Pub Date : 2020-01-01DOI: 10.4018/978-1-7998-2454-1.ch041
S. Deshpande, Umesh M. Kulkarni, Mritunjay Ojha
Wireless Sensor nodes are being employed in various applications like in traffic control, battlefield, and habitat monitoring, emergency rescue, aerospace systems, healthcare systems and in intruder tracking recently. Tracking techniques differ in almost every application of Wireless Sensor Network (WSN), as WSN is itself application specific. The chapter aims to present the current state of art of the tracking techniques. It throws light on how mathematically target tracking is perceived and then explains tracking schemes and routing techniques based on tracking techniques. An insight of how to code localization techniques in matlab simulation tool is provided and analyzed. It further draws the attention of the readers to types of tracking scenarios. Some of the well established tracking techniques are also surveyed for the reader's benefit. The chapter presents with open research challenges that need to be addressed along with target tracking in wireless sensor networks.
{"title":"Target Tracking in Wireless Sensor Network","authors":"S. Deshpande, Umesh M. Kulkarni, Mritunjay Ojha","doi":"10.4018/978-1-7998-2454-1.ch041","DOIUrl":"https://doi.org/10.4018/978-1-7998-2454-1.ch041","url":null,"abstract":"Wireless Sensor nodes are being employed in various applications like in traffic control, battlefield, and habitat monitoring, emergency rescue, aerospace systems, healthcare systems and in intruder tracking recently. Tracking techniques differ in almost every application of Wireless Sensor Network (WSN), as WSN is itself application specific. The chapter aims to present the current state of art of the tracking techniques. It throws light on how mathematically target tracking is perceived and then explains tracking schemes and routing techniques based on tracking techniques. An insight of how to code localization techniques in matlab simulation tool is provided and analyzed. It further draws the attention of the readers to types of tracking scenarios. Some of the well established tracking techniques are also surveyed for the reader's benefit. The chapter presents with open research challenges that need to be addressed along with target tracking in wireless sensor networks.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74340481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-5225-0058-2.CH011
P. Kuila, P. K. Jana
With proliferation of Computational Intelligence (CI), evolutionary algorithms have drawn enormous attention among researchers. Such algorithms have been studied to solve many optimization problems. Clustering and routing are two well known optimization problems which are well researched in the field of Wireless Sensor Networks (WSNs). These problems are NP-hard. Therefore, many researchers have applied meta-heuristic approaches to develop various evolutionary algorithms to solve them. In this chapter, the authors rigorously study and present various evolutionary algorithms that include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution, etc. and show how these algorithms are applied to solve clustering and routing problems in WSNs. The chapter starts with an introduction of WSNs along with clustering and routing problems in WSNs accompanied by a discussion why these problems are solved by evolutionary algorithms. The authors then give an overview of various evolutionary approaches that are applied to solve clustering and routing problems. Various evolutionary algorithms are then presented towards the solution of these problems. A comparison table is also made by highlighting strengths and weaknesses of the algorithms. Finally, the authors present new directions of future research in this domain.
{"title":"Evolutionary Computing Approaches for Clustering and Routing in Wireless Sensor Networks","authors":"P. Kuila, P. K. Jana","doi":"10.4018/978-1-5225-0058-2.CH011","DOIUrl":"https://doi.org/10.4018/978-1-5225-0058-2.CH011","url":null,"abstract":"With proliferation of Computational Intelligence (CI), evolutionary algorithms have drawn enormous attention among researchers. Such algorithms have been studied to solve many optimization problems. Clustering and routing are two well known optimization problems which are well researched in the field of Wireless Sensor Networks (WSNs). These problems are NP-hard. Therefore, many researchers have applied meta-heuristic approaches to develop various evolutionary algorithms to solve them. In this chapter, the authors rigorously study and present various evolutionary algorithms that include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution, etc. and show how these algorithms are applied to solve clustering and routing problems in WSNs. The chapter starts with an introduction of WSNs along with clustering and routing problems in WSNs accompanied by a discussion why these problems are solved by evolutionary algorithms. The authors then give an overview of various evolutionary approaches that are applied to solve clustering and routing problems. Various evolutionary algorithms are then presented towards the solution of these problems. A comparison table is also made by highlighting strengths and weaknesses of the algorithms. Finally, the authors present new directions of future research in this domain.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74376754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-7998-2454-1.ch047
H. Ammari, A. Shaout, Fatme Mustapha
Efficient sensor deployment has been one of the most challenging and interesting research areas. The importance and effectiveness of real-world sensing applications, such as underwater and atmospheric sensing, military applications, health systems, and alert systems, which target specific events, raise the need for adaptable design of Wireless Sensor Networks (WSNs). The main challenge in the design of such networks is the optimal sensor deployment, which helps extend the operational network lifetime. Indeed, by maintaining coverage and connectivity with the least number of active nodes and least communication cost, the operable time of the network is guaranteed to be prolonged. The study of two-dimensional (2D) WSNs introduced a significant advancement to the wireless sensor computing technology for different types of smart environments. Nevertheless, 2D WSNs were not sufficient concerning certain applications that require three-dimensional (3D) design. Previous work focused on the design and analysis of various approaches to cover a 3D field of interest, and expanded existing design from 2D to 3D space. Hence, the complexity of such approaches is a major stumbling block. To alleviate this problem, more efficient solutions for the design of WSNs for 3D space deployment have been introduced. By tessellation of the 3D space, which is one of the proposed solutions, researchers studied the partitioning of the space based on Voronoi tessellation by generating identical space-filling cells. Using space fillers cells, which are represented by polyhedra, to model the sensing range of the sensor nodes is assumed to be an optimal solution since these polyhedra can fill a 3D space without leaving gaps or overlaps among them. In the existing literature, the coverage problem in 3D space is concerned with finding the polyhedron that can best approximate the spherical sensing range and eliminates gaps without scarifying the network connectivity. Therefore, the latter is directly related to the sensor node placement strategy. This book chapter studies various proposed solutions for the design of 3D WSNs, with a focus on coverage and connectivity. More specifically, it presents several space filling polyhedra, including the cube, truncated octahedron, hexagonal prism, and rhombic dodecahedron. Also, it compares all these space filling polyhedra to cover a 3D space.
{"title":"Sensing Coverage in Three-Dimensional Space","authors":"H. Ammari, A. Shaout, Fatme Mustapha","doi":"10.4018/978-1-7998-2454-1.ch047","DOIUrl":"https://doi.org/10.4018/978-1-7998-2454-1.ch047","url":null,"abstract":"Efficient sensor deployment has been one of the most challenging and interesting research areas. The importance and effectiveness of real-world sensing applications, such as underwater and atmospheric sensing, military applications, health systems, and alert systems, which target specific events, raise the need for adaptable design of Wireless Sensor Networks (WSNs). The main challenge in the design of such networks is the optimal sensor deployment, which helps extend the operational network lifetime. Indeed, by maintaining coverage and connectivity with the least number of active nodes and least communication cost, the operable time of the network is guaranteed to be prolonged. The study of two-dimensional (2D) WSNs introduced a significant advancement to the wireless sensor computing technology for different types of smart environments. Nevertheless, 2D WSNs were not sufficient concerning certain applications that require three-dimensional (3D) design. Previous work focused on the design and analysis of various approaches to cover a 3D field of interest, and expanded existing design from 2D to 3D space. Hence, the complexity of such approaches is a major stumbling block. To alleviate this problem, more efficient solutions for the design of WSNs for 3D space deployment have been introduced. By tessellation of the 3D space, which is one of the proposed solutions, researchers studied the partitioning of the space based on Voronoi tessellation by generating identical space-filling cells. Using space fillers cells, which are represented by polyhedra, to model the sensing range of the sensor nodes is assumed to be an optimal solution since these polyhedra can fill a 3D space without leaving gaps or overlaps among them. In the existing literature, the coverage problem in 3D space is concerned with finding the polyhedron that can best approximate the spherical sensing range and eliminates gaps without scarifying the network connectivity. Therefore, the latter is directly related to the sensor node placement strategy. This book chapter studies various proposed solutions for the design of 3D WSNs, with a focus on coverage and connectivity. More specifically, it presents several space filling polyhedra, including the cube, truncated octahedron, hexagonal prism, and rhombic dodecahedron. Also, it compares all these space filling polyhedra to cover a 3D space.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76509035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-7998-2454-1.ch069
H. Ammari, Amer Ahmed
A wireless sensor network is a collection of sensor nodes that have the ability to sense phenomena in a given environment and collect data, perform computation on the gathered data, and transmit (or forward) it to their destination. Unfortunately, these sensor nodes have limited power, computational, and storage capabilities. These factors have an influence on the design of wireless sensor networks and make it more challenging. In order to overcome these limitations, various power management techniques and energy-efficient protocols have been designed. Among such techniques and protocols, geographic routing is one of the most efficient ways to solve some of the design issues. Geographic routing in wireless sensor networks uses location information of the sensor nodes to define a path from source to destination without having to build a network topology. In this paper, we present a survey of the existing geographic routing techniques both in two-dimensional (2D) and three-dimensional (3D) spaces. Furthermore, we will study the advantages of each routing technique and provide a discussion based on their practical possibility of deployment.
{"title":"Sensor Data Geographic Forwarding in Two-Dimensional and Three-Dimensional Spaces","authors":"H. Ammari, Amer Ahmed","doi":"10.4018/978-1-7998-2454-1.ch069","DOIUrl":"https://doi.org/10.4018/978-1-7998-2454-1.ch069","url":null,"abstract":"A wireless sensor network is a collection of sensor nodes that have the ability to sense phenomena in a given environment and collect data, perform computation on the gathered data, and transmit (or forward) it to their destination. Unfortunately, these sensor nodes have limited power, computational, and storage capabilities. These factors have an influence on the design of wireless sensor networks and make it more challenging. In order to overcome these limitations, various power management techniques and energy-efficient protocols have been designed. Among such techniques and protocols, geographic routing is one of the most efficient ways to solve some of the design issues. Geographic routing in wireless sensor networks uses location information of the sensor nodes to define a path from source to destination without having to build a network topology. In this paper, we present a survey of the existing geographic routing techniques both in two-dimensional (2D) and three-dimensional (3D) spaces. Furthermore, we will study the advantages of each routing technique and provide a discussion based on their practical possibility of deployment.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80036858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-7998-2454-1.ch026
B. Khan, R. Bilal
Robustness and reliability are two essential network parameters to be given priority in Industrial Wireless Sensor Network. But at the same time it is difficult to achieve gain in these performance metrics. Since in industries these networks are used for monitoring, control and automation processes, therefore, it also requires robust communication with minimum delay. Considering the need of high QoS in Industrial WSN, protocols and standards were developed to fulfil the requirement of reliable data communication in harsh environment. In year 2007, HART community designed a Wireless HART standard for efficient industrial communication. This standard gain high reputation soon after its implementation and still being used as a universal solution for industries. In 2009, another standard ISA100.11a was developed, it also gives promised results but fails to eliminate WHART. Both these standards are still competing in industry and the results of these standards are more reliable in comparison to other wireless industrial protocols that exists.
{"title":"Cross-Layer Cooperative Protocol for Industrial Wireless Sensor Network","authors":"B. Khan, R. Bilal","doi":"10.4018/978-1-7998-2454-1.ch026","DOIUrl":"https://doi.org/10.4018/978-1-7998-2454-1.ch026","url":null,"abstract":"Robustness and reliability are two essential network parameters to be given priority in Industrial Wireless Sensor Network. But at the same time it is difficult to achieve gain in these performance metrics. Since in industries these networks are used for monitoring, control and automation processes, therefore, it also requires robust communication with minimum delay. Considering the need of high QoS in Industrial WSN, protocols and standards were developed to fulfil the requirement of reliable data communication in harsh environment. In year 2007, HART community designed a Wireless HART standard for efficient industrial communication. This standard gain high reputation soon after its implementation and still being used as a universal solution for industries. In 2009, another standard ISA100.11a was developed, it also gives promised results but fails to eliminate WHART. Both these standards are still competing in industry and the results of these standards are more reliable in comparison to other wireless industrial protocols that exists.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90180131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-5225-0501-3.CH021
P. Mishra, Subhash Kumar
Underground mines include a number of challenges due to their hostile milieu. Therefore, geotechnical and environmental monitoring mainly in underground coal mines have always been a critical task to ensure safe working conditions. If the monitoring device is cable based, then it requires an huge amount of cable deployment which can pose not only the high maintenance cost but difficulty in laying out the cable throughout the underground galleries. on the other hand, if it is direct wireless communication between sensing devices and the central processing unit, it is also not so feasible due to the crisscross, uneven and incline path. Therefore, Wireless Sensor Networks grab an opportunity to be deployed in such a hostile environment. Keeping in view, in the present chapter, attempts have been made to discuss the different aspects of wireless sensor network for underground coal mining services applications to overcome the various threats. Further, the best suited logical topology has been identified for the same.
{"title":"Wireless Sensor Network for Underground Mining Services Applications","authors":"P. Mishra, Subhash Kumar","doi":"10.4018/978-1-5225-0501-3.CH021","DOIUrl":"https://doi.org/10.4018/978-1-5225-0501-3.CH021","url":null,"abstract":"Underground mines include a number of challenges due to their hostile milieu. Therefore, geotechnical and environmental monitoring mainly in underground coal mines have always been a critical task to ensure safe working conditions. If the monitoring device is cable based, then it requires an huge amount of cable deployment which can pose not only the high maintenance cost but difficulty in laying out the cable throughout the underground galleries. on the other hand, if it is direct wireless communication between sensing devices and the central processing unit, it is also not so feasible due to the crisscross, uneven and incline path. Therefore, Wireless Sensor Networks grab an opportunity to be deployed in such a hostile environment. Keeping in view, in the present chapter, attempts have been made to discuss the different aspects of wireless sensor network for underground coal mining services applications to overcome the various threats. Further, the best suited logical topology has been identified for the same.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90286606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-5225-2229-4.CH045
M. Elhoseny, A. Farouk, J. Batle, A. Shehab, A. Hassanien
WSN as a new category of computer-based computing platforms and network structures is showing new applications in different areas such as environmental monitoring, health care and military applications. Although there are a lot of secure image processing schemas designed for image transmission over a network, the limited resources and the dynamic environment make it invisible to be used with Wireless Sensor Networks (WSNs). In addition, the current secure data transmission schemas in WSN are concentrated on the text data and are not applicable for image transmission's applications. Furthermore, secure image transmission is a big challenging issue in WSNs especially for the application that uses image as its main data such as military applications. The reason why is because the limited resources of the sensor nodes which are usually deployed in unattended environments. This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE).
{"title":"Secure Image Processing and Transmission Schema in Cluster-Based Wireless Sensor Network","authors":"M. Elhoseny, A. Farouk, J. Batle, A. Shehab, A. Hassanien","doi":"10.4018/978-1-5225-2229-4.CH045","DOIUrl":"https://doi.org/10.4018/978-1-5225-2229-4.CH045","url":null,"abstract":"WSN as a new category of computer-based computing platforms and network structures is showing new applications in different areas such as environmental monitoring, health care and military applications. Although there are a lot of secure image processing schemas designed for image transmission over a network, the limited resources and the dynamic environment make it invisible to be used with Wireless Sensor Networks (WSNs). In addition, the current secure data transmission schemas in WSN are concentrated on the text data and are not applicable for image transmission's applications. Furthermore, secure image transmission is a big challenging issue in WSNs especially for the application that uses image as its main data such as military applications. The reason why is because the limited resources of the sensor nodes which are usually deployed in unattended environments. This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE).","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80751569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-5225-0486-3.CH009
Sanatan Mohanty, S. K. Patra
Wireless Sensor Network (WSN) consists of many tiny, autonomous sensor nodes capable of sensing, computation and communication. The main objective of IEEE 802.15.4 based WSN standard is to provide low cost, low power and short range communication. Providing QoS in WSN is a challenging task due to its severe resource constraints in terms of energy, network bandwidth, memory, and CPU. In this chapter, Quality of Service (QoS) performance evaluation has been carried out for IEEE 802.15.4 networks based WSN star and mesh topology using routing protocols like AODV, DSR and DYMO in QualNet 4.5 simulator. Performance evaluations metrics like Packet Delivery Ratio (PDR), throughput, average end to end delay, energy per goodput bit, network lifetime of battery model and total energy consumption which includes transmission, reception, idle and sleep mode were considered for both the topology. From the simulation studies and analysis, it can be seen that on an average DSR and DYMO performs better than AODV for different traffic load rates.
{"title":"Performance Evaluation of Quality of Service in IEEE 802.15.4-Based Wireless Sensor Networks","authors":"Sanatan Mohanty, S. K. Patra","doi":"10.4018/978-1-5225-0486-3.CH009","DOIUrl":"https://doi.org/10.4018/978-1-5225-0486-3.CH009","url":null,"abstract":"Wireless Sensor Network (WSN) consists of many tiny, autonomous sensor nodes capable of sensing, computation and communication. The main objective of IEEE 802.15.4 based WSN standard is to provide low cost, low power and short range communication. Providing QoS in WSN is a challenging task due to its severe resource constraints in terms of energy, network bandwidth, memory, and CPU. In this chapter, Quality of Service (QoS) performance evaluation has been carried out for IEEE 802.15.4 networks based WSN star and mesh topology using routing protocols like AODV, DSR and DYMO in QualNet 4.5 simulator. Performance evaluations metrics like Packet Delivery Ratio (PDR), throughput, average end to end delay, energy per goodput bit, network lifetime of battery model and total energy consumption which includes transmission, reception, idle and sleep mode were considered for both the topology. From the simulation studies and analysis, it can be seen that on an average DSR and DYMO performs better than AODV for different traffic load rates.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78982941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.4018/978-1-7998-2454-1.ch073
Nassima Bouadem, Rahim Kacimi, A. Tari
Wireless Sensor Networks (WSNs) became omnipresent in our daily life. As a result, they have emerged as a fruitful research topic, because of their advantages, especially their low cost and easy deployment. However, these attractive merits imply that available resources, especially energy, in each sensor node have to be wisely used through different network dynamics. Beside other techniques, duty-cycling (DC) is the first widely used one to save energy in WSNs. However, due to the continuous changes, mainly in the energy availability, the nodes have to operate in a very low DC which is a required strategy in many applications in order to keep the network operational. This article presents a detailed survey that provides an interesting view of different DC schemes which are proposed to tackle the specific WSN challenges, and it also gives a novel classification of DC schemes that includes the most recent techniques. The last part aims to investigate the impact of the low DC on both the network and the application layer.
{"title":"Impact of Duty-Cycling","authors":"Nassima Bouadem, Rahim Kacimi, A. Tari","doi":"10.4018/978-1-7998-2454-1.ch073","DOIUrl":"https://doi.org/10.4018/978-1-7998-2454-1.ch073","url":null,"abstract":"Wireless Sensor Networks (WSNs) became omnipresent in our daily life. As a result, they have emerged as a fruitful research topic, because of their advantages, especially their low cost and easy deployment. However, these attractive merits imply that available resources, especially energy, in each sensor node have to be wisely used through different network dynamics. Beside other techniques, duty-cycling (DC) is the first widely used one to save energy in WSNs. However, due to the continuous changes, mainly in the energy availability, the nodes have to operate in a very low DC which is a required strategy in many applications in order to keep the network operational. This article presents a detailed survey that provides an interesting view of different DC schemes which are proposed to tackle the specific WSN challenges, and it also gives a novel classification of DC schemes that includes the most recent techniques. The last part aims to investigate the impact of the low DC on both the network and the application layer.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76613537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.12677/jsta.2020.82005
张红 郝
Whether the bridge is health or not directly affects the normal operation of the transportation networks, even threatens the safety of people’s life and property. Therefore, the health monitoring of the bridge has a very important social value. Data acquisition is the key to the bridge health monitoring and the basis of the bridge health diagnosis and assessment. A data acquisition system based on NI ELVIS II hardware platform and Labview is developed. It can acquire the environment temperature, wind speed, strain response, tilt posture, vibration response of bridge. Those data are displayed on the monitoring interface which compiled by Labview. The software and hardware implementation of the data acquisition system are introduced in detail. The test results show that the system features the characteristics such as real time capability, simple operation and so on, which may be a useful try for designing bridge health monitoring system in the future.
{"title":"Design and Implementation of Data Acquisition System for Bridge Health Monitoring","authors":"张红 郝","doi":"10.12677/jsta.2020.82005","DOIUrl":"https://doi.org/10.12677/jsta.2020.82005","url":null,"abstract":"Whether the bridge is health or not directly affects the normal operation of the transportation networks, even threatens the safety of people’s life and property. Therefore, the health monitoring of the bridge has a very important social value. Data acquisition is the key to the bridge health monitoring and the basis of the bridge health diagnosis and assessment. A data acquisition system based on NI ELVIS II hardware platform and Labview is developed. It can acquire the environment temperature, wind speed, strain response, tilt posture, vibration response of bridge. Those data are displayed on the monitoring interface which compiled by Labview. The software and hardware implementation of the data acquisition system are introduced in detail. The test results show that the system features the characteristics such as real time capability, simple operation and so on, which may be a useful try for designing bridge health monitoring system in the future.","PeriodicalId":68742,"journal":{"name":"传感技术(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66128388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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