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The open-ended coaxial probe is the most common measurement tool used to dielectrically characterize biological tissues. Most healthy and malignant biological tissues are macroscopically heterogeneous, with the exception of a few tissues, such as liver. Heterogeneous biological samples are dielectrically characterized by defining the dielectric properties of each tissue type constituting the sample. In order to accurately characterize a specific tissue type with a coaxial probe, it is fundamental that only the tissue of interest is contained within the probe sensing volume, which is defined by the sensing radius and sensing depth. In the literature, several studies have investigated the sensing depth with bilayer or multilayer heterogeneous tissues. However, in this paper, we examine the sensing radius through concentrically heterogeneous tissues. In particular, samples composed of two different concentric tissues were modeled to estimate the minimum width of the homogenous tissue region required to accurately acquire the corresponding dielectric properties. As recent studies have indicated that the sensing radius depends on the dielectric properties of the interrogated tissue, in this paper, the sensing radius of a coaxial probe has been numerically quantified across a wide range of scenarios, involving different tissues with varying dielectric contrasts. The numerical results indicate that: 1) the sensing radius increases with the contrast in permittivity between the constituent tissues and 2) the sensing radius is highly dependent on the permittivity of the tissue closest to the inner conductor of the probe. Finally, the numerical outcome has been confirmed with dielectric measurements performed on animal tissues.

In accordance with the features of variety and disparity of traffic information, using wireless sensor network to monitor traffic environment, this paper proposes an optimization algorithm of applying wireless sensor to monitor traffic environment. In this paper, to optimize the coverage, we analyze the irregularity of network sensing areas based on environmental factors and propose a wireless sensor network optimization algorithm. According to the irregularity of network node sensing areas, we build an irregular network coverage model, divide the node monitoring area to improve the network coverage and make corrections to the coverage according to the network coverage connectivity and other features. The simulation test proves that the method proposed in this paper can avoid too many redundant nodes - it only requires a reasonable number of network nodes. This will reduce network energy costs and increase network connectivity without affecting the coverage, thus improving the network performance. the algorithm can satisfy the requirements of real-time acquisition, processing and remote supervision of traffic information. [ABSTRACT FROM AUTHOR]

The positioning techniques and adjusting sensing radius of nodes have an important role in improving the network coverage of hybrid wireless sensor networks. In this paper, we propose a novel optimized bidding-based algorithm that able to identify the coverage holes after deploying the stationary sensor nodes, also adjust sensing radius of nodes effectively based on the Delaunay triangulation. In addition, if necessary, an endeavor is made to relocate a portion of mobile nodes at the appropriate positions to cover the holes and reduce the overlapping area. Furthermore, the structure of created triangles i.e. acute and obtuse, layout vertices, region coverage status in before and after the relocation are considered in moving strategy of the proposed algorithm. Extensive simulations have been performed to validate the effectiveness of the proposed algorithm in terms of the coverage ratio, number of moved nodes, number of alive nodes and average of nodes movement. [ABSTRACT FROM AUTHOR]

In order to optimize the wireless sensor network coverage, this paper designs a coverage optimization strategy for wireless sensor network (EACS) based on energy-aware. Under the assumption that the geographic positions of sensor nodes are available, the proposed strategy consists of energy-aware and network coverage adjustment. It is restricted to conditions such as path loss, residual capacity and monitored area and according to awareness ability of sensors, it would adjust the monitored area, repair network hole and kick out the redundant coverage. The purpose is to balance the energy distribution of working nodes, reduce the number of "dead" nodes and balance network energy consumption. As a result, the network lifetime is expanded. Simulation results show that: EACS effectively reduces the number of working nodes, improves network coverage, lowers network energy consumption while ensuring the wireless sensor network coverage and connectivity, so as to balance network energy consumption. [ABSTRACT FROM AUTHOR]

In the present work, a Multi-Information Communication Field Model is proposed, which accurately describes the processes for which an Evacuation Assistant disseminates the information of each exit route using the strategy and evacuees receive, cognize and react to the multi-information. The information’s influence and Evacuation Assistant’s dynamic adjustment guiding strategy according to the crowd’s exit selection are highlighted. The effectiveness of the Evacuation Assistant’s guiding strategy and its influence factors, such as Evacuation Assistant’s sensing radius, evacuees’ prior exit preference and cognitive inertia, are considered and fully discussed. The simulations of crowd’s segregation process were performed in a T-shaped channel scenario and the conclusions indicated that the Evacuation Assistant’s guiding effect will be insufficient, optimum, or excessive for different sensing radius values, a larger sensing radius is not necessarily better, and the appropriate sensing radius could help the Evacuation Assistant achieve the segregation target. When the segregation target, the speed of the evacuees, and the evacuees’ exit preference vary, the sensing range should be changed accordingly. And the optimal sensing radius and its changing law were presented as well. [ABSTRACT FROM AUTHOR]

For wireless sensor networks, monitoring large inaccessible areas where deterministic node deployment is not possible, self-organized techniques are in demand to cover an area using optimal number of nodes. In this paper, given an initial random deployment of mobile sensor nodes, we propose a simple and novel technique for self-organized node movement to satisfy the coverage of the given region of interest using a least number of nodes, such that the maximum node displacement is minimized. We present a simple centralized algorithm and also a distributed version of it for node placement. Moreover, in case of a node failure, a distributed fault recovery algorithm is proposed to replace it locally utilizing the available free nodes. Analysis, simulation, and comparison studies show that the proposed algorithms with less neighborhood information result in significant improvement in terms of average and maximum displacement of a node, rounds of communication, and number of active nodes. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are commonly used in surveillance to sense the event of interest in the monitoring field and report it to the sink in a timely manner. In Area coverage, network monitors the Area of interest and recognizes any intruder attempting to cross the monitoring Area. In this paper, we have analyzed the intruder detection probability with respect to network parameters such as sensing radius, node density. We also investigated the detection probability related to speed of intruder, availability of sensor nodes along with the time frame required to identify the intruder. In addition, we also discussed the k-detection probability to make the system more reliable. Furthermore in this paper we have also developed the analytical framework for the expected hop count in multi-hop WSN . [ABSTRACT FROM AUTHOR]

Interference can cause serious problems in our daily life. Traditional ways in localizing a target can't work well when it comes to the source of interference for it may take an uncooperative or even resistant attitude towards localization. To tackle this issue, we take the BPSN (Binary Proximity Sensor Networks) and consider a passive way in this paper. No cooperation is needed and it is based on simple sensor node suitable for large-scale deployment. By dividing the sensing field into different patches, when enough patches are formed, good localization accuracy can be achieved with high resolution. Then we analyze the relationship between sensing radius and localization error, we find that in a finite region where edge effect can't be ignored, the trend between sensing radius and localization error is not always consistent. Through theoretical analysis and simulation, we explore to determine the best sensing radius to achieve high localization accuracy. [ABSTRACT FROM AUTHOR]

In event localization, wireless sensors try to locate the source of an event from its emitted power. This is more challenging than sensor localization as the power level at the source of an event is neither predictable with precision nor can be controlled. Considering the emerging trend of long sensing range for cost-effective sensor deployment, locating events within a region much smaller than the sensing area of a single sensor has gained research interest. This paper proposes the first range-free event localization framework, which avoids expensive hardware needed by the range-based counterparts. Our approach first develops a sensing range model from the statistical information on the emitted power of a type of events so that user-defined event-detection quality can be provisioned using a minimal network of static sensors. Then an accurate event location boundary estimation technique is developed from the sensing feedbacks, which also facilitates guided expansion of the area of possible event location (APEL) to deal with sensing errors. Finally, user-defined event-localization quality guarantee is provisioned cost-effectively by inviting mobile sensors on-demand to target positions. Analytical solutions are provided whenever appropriate and comprehensive simulations are carried out to evaluate localization performance. The proposed event localization technique outperforms the state-of-the-art range-based counterpart (Xu et al., 2011) in realistic environment with path loss, shadow fading, and sensor positioning errors. [ABSTRACT FROM AUTHOR]

This comment points out four inaccurate equations. The correct equations are provided. [ABSTRACT FROM AUTHOR]

One of the main applications of wireless sensor networks is to provide proper coverage of their deployment regions. A wireless sensor network k-covers its deployment region if every point in its deployment region is within the coverage ranges of at least k sensors. In this paper, we assume that the sensors are deployed as either a Poisson point process or a uniform point process in a square or disk region, and study how the probability of the k-coverage changes with the sensing radius or the number of sensors. Our results take the complicated boundary effect into account, rather than avoiding it by assuming the toroidal metric as done in the literature. [ABSTRACT FROM AUTHOR]

• This method improves the gap coverage performance. • This method improves the service quality of multi-hop sensor networks. • This method improves the coverage area of multi-hop sensor networks. • This method has important significance in the rational deployment of sensor nodes. • This method extends the life cycle of multi-hop sensor networks. The traditional method does not calculate the moving distance parameter when detecting coverage vulnerabilities, so its coverage performance is poor. The clustering algorithm can effectively calculate the moving distance parameter. Therefore, a method to detect the coverage hole in wireless sensor network based on clustering algorithm was proposed. Firstly, the parameter of coverage hole in wireless sensor network were calculated, including the moving distance parameters, circular intersection area parameters and redundancy parameters. Secondly, the algorithm of hole edge intersection was used to judge edge nodes of coverage holes in wireless sensor network. By judging whether there was a hole edge intersection on the sensing circle, the edge nodes of coverage holes in wireless sensor network could be determined. Thirdly, the mobile nodes were deployed in the way of airdrop, and then they were distributed evenly. The density of the initially deployed mobile nodes should meet the highest coverage requirement in wireless sensor network. After determining the edge nodes of coverage holes in wireless sensor network, the deployed mobile nodes were used to find the edge nodes of coverage holes in wireless sensor networks by random walk. Meanwhile, the coverage holes were approximated by the set of edge nodes. Finally, it was able to detect the coverage holes in wireless sensor network by clustering algorithm, including the detection of hole shape and the judgment of holes size. In order to verify the gap coverage performance of the coverage hole detection method based on clustering algorithm, the traditional method was compared with the proposed method. Experimental results show that the gap coverage performance of the proposed method is better than that of traditional method. The gap coverage performance of this method is 389 T, while the traditional method is only 351 T. so this method is more suitable for the detection of coverage hole in wireless sensor network. [ABSTRACT FROM AUTHOR]