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Xianjun Deng - One of the best experts on this subject based on the ideXlab platform.
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a nature inspired node deployment strategy for connected confident Information Coverage in industrial internet of things
2019Co-Authors: Lu Dai, Bang Wang, Laurence T Yang, Xianjun DengAbstract:The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident Information Coverage, network connectivity, energy efficiency, fault tolerance, and reliability. An IoT node deployment scheme based on an improved nature-inspired genetic algorithm is proposed to solve the defined constrained optimization problem. In the proposed IoT node deployment scheme, we utilize a population initialization based on the Delaunay triangulation to generate the better initial population, a chromosome modification operation to achieve both connectivity and Coverage for each chromosome and a chromosome mirror-crossover operation to produce the better offsprings. Experimental results show that our deployment schema equips better performance in terms of longer network lifetime and comparable Coverage ratio compared with the other four peer algorithms.
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Healing Multimodal Confident Information Coverage Holes in NB-IoT-Enabled Networks
2018Co-Authors: Xianjun Deng, Zujun Tang, Laurence T YangAbstract:The Internet of Things (IoT) evolving from the conventional wireless sensor networks (WSNs) with more smart sensors has attracted significant attention. As one of the most crucial metrics for evaluating the quality of service (QoS) of both IoT and WSNs, sensing Coverage characterizes the monitoring status of a sensing field of interest. However, the existence of Coverage holes will remarkably degrade the QoS of the IoT. Based on the novel confident Information Coverage (CIC) model, this paper provides an in-depth study on how to energy-efficiently heal the multimodal CIC holes (MCICH) in a narrowband IoT (NB-IoT)-enabled hybrid IoT deployed for radiological pollution monitoring, where both mobile and stationary sensors equip multimodal sensing units for sensing dissimilar multimodal physical attributes and the NB-IoT provides satisfied network connectivity. We pinpoint the MCICH healing (MCICHH) problem with the objective of energy-efficiently dispatching a series of multimodal mobile IoT sensors to the CIC holes such that the MCIC holes can be headed and the CIC performance can be satisfied. After proving the NP-completeness of MCICHH by reducing it to the set partition problem, we develop a family of effective heuristic schemes including the centralized-MCICHH, the distributed-MCICHH and random CIC hole healing, all of which target for efficiently healing the MCIC holes while minimizing the total moving energy consumption of the dispatched multimodal mobile sensors or maximizing the average remaining energy of the multimodal mobile sensors. Extensive experiments verify the effectiveness and practicality of the proposed schemes.
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confident Information Coverage hole healing in hybrid industrial wireless sensor networks
2018Co-Authors: Xianjun Deng, Laurence T Yang, Zujun Tang, Man Lin, Bang WangAbstract:The emergence of Coverage holes will dramatically degrade the quality of service of the industrial wireless sensor networks (IWSNs). Based on the novel confident Information Coverage (CIC) model, this work focuses on how to heal the CIC holes in hybrid IWSNs containing both static nodes and mobile nodes. We pinpoint the CIC hole healing (CICHH) problem with the goal of selecting and dispatching some randomly scattered mobile nodes to the CIC holes detected by the stationary nodes such that the CIC holes can be repaired and the CIC performance can be satisfied, and prove its NP-completeness. For handling the CICHH problem, we devise two energy-efficient heuristic solutions including a centralized CICHH algorithm and a distributed one. Both the proposed schemes aim at efficiently healing the CIC holes while minimizing the total moving energy consumption of the dispatched mobile nodes, or maximizing the mobile nodes’ average remaining energy after movement, or minimizing the maximum mobile energy consumption of each dispatched mobile node. Experimental simulation results show the proposed schemes can energy-efficiently heal the CIC holes and outperform three peer algorithms in terms of energy efficiency and Coverage ratio.
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localized confident Information Coverage hole detection in internet of things for radioactive pollution monitoring
2017Co-Authors: Lingzhi Yi, Xianjun Deng, Dexin Ding, Minghua Wang, Yan WangAbstract:As a novel cyber-physical-social network paradigm, the Internet of Things (IoT) provides a powerful tool to monitor the hazardous fields of interest. Due to the uneven random deployment, sensor energy depletion, and external attacks, the emergence of Coverage holes would remarkably degrade the network performance and quality of service. For overcoming the drawbacks resulting from the Coverage holes, this paper focuses on how to locally detect Coverage holes by exploiting one-hop neighboring sensors’ cooperation based on the novel confident Information Coverage model (CIC), which is formulated as the localized confident Information Coverage hole detection (LCICHD) problem. For handling the CICHD problem, we devise a family of heuristic CIC holes detection schemes including the LCHD, LCHDRL, random and randomRL. Both the LCHD and LCHDRL schemes locally determine Coverage status of each subregion and take the sensor communication ability into consideration. While the LCHDRL considers not only the sensor remaining energy but also the residual lifetime during the CIC hole detection. After acquiring the Coverage status of each partitioned local subregion, the Coverage hole boundary will be extracted by image processing techniques. For comparison, both the Random and RandomRL schemes arbitrarily select sensors within the sensing field to detect CIC holes, and the RandomRL scheme takes the sensors’ residual lifetime into consideration during the hole detection process. Experimental simulations show that the proposed schemes can efficiently detect the emerged Coverage holes including the locations and the number, and the LCHDRL algorithm is more practical and efficient compared with the other three peer solutions.
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confident Information Coverage hole detection in sensor networks for uranium tailing monitoring
2017Co-Authors: Xianjun Deng, Zenghui Zou, Dexin Ding, Laurence T YangAbstract:Abstract The wireless sensor networks recently abstract great attention and are used for a wide range of cyber-enabled applications each of which with rigid accuracy requirements. The emergence and existence of Coverage holes in WSNs will dramatically degrade the network Coverage performance and quality of service. To diminish the negative effects of Coverage holes, this paper addresses and studies the confident Information Coverage hole detection problem (CICHD) based on the proposed novel confident Information Coverage model (CIC). For solving the CICHD problem, we design two effective heuristic CIC holes detection algorithms including the CHD without considering the nodes residual energy and the other CHDRE taking the nodes’ residual energy into account. In the both proposed algorithms, the sensing field is firstly partitioned into a series of reconstruction grids based on the spatial correlation and correlation range. Then each reconstruction grid will be scanned and detected based on the CIC model to be judged whether it is a hole. Once obtaining the Coverage status of every reconstruction grid, the boundary of the Coverage hole will be exacted by image processing method. The results of the simulations show that both the proposed schemes can efficiently detect the emerged Coverage holes including the locations and the number, and the CHDRE algorithm is more practical and efficient compared to the CHD without considering the energy problem.
Laurence T Yang - One of the best experts on this subject based on the ideXlab platform.
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a nature inspired node deployment strategy for connected confident Information Coverage in industrial internet of things
2019Co-Authors: Lu Dai, Bang Wang, Laurence T Yang, Xianjun DengAbstract:The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident Information Coverage, network connectivity, energy efficiency, fault tolerance, and reliability. An IoT node deployment scheme based on an improved nature-inspired genetic algorithm is proposed to solve the defined constrained optimization problem. In the proposed IoT node deployment scheme, we utilize a population initialization based on the Delaunay triangulation to generate the better initial population, a chromosome modification operation to achieve both connectivity and Coverage for each chromosome and a chromosome mirror-crossover operation to produce the better offsprings. Experimental results show that our deployment schema equips better performance in terms of longer network lifetime and comparable Coverage ratio compared with the other four peer algorithms.
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Healing Multimodal Confident Information Coverage Holes in NB-IoT-Enabled Networks
2018Co-Authors: Xianjun Deng, Zujun Tang, Laurence T YangAbstract:The Internet of Things (IoT) evolving from the conventional wireless sensor networks (WSNs) with more smart sensors has attracted significant attention. As one of the most crucial metrics for evaluating the quality of service (QoS) of both IoT and WSNs, sensing Coverage characterizes the monitoring status of a sensing field of interest. However, the existence of Coverage holes will remarkably degrade the QoS of the IoT. Based on the novel confident Information Coverage (CIC) model, this paper provides an in-depth study on how to energy-efficiently heal the multimodal CIC holes (MCICH) in a narrowband IoT (NB-IoT)-enabled hybrid IoT deployed for radiological pollution monitoring, where both mobile and stationary sensors equip multimodal sensing units for sensing dissimilar multimodal physical attributes and the NB-IoT provides satisfied network connectivity. We pinpoint the MCICH healing (MCICHH) problem with the objective of energy-efficiently dispatching a series of multimodal mobile IoT sensors to the CIC holes such that the MCIC holes can be headed and the CIC performance can be satisfied. After proving the NP-completeness of MCICHH by reducing it to the set partition problem, we develop a family of effective heuristic schemes including the centralized-MCICHH, the distributed-MCICHH and random CIC hole healing, all of which target for efficiently healing the MCIC holes while minimizing the total moving energy consumption of the dispatched multimodal mobile sensors or maximizing the average remaining energy of the multimodal mobile sensors. Extensive experiments verify the effectiveness and practicality of the proposed schemes.
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confident Information Coverage hole healing in hybrid industrial wireless sensor networks
2018Co-Authors: Xianjun Deng, Laurence T Yang, Zujun Tang, Man Lin, Bang WangAbstract:The emergence of Coverage holes will dramatically degrade the quality of service of the industrial wireless sensor networks (IWSNs). Based on the novel confident Information Coverage (CIC) model, this work focuses on how to heal the CIC holes in hybrid IWSNs containing both static nodes and mobile nodes. We pinpoint the CIC hole healing (CICHH) problem with the goal of selecting and dispatching some randomly scattered mobile nodes to the CIC holes detected by the stationary nodes such that the CIC holes can be repaired and the CIC performance can be satisfied, and prove its NP-completeness. For handling the CICHH problem, we devise two energy-efficient heuristic solutions including a centralized CICHH algorithm and a distributed one. Both the proposed schemes aim at efficiently healing the CIC holes while minimizing the total moving energy consumption of the dispatched mobile nodes, or maximizing the mobile nodes’ average remaining energy after movement, or minimizing the maximum mobile energy consumption of each dispatched mobile node. Experimental simulation results show the proposed schemes can energy-efficiently heal the CIC holes and outperform three peer algorithms in terms of energy efficiency and Coverage ratio.
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confident Information Coverage hole detection in sensor networks for uranium tailing monitoring
2017Co-Authors: Xianjun Deng, Zenghui Zou, Dexin Ding, Laurence T YangAbstract:Abstract The wireless sensor networks recently abstract great attention and are used for a wide range of cyber-enabled applications each of which with rigid accuracy requirements. The emergence and existence of Coverage holes in WSNs will dramatically degrade the network Coverage performance and quality of service. To diminish the negative effects of Coverage holes, this paper addresses and studies the confident Information Coverage hole detection problem (CICHD) based on the proposed novel confident Information Coverage model (CIC). For solving the CICHD problem, we design two effective heuristic CIC holes detection algorithms including the CHD without considering the nodes residual energy and the other CHDRE taking the nodes’ residual energy into account. In the both proposed algorithms, the sensing field is firstly partitioned into a series of reconstruction grids based on the spatial correlation and correlation range. Then each reconstruction grid will be scanned and detected based on the CIC model to be judged whether it is a hole. Once obtaining the Coverage status of every reconstruction grid, the boundary of the Coverage hole will be exacted by image processing method. The results of the simulations show that both the proposed schemes can efficiently detect the emerged Coverage holes including the locations and the number, and the CHDRE algorithm is more practical and efficient compared to the CHD without considering the energy problem.
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Sensor Density for Confident Information Coverage in Randomly Deployed Sensor Networks
2016Co-Authors: Bang Wang, Laurence T Yang, Yijun MoAbstract:Coverage is one of the fundamental issues in wireless sensor networks, yet most of the current studies on Coverage are based on the simplest disk Coverage model. Based on the theory of field reconstruction, we proposed a novel Coverage model called confident Information Coverage in our previous study. In this paper, based on the confident Information Coverage model, we study the critical sensor density to achieve complete Coverage in randomly deployed sensor networks. We first use the average vacancy to measure the degree of Coverage, and compute the average vacancy through the computation of the probability that an arbitrary point is not covered by randomly deployed sensors within its correlation range. We then propose a numerical computation method called discrete approximation algorithm to compute this probability, and prove that this probability is actually the limit of the output of the proposed algorithm. Furthermore, we derive the upper and lower bound for the average vacancy as a function of sensor density, which provides a useful insight for the critical sensor density to achieve complete Coverage. The simulation results validate our theoretical analysis.
Bang Wang - One of the best experts on this subject based on the ideXlab platform.
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a nature inspired node deployment strategy for connected confident Information Coverage in industrial internet of things
2019Co-Authors: Lu Dai, Bang Wang, Laurence T Yang, Xianjun DengAbstract:The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident Information Coverage, network connectivity, energy efficiency, fault tolerance, and reliability. An IoT node deployment scheme based on an improved nature-inspired genetic algorithm is proposed to solve the defined constrained optimization problem. In the proposed IoT node deployment scheme, we utilize a population initialization based on the Delaunay triangulation to generate the better initial population, a chromosome modification operation to achieve both connectivity and Coverage for each chromosome and a chromosome mirror-crossover operation to produce the better offsprings. Experimental results show that our deployment schema equips better performance in terms of longer network lifetime and comparable Coverage ratio compared with the other four peer algorithms.
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confident Information Coverage hole healing in hybrid industrial wireless sensor networks
2018Co-Authors: Xianjun Deng, Laurence T Yang, Zujun Tang, Man Lin, Bang WangAbstract:The emergence of Coverage holes will dramatically degrade the quality of service of the industrial wireless sensor networks (IWSNs). Based on the novel confident Information Coverage (CIC) model, this work focuses on how to heal the CIC holes in hybrid IWSNs containing both static nodes and mobile nodes. We pinpoint the CIC hole healing (CICHH) problem with the goal of selecting and dispatching some randomly scattered mobile nodes to the CIC holes detected by the stationary nodes such that the CIC holes can be repaired and the CIC performance can be satisfied, and prove its NP-completeness. For handling the CICHH problem, we devise two energy-efficient heuristic solutions including a centralized CICHH algorithm and a distributed one. Both the proposed schemes aim at efficiently healing the CIC holes while minimizing the total moving energy consumption of the dispatched mobile nodes, or maximizing the mobile nodes’ average remaining energy after movement, or minimizing the maximum mobile energy consumption of each dispatched mobile node. Experimental simulation results show the proposed schemes can energy-efficiently heal the CIC holes and outperform three peer algorithms in terms of energy efficiency and Coverage ratio.
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Sensor Density for Confident Information Coverage in Randomly Deployed Sensor Networks
2016Co-Authors: Bang Wang, Laurence T Yang, Yijun MoAbstract:Coverage is one of the fundamental issues in wireless sensor networks, yet most of the current studies on Coverage are based on the simplest disk Coverage model. Based on the theory of field reconstruction, we proposed a novel Coverage model called confident Information Coverage in our previous study. In this paper, based on the confident Information Coverage model, we study the critical sensor density to achieve complete Coverage in randomly deployed sensor networks. We first use the average vacancy to measure the degree of Coverage, and compute the average vacancy through the computation of the probability that an arbitrary point is not covered by randomly deployed sensors within its correlation range. We then propose a numerical computation method called discrete approximation algorithm to compute this probability, and prove that this probability is actually the limit of the output of the proposed algorithm. Furthermore, we derive the upper and lower bound for the average vacancy as a function of sensor density, which provides a useful insight for the critical sensor density to achieve complete Coverage. The simulation results validate our theoretical analysis.
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sensor placement based on delaunay triangulation for complete confident Information Coverage in an area with obstacles
2015Co-Authors: Lu Dai, Bang WangAbstract:This paper studies the sensor placement problem for ensuring complete Coverage in an area with obstacles. Instead of using the simplistic disk Coverage model, we adopt our recently proposed confident Information Coverage model for field attribute monitoring applications. We propose a node placement algorithm based on iterative Delaunay triangulation, which is to first obtain Delaunay triangles for some initial seed nodes. Among all Delaunay triangles, we propose algorithms to find a valid one yet with the largest Coverage hole for placing a new node. The Delaunay triangulation process is then repeated, until all the Delaunday triangles can be completely covered. Simulation results show that our algorithm has comparable performance in terms of the number of placed nodes, compared with a peer algorithm based on a grid approach to discretize the continuous field. However, our algorithm can truly achieve complete Coverage yet with significantly smaller computation time.
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sensor scheduling for multi modal confident Information Coverage in sensor networks
2015Co-Authors: Xianjun Deng, Bang Wang, Wenyu Liu, Laurence T YangAbstract:Network lifetime maximization with guaranteed Coverage is an important issue in wireless sensor networks. Based on our recently proposed confident Information Coverage (CIC) model, this paper studies the multi-modal confident Information Coverage (M2CIC) problem. Assuming that each node is equipped with different types of sensors, the objective is to schedule the multi-modal sensors’ activity, such that the confident Information Coverage for each sensing modality can be guaranteed while the network lifetime can be maximized. We model the M2CIC problem as a multi-modal set cover problem (M2SC) and prove its NP-completeness. For solving the M2SC problem, we design two energy-efficient heuristics including a centralized one and a distributed one. In the proposed algorithms, different modal sensors are organized into a family of set covers, each of which can provide confident Information Coverage for all the monitored physical phenomena. Simulation results show that both the proposed algorithms can efficiently prolong the network lifetime and outperform two classical peer algorithms in terms of the extended network lifetime.
Darren T Roulstone - One of the best experts on this subject based on the ideXlab platform.
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analyst initiations of Coverage and stock return synchronicity
2012Co-Authors: Steven S Crawford, Darren T RoulstoneAbstract:We examine how the Information produced by analysts when they initiate Coverage contributes to the mix of firm-specific, industry-, and market-wide Information available about the firm. We hypothesize that the first analyst to initiate Coverage provides low cost market and industry Information allowing him/her to follow more stocks, whereas subsequent analysts provide firm-specific Information to distinguish themselves from existing analysts. We use stock return synchronicity to measure the mix of Information available about a firm, with higher synchronicity indicating more industry and market Information. Coverage initiations of firms with no prior analyst Coverage increase synchronicity suggesting that analysts produce industry- and market-wide Information. In contrast, analysts initiating Coverage on firms with existing Coverage appear to focus on producing firm-specific Information as these initiations lead to reduced synchronicity. Together, our findings indicate that the type of Information analysts produce at initiation depends on the Information provided by other analysts.
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analyst initiations of Coverage and stock return synchronicity
2012Co-Authors: Steven S Crawford, Darren T RoulstoneAbstract:ABSTRACT: We examine how the Information produced by analysts when they initiate Coverage contributes to the mix of firm-specific, industry-, and market-wide Information available about the firm. We hypothesize that the first analyst to initiate Coverage provides low-cost market and industry Information allowing him/her to follow more stocks, whereas subsequent analysts provide firm-specific Information to distinguish themselves from existing analysts. We use stock return synchronicity to measure the mix of Information available about a firm, with higher synchronicity indicating more industry and market Information. Coverage initiations of firms with no prior analyst Coverage increase synchronicity, suggesting that analysts produce industry- and market-wide Information. In contrast, analysts initiating Coverage on firms with existing Coverage appear to focus on producing firm-specific Information as these initiations lead to reduced synchronicity. Together, our findings indicate that the type of informati...
Robe W Heath - One of the best experts on this subject based on the ideXlab platform.
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millimeter wave energy harvesting
2016Co-Authors: Talha Ahmed Kha, Ahmed Alkhateeb, Robe W HeathAbstract:The millimeter wave (mmWave) band, a prime candidate for 5G cellular networks, seems attractive for wireless energy harvesting since it will feature large antenna arrays and extremely dense base station (BS) deployments. The viability of mmWave for energy harvesting though is unclear, due to the differences in propagation characteristics, such as extreme sensitivity to building blockages. This paper considers a scenario where low-power devices extract energy and/or Information from the mmWave signals. Using stochastic geometry, analytical expressions are derived for the energy Coverage probability, the average harvested power, and the overall (energy-and-Information) Coverage probability at a typical wireless-powered device in terms of the BS density, the antenna geometry parameters, and the channel parameters. Numerical results reveal several network and device level design insights. At the BSs, optimizing the antenna geometry parameters, such as beamwidth, can maximize the network-wide energy Coverage for a given user population. At the device level, the performance can be substantially improved by optimally splitting the received signal for energy and Information extraction, and by deploying multi-antenna arrays. For the latter, an efficient low-power multi-antenna mmWave receiver architecture is proposed for simultaneous energy and Information transfer. Overall, simulation results suggest that mmWave energy harvesting generally outperforms lower frequency solutions.
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millimeter wave energy harvesting
2015Co-Authors: Talha Khan, Ahmed Alkhateeb, Robe W HeathAbstract:The millimeter wave (mmWave) band, which is a prime candidate for 5G cellular networks, seems attractive for wireless energy harvesting. This is because it will feature large antenna arrays as well as extremely dense base station (BS) deployments. The viability of mmWave for energy harvesting though is unclear, due to the differences in propagation characteristics such as extreme sensitivity to building blockages. This paper considers a scenario where low-power devices extract energy and/or Information from the mmWave signals. Using stochastic geometry, analytical expressions are derived for the energy Coverage probability, the average harvested power, and the overall (energy-and-Information) Coverage probability at a typical wireless-powered device in terms of the BS density, the antenna geometry parameters, and the channel parameters. Numerical results reveal several network and device level design insights. At the BSs, optimizing the antenna geometry parameters such as beamwidth can maximize the network-wide energy Coverage for a given user population. At the device level, the performance can be substantially improved by optimally splitting the received signal for energy and Information extraction, and by deploying multi-antenna arrays. For the latter, an efficient low-power multi-antenna mmWave receiver architecture is proposed for simultaneous energy and Information transfer. Overall, simulation results suggest that mmWave energy harvesting generally outperforms lower frequency solutions.