the sensor nodes using time of arrival (TOA) measurements, through the aid of a few anchor nodes whose positions are known <emphasis emphasistype="italic">a priori</emphasis>. The successive nature of the proposed algorithm makes it attractive for distributed computation in a resource constrained environment. The proposed technique uses subsets of TOAs to obtain coarse sensor node estimates. Depending on available computation and transmission resources, the node positions are refined to improve their accuracies. The solution of the proposed node localization algorithm is algebraic and closed-form, which simplifies computation and avoids possible local convergence or divergence problems as in the traditional iterative approaches. A main benefit of the proposed algorithm is that although it is closed-form and performs successive estimation of the node locations, it is able to reach the CramÉr–Rao lower bound (CRLB) accuracy under white Gaussian measurement noise with sufficient SNR. This is confirmed by the theoretical analysis and corroborated by simulations. </para>

In this paper, we analyze the phenomena and problems that can occur in the sensor node localization of optics-based sensor networks using MEMS (Micro Electro Mechanical Systems) CCR (Corner Cube Retro-reflector). CCR reflects incident rays back in the opposite direction to calculate the distance between the sensor node and the base station and measuring the difference in source and sink detection time. The sensor node position can be measured from the ToF (Time of Flight) and the AoA (Angle of Arrival). However, when the MEMS CCR is used, reflected ray’s power is not strong enough to be detected. In the optics-based sensor network, sensor nodes are distributed randomly. Some sensor nodes cannot be detected due to the rectilinear propagation characteristics of light. To overcome these problems, we analyze the reflected ray’s power and verify the results experimentally. Based on the analysis, we replaced the photo detector to increase the detectable range. We also showed that multiple base stations can solve the randomly distributed sensor node issue and improve sensor node localization.

Background and Objectives The canalith reposition procedure (CRP) is used for the treatment of benign paroxysmal positional vertigo (BPPV) where the accuracy of position may affect the therapeutic efficacy. We investigate the accuracy of head position in CRP and its influencing factors during the procedure by measuring the position using inertial sensors and three dimensional remodeling.Subjects and Method We included 28 patients who were diagnosed as BPPV. To evaluate the accuracy of the CRP, we used the inertial sensor on the patient’s goggle used for videonystagmography. We evaluated the accuracy of the treatment compared to the textual treatment used during CRP. We also evaluated patient factors that affected the accuracy of head position as well as analyzing the correlation between the error rate and the successful treatment rate.Results While the average error rate was 12.6±5.8% for the PSCC group, it was 10.2±5.2% for the lateral semicircular canal (LSCC) group. For the posterior semicircular canal (PSCC) the group with body mass index (BMI), less than 25 patients had the lower error rate than the group with BMI greater than 25. There was no significant differences regarding the error rate according to BMI or age in the PSCC group. There is no significant differences regarding the error rate between those treated within 1 week and those over 1 week. For the LSCC delayed treatment group, there was no significant differences of error rate between the 1st and 2nd maneuver at each position.Conclusion For the Epley maneuver, the error rate of patients with high BMI is higher than those with low BMI. When the repeated barbeque maneuver was conducted, patients could have a more accurate position due to the learning effect. Care should be taken to ensure accurate CRP by considering various factors.