Pub Date : 2022-03-01DOI: 10.1177/15501329221077932
Xiaofeng Wu, Zhuangqi Chen, Yi Zhong, Hui Zhu, Pingjian Zhang
Several data collection algorithms, which are based on the combination of using mobile sinks and multiple-hop forwarding, have been proposed to prolong the network lifetime of wireless sensor networks. However, most approaches treat the collection point selection and touring path planning as two independent problems, which leads to a sub-optimal solution for data collection. This article proposed an ant colony optimization based end-to-end data collection strategy to perform the collection point selection and the touring path planning simultaneously. The proposed algorithm first constructs a data-forwarding tree, and then heuristically selects collection points and plans a touring path at the same time. The performance evaluation shows that the end-to-end strategy can improve the network lifetime of wireless sensor network compared to other approaches, especially in the unbalanced distribution scenario of sensors. The end-to-end strategy is also capable of being integrated with other methods.
{"title":"End-to-end data collection strategy using mobile sink in wireless sensor networks","authors":"Xiaofeng Wu, Zhuangqi Chen, Yi Zhong, Hui Zhu, Pingjian Zhang","doi":"10.1177/15501329221077932","DOIUrl":"https://doi.org/10.1177/15501329221077932","url":null,"abstract":"Several data collection algorithms, which are based on the combination of using mobile sinks and multiple-hop forwarding, have been proposed to prolong the network lifetime of wireless sensor networks. However, most approaches treat the collection point selection and touring path planning as two independent problems, which leads to a sub-optimal solution for data collection. This article proposed an ant colony optimization based end-to-end data collection strategy to perform the collection point selection and the touring path planning simultaneously. The proposed algorithm first constructs a data-forwarding tree, and then heuristically selects collection points and plans a touring path at the same time. The performance evaluation shows that the end-to-end strategy can improve the network lifetime of wireless sensor network compared to other approaches, especially in the unbalanced distribution scenario of sensors. The end-to-end strategy is also capable of being integrated with other methods.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41660326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval problem, where re-ranking is important for performance enhancement. In the vehicle re-identification ranking list, images whose orientations are dissimilar to that of the query image must preferably be optimized on priority. However, traditional methods are incompatible with such samples, resulting in unsatisfactory vehicle re-identification performances. Therefore, in this study, we propose a vehicle re-identification re-ranking method with orientation-guide query expansion to optimize the initial ranking list obtained by a re-identification model. In the proposed method, we first find the nearest neighbor image whose orientation is dissimilar to the queried image and then fuse the features of the query and neighbor images to obtain new features for information retrieval. Experiments are performed on two public data sets, VeRi-776 and VehicleID, and the effectiveness of the proposed method is confirmed.
{"title":"Re-ranking vehicle re-identification with orientation-guide query expansion","authors":"Xue Zhang, Xiushan Nie, Ziruo Sun, Xiaofeng Li, Chuntao Wang, Peng Tao, Sumaira Hussain","doi":"10.1177/15501477211066305","DOIUrl":"https://doi.org/10.1177/15501477211066305","url":null,"abstract":"Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval problem, where re-ranking is important for performance enhancement. In the vehicle re-identification ranking list, images whose orientations are dissimilar to that of the query image must preferably be optimized on priority. However, traditional methods are incompatible with such samples, resulting in unsatisfactory vehicle re-identification performances. Therefore, in this study, we propose a vehicle re-identification re-ranking method with orientation-guide query expansion to optimize the initial ranking list obtained by a re-identification model. In the proposed method, we first find the nearest neighbor image whose orientation is dissimilar to the queried image and then fuse the features of the query and neighbor images to obtain new features for information retrieval. Experiments are performed on two public data sets, VeRi-776 and VehicleID, and the effectiveness of the proposed method is confirmed.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41421953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221082430
Yanfang Dong, Feifan Chen, M. Qiu
As the most important segment of the spindle unit angular contact ball bearing, the preload significantly influences the bearing characteristics. Thus, the thermal-induced preload derived from the thermal expansion of spindle unit components also affects the increase in bearing temperature, stiffness, fatigue life, and ball skidding significantly. However, such preload is hard to monitor and analyze. Thus, in this article, the authors presented a fiber Bragg gating sensor-based structure for the identification of thermal-induced bearing preload. In addition, a bearing total preload control mechanism was designed with an emphasis on its thermal component. Based on the comparison of the shaft and the outer ring deformation temperature increases measured by embedded fiber Bragg gating sensors, the reasonable bearing preload range was achieved based on Hirano’s theory. Finally, the conclusions provide a reference for improving the performance of angular contact ball bearings and reducing the spindle vibration.
{"title":"Thermal-induced influences considered spindle unit angular contact ball bearing preload determination using embedded fiber Bragg gating sensors","authors":"Yanfang Dong, Feifan Chen, M. Qiu","doi":"10.1177/15501329221082430","DOIUrl":"https://doi.org/10.1177/15501329221082430","url":null,"abstract":"As the most important segment of the spindle unit angular contact ball bearing, the preload significantly influences the bearing characteristics. Thus, the thermal-induced preload derived from the thermal expansion of spindle unit components also affects the increase in bearing temperature, stiffness, fatigue life, and ball skidding significantly. However, such preload is hard to monitor and analyze. Thus, in this article, the authors presented a fiber Bragg gating sensor-based structure for the identification of thermal-induced bearing preload. In addition, a bearing total preload control mechanism was designed with an emphasis on its thermal component. Based on the comparison of the shaft and the outer ring deformation temperature increases measured by embedded fiber Bragg gating sensors, the reasonable bearing preload range was achieved based on Hirano’s theory. Finally, the conclusions provide a reference for improving the performance of angular contact ball bearings and reducing the spindle vibration.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45864007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221087055
Zhu Liu, Xue-song Qiu, Yonggui Wang, Shuai Zhang, Zhi Li
Aiming at the hardware reusability, multi-service carrying capacity, and computing resource limitations of edge devices, a light-weight voltage sag monitoring and classification method based on improved firefly algorithm optimization, extended Kalman filter, and least-square support-vector machine is proposed. The strategy of linearly decreasing inertia weight is introduced to optimize the state error of the extended Kalman filter algorithm and the measurement noise covariance matrix to achieve accurate monitoring of voltage sags. Extract characteristic quantities such as average value, duration of sag, minimum sag dispersion characteristics, number of sag phases, and flow direction of disturbance energy. As a model training data set, the least-square support-vector machine method optimized based on the improved firefly algorithm is used to create a multi-level classification model of voltage sag source to realize the classification of voltage sag sources. This method fully considers the influence of the limited resources of edge computing equipment on the algorithm, and effectively improves the use of computing resources by improving the optimization algorithm. Simulation and experimental results show that this method is suitable for edge computing equipment to monitor and distinguish voltage sags.
{"title":"Improved firefly algorithm–extended Kalman filter–least-square support-vector machine voltage sag monitoring and classification method based on edge computing","authors":"Zhu Liu, Xue-song Qiu, Yonggui Wang, Shuai Zhang, Zhi Li","doi":"10.1177/15501329221087055","DOIUrl":"https://doi.org/10.1177/15501329221087055","url":null,"abstract":"Aiming at the hardware reusability, multi-service carrying capacity, and computing resource limitations of edge devices, a light-weight voltage sag monitoring and classification method based on improved firefly algorithm optimization, extended Kalman filter, and least-square support-vector machine is proposed. The strategy of linearly decreasing inertia weight is introduced to optimize the state error of the extended Kalman filter algorithm and the measurement noise covariance matrix to achieve accurate monitoring of voltage sags. Extract characteristic quantities such as average value, duration of sag, minimum sag dispersion characteristics, number of sag phases, and flow direction of disturbance energy. As a model training data set, the least-square support-vector machine method optimized based on the improved firefly algorithm is used to create a multi-level classification model of voltage sag source to realize the classification of voltage sag sources. This method fully considers the influence of the limited resources of edge computing equipment on the algorithm, and effectively improves the use of computing resources by improving the optimization algorithm. Simulation and experimental results show that this method is suitable for edge computing equipment to monitor and distinguish voltage sags.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47044102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221084226
Ben He, Yi Chen, Yonghui Zhou, Yongrong Wang, Yanli Chen
In recent years, reversible data hiding technology has been widely used in JPEG images for special purposes such as file management and image authentication. Histogram shifting is one of the most popular techniques for achieving reversible data hiding technology. However, invalid shifting in histogram shifting limits the performance of existing reversible data hiding schemes. Therefore, we propose a two-dimensional histogram shifting-based reversible data hiding scheme in this article to improve the performance of marked JPEG images in terms of visual quality and file size. In the proposed histogram shifting method, only the coefficient pairs containing two non-zero quantized discrete cosine transform coefficients are changed for embedding data. Specifically, the coefficient pairs with at least one quantized discrete cosine transform coefficient valued −1 or +1 are shifted and the rests leave room for embedding data. With our proposed reversible data hiding scheme, the number of invalid shifting pixels is reduced so that it improves the performance of marked JPEG images. The experimental results show that the proposed method achieves a higher peak signal-to-noise ratio and has a lower increase in file size than state-of-art methods.
{"title":"A novel two-dimensional reversible data hiding scheme based on high-efficiency histogram shifting for JPEG images","authors":"Ben He, Yi Chen, Yonghui Zhou, Yongrong Wang, Yanli Chen","doi":"10.1177/15501329221084226","DOIUrl":"https://doi.org/10.1177/15501329221084226","url":null,"abstract":"In recent years, reversible data hiding technology has been widely used in JPEG images for special purposes such as file management and image authentication. Histogram shifting is one of the most popular techniques for achieving reversible data hiding technology. However, invalid shifting in histogram shifting limits the performance of existing reversible data hiding schemes. Therefore, we propose a two-dimensional histogram shifting-based reversible data hiding scheme in this article to improve the performance of marked JPEG images in terms of visual quality and file size. In the proposed histogram shifting method, only the coefficient pairs containing two non-zero quantized discrete cosine transform coefficients are changed for embedding data. Specifically, the coefficient pairs with at least one quantized discrete cosine transform coefficient valued −1 or +1 are shifted and the rests leave room for embedding data. With our proposed reversible data hiding scheme, the number of invalid shifting pixels is reduced so that it improves the performance of marked JPEG images. The experimental results show that the proposed method achieves a higher peak signal-to-noise ratio and has a lower increase in file size than state-of-art methods.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47962528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221088740
Yan-Xin Lin, Hongliang Zhu, Guoai Xu, Guosheng Xu
Wireless sensor network is a key technology in the sensing layer of the Internet of Things. Data security in wireless sensor network is directly related to the authenticity and validity of data transmitted in the Internet of Things. Due to the large number and different types of nodes in wireless sensor networks, layered secret key sharing technology is increasingly used in wireless sensor networks. In a hierarchical secret sharing scheme, participants are divided into sections with different permissions for each team, but the same permissions for participants in the same team. In this article, we follow the approach of the hierarchical secret sharing scheme derived from the linear homogeneous recurrence relations. We design a hierarchical multi-secret sharing scheme for wireless sensor networks on the basis of the elliptic curve public key cryptosystem combined with the linear homogeneous recurrence relations. In the proposed scheme, we do not make sure that the participants are half-truthful. In addition, the participants’ shadows can be reused. Our scheme is computational security. Only one share from each member is required in our hierarchical multi-secret sharing scheme. It is more suitable for wireless sensor networks compared to the up-to-date schemes.
{"title":"Hierarchical secret sharing scheme for WSN based on linear homogeneous recurrence relations","authors":"Yan-Xin Lin, Hongliang Zhu, Guoai Xu, Guosheng Xu","doi":"10.1177/15501329221088740","DOIUrl":"https://doi.org/10.1177/15501329221088740","url":null,"abstract":"Wireless sensor network is a key technology in the sensing layer of the Internet of Things. Data security in wireless sensor network is directly related to the authenticity and validity of data transmitted in the Internet of Things. Due to the large number and different types of nodes in wireless sensor networks, layered secret key sharing technology is increasingly used in wireless sensor networks. In a hierarchical secret sharing scheme, participants are divided into sections with different permissions for each team, but the same permissions for participants in the same team. In this article, we follow the approach of the hierarchical secret sharing scheme derived from the linear homogeneous recurrence relations. We design a hierarchical multi-secret sharing scheme for wireless sensor networks on the basis of the elliptic curve public key cryptosystem combined with the linear homogeneous recurrence relations. In the proposed scheme, we do not make sure that the participants are half-truthful. In addition, the participants’ shadows can be reused. Our scheme is computational security. Only one share from each member is required in our hierarchical multi-secret sharing scheme. It is more suitable for wireless sensor networks compared to the up-to-date schemes.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44948378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501477211049910
Li Duan, Jingxian Zhou, You Wu, Wenyao Xu
In smart systems, attackers can use botnets to launch different cyber attack activities against the Internet of Things. The traditional methods of detecting botnets commonly used machine learning algorithms, and it is difficult to detect and control botnets in a network because of unbalanced traffic data. In this article, we present a novel and highly efficient botnet detection method based on an autoencoder neural network in cooperation with decision trees on a given network. The deep flow inspection method and statistical analysis are first applied as a feature selection technique to select relevant features, which are used to characterize the communication-related behavior between network nodes. Then, the autoencoder neural network for feature selection is used to improve the efficiency of model construction. Finally, Tomek-Recursion Borderline Synthetic Minority Oversampling Technique generates additional minority samples to achieve class balance, and an improved gradient boosting decision tree algorithm is used to train and establish an abnormal traffic detection model to improve the detection of unbalanced botnet data. The results of experiments on the ISCX-botnet traffic dataset show that the proposed method achieved better botnet detection performance with 99.10% recall, 99.20% accuracy, 99.1% F1 score, and 99.0% area under the curve.
{"title":"A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems","authors":"Li Duan, Jingxian Zhou, You Wu, Wenyao Xu","doi":"10.1177/15501477211049910","DOIUrl":"https://doi.org/10.1177/15501477211049910","url":null,"abstract":"In smart systems, attackers can use botnets to launch different cyber attack activities against the Internet of Things. The traditional methods of detecting botnets commonly used machine learning algorithms, and it is difficult to detect and control botnets in a network because of unbalanced traffic data. In this article, we present a novel and highly efficient botnet detection method based on an autoencoder neural network in cooperation with decision trees on a given network. The deep flow inspection method and statistical analysis are first applied as a feature selection technique to select relevant features, which are used to characterize the communication-related behavior between network nodes. Then, the autoencoder neural network for feature selection is used to improve the efficiency of model construction. Finally, Tomek-Recursion Borderline Synthetic Minority Oversampling Technique generates additional minority samples to achieve class balance, and an improved gradient boosting decision tree algorithm is used to train and establish an abnormal traffic detection model to improve the detection of unbalanced botnet data. The results of experiments on the ISCX-botnet traffic dataset show that the proposed method achieved better botnet detection performance with 99.10% recall, 99.20% accuracy, 99.1% F1 score, and 99.0% area under the curve.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44095249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221077165
Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang
Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. In the framework of the stagewise orthogonal matching pursuit algorithm, the algorithm in this article uses a combination of a fixed-value strategy and a threshold strategy to screen the candidate atom sets in two rounds to improve the accuracy of atom selection, and then according to the sparsity adaptive principle, the sparse approximation and accurate signal reconstruction are realized by the variable step size method. The simulation results show that the algorithm proposed in this article is compared with the orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, and stagewise orthogonal matching pursuit algorithm. When the sparsity is 35 < K < 45, regardless of the size of the perception matrix and the length of the signal, M = 128, N = 256 or M = 128, N = 512 are improved, and the reconstruction time is when the sparsity is 10, the fastest time between 25 and 25, that is, less than 4.5 s. It can be seen that the sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm has better adaptive characteristics to the sparsity of the signal, which is beneficial for users to receive more accurate original signals.
{"title":"An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks","authors":"Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang","doi":"10.1177/15501329221077165","DOIUrl":"https://doi.org/10.1177/15501329221077165","url":null,"abstract":"Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. In the framework of the stagewise orthogonal matching pursuit algorithm, the algorithm in this article uses a combination of a fixed-value strategy and a threshold strategy to screen the candidate atom sets in two rounds to improve the accuracy of atom selection, and then according to the sparsity adaptive principle, the sparse approximation and accurate signal reconstruction are realized by the variable step size method. The simulation results show that the algorithm proposed in this article is compared with the orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, and stagewise orthogonal matching pursuit algorithm. When the sparsity is 35 < K < 45, regardless of the size of the perception matrix and the length of the signal, M = 128, N = 256 or M = 128, N = 512 are improved, and the reconstruction time is when the sparsity is 10, the fastest time between 25 and 25, that is, less than 4.5 s. It can be seen that the sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm has better adaptive characteristics to the sparsity of the signal, which is beneficial for users to receive more accurate original signals.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501477211067740
Gerald K. Ijemaru, Kenneth Li-Minn Ang, Jasmine KP Seng
Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often hampered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.
{"title":"Wireless power transfer and energy harvesting in distributed sensor networks: Survey, opportunities, and challenges","authors":"Gerald K. Ijemaru, Kenneth Li-Minn Ang, Jasmine KP Seng","doi":"10.1177/15501477211067740","DOIUrl":"https://doi.org/10.1177/15501477211067740","url":null,"abstract":"Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often hampered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44676727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221085495
Li-yong Yuan, Feilong Lin
Routing optimization in wireless sensor networks facilitates to reduce the overhead of the maintaining of wireless sensor networks and extend the lifetime of wireless sensor networks. Collection tree-based routing protocol, which does not require route discovery, has been widely used for low overheads of calculation and storage. However, with collection tree-based routing protocol, some nodes easily become the bottleneck points and quickly run out of the energy. To deal with this drawback, this article proposes a collection tree-oriented mesh routing strategy with cooperatively consuming the residual energy among the neighboring sensor nodes. The collection tree-oriented mesh routing is formulated into a linear programming problem with the purpose to maximize the network lifetime. By solving the optimization problem, the optimal mesh routing and data forwarding scheme is derived. Experimental simulations show that the proposed collection tree-oriented mesh routing optimization strategy can extend the network lifetime by more than 20%.
{"title":"Collection tree-oriented mesh routing optimization for extending the lifetime of wireless sensor networks","authors":"Li-yong Yuan, Feilong Lin","doi":"10.1177/15501329221085495","DOIUrl":"https://doi.org/10.1177/15501329221085495","url":null,"abstract":"Routing optimization in wireless sensor networks facilitates to reduce the overhead of the maintaining of wireless sensor networks and extend the lifetime of wireless sensor networks. Collection tree-based routing protocol, which does not require route discovery, has been widely used for low overheads of calculation and storage. However, with collection tree-based routing protocol, some nodes easily become the bottleneck points and quickly run out of the energy. To deal with this drawback, this article proposes a collection tree-oriented mesh routing strategy with cooperatively consuming the residual energy among the neighboring sensor nodes. The collection tree-oriented mesh routing is formulated into a linear programming problem with the purpose to maximize the network lifetime. By solving the optimization problem, the optimal mesh routing and data forwarding scheme is derived. Experimental simulations show that the proposed collection tree-oriented mesh routing optimization strategy can extend the network lifetime by more than 20%.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42988941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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