Pub Date : 2023-08-22DOI: 10.1080/00051144.2023.2243143
S. S, L. Gunisetti, Shirin Bhanu Koduri, B. Kiranmai
The performance of Wireless Sensor Networks (WSNs), a subset of Wireless Ad-hoc Networks, is significantly influenced by the application, lifetime, storage capacity, processing power, changes in topology, communication medium, and bandwidth. These restrictions call for a strong data transport control in WSNs that takes into account quality of service, energy efficiency, and congestion management. Wireless networks face a significant difficulty with congestion which impacts on the loss rate, channel quality, link utilization, the number of retransmissions, traffic flow, network lifetime, latency, energy, and throughput are all negatively impacted by congestion in WSNs. Since the routing problem has been shown to be NP-hard and it has been realized that a heuristic based method delivers better performance than their traditional counterparts, routing is one of the most popular methods for reducing the energy consumption of nodes and increasing throughput in WSNs. This research provides a Rate Aware Congestion Control (RACC), an effective congestion avoidance method that enhances network performance by applying Modified Harris Hawks Optimization (MHHO). Nodes are initially clustered using the DBSCAN clustering algorithm. When compared to existing approaches, the simulation outcomes of the developed technique indicate superior service, low delay, high energy, packet delivery ratio and increased living nodes.
{"title":"Energy efficient congestion control scheme based on Modified Harris Hawks Optimization for heavy traffic Wireless Sensor Networks","authors":"S. S, L. Gunisetti, Shirin Bhanu Koduri, B. Kiranmai","doi":"10.1080/00051144.2023.2243143","DOIUrl":"https://doi.org/10.1080/00051144.2023.2243143","url":null,"abstract":"The performance of Wireless Sensor Networks (WSNs), a subset of Wireless Ad-hoc Networks, is significantly influenced by the application, lifetime, storage capacity, processing power, changes in topology, communication medium, and bandwidth. These restrictions call for a strong data transport control in WSNs that takes into account quality of service, energy efficiency, and congestion management. Wireless networks face a significant difficulty with congestion which impacts on the loss rate, channel quality, link utilization, the number of retransmissions, traffic flow, network lifetime, latency, energy, and throughput are all negatively impacted by congestion in WSNs. Since the routing problem has been shown to be NP-hard and it has been realized that a heuristic based method delivers better performance than their traditional counterparts, routing is one of the most popular methods for reducing the energy consumption of nodes and increasing throughput in WSNs. This research provides a Rate Aware Congestion Control (RACC), an effective congestion avoidance method that enhances network performance by applying Modified Harris Hawks Optimization (MHHO). Nodes are initially clustered using the DBSCAN clustering algorithm. When compared to existing approaches, the simulation outcomes of the developed technique indicate superior service, low delay, high energy, packet delivery ratio and increased living nodes.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47721086","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 : 2023-08-18DOI: 10.1080/00051144.2023.2246246
S. S, R. S, S. K. G, S. S
The creation of a network of tiny sensors installed in, on or around the human body has been facilitated by advancements in wireless communications and wearable devices. Because of its potential to transform healthcare delivery, Wireless Body Area Network (WBAN) has been increasingly important in modern medical systems over the last decade. Individual nodes (sensors and actuators) embedded in a person's clothing, body, or skin form a WBAN. Both academia and industry have increased their efforts in WBAN research and development. The wearable antenna, whether on or off the human body, is a critical component of contact with particular design in WBAN networks. Ultra-wideband (UWB) technology can provide high-capacity, short-range communications with minimal energy consumption, which is appropriate for wireless body area networks. The human body's involvement in such a device creates significant challenges for both the wearable antenna's construction and the broadcast paradigm. To achieve many functionalities, multi-band and broadband antennas are better solutions. The proposed multi-band antenna is constructed from a FR4 substrate with dimensions of (24 × 25 × 1.6) mm3. The proposed design was successfully tested with different configurations and enhanced with a broad impedance bandwidth of over 100 percent, where the UWB frequency spectrum encompassed the range from 3 to 9 GHz with a reflective coefficient of −15 dB and gain of 2.5 dBi, as well as fair radiation patterns in the Federal Communications Commission range. The SAR value of the devised antenna with and without SRR being 2 W/kg, 3.5 W/kg, respectively. This solution may be a worthy contender for meeting the UWB demands as a result, could be an excellent fit for wireless body technologies.
{"title":"Performance analysis of triple-band miniaturized hexagonal ultra-wideband antenna for wireless body worn applications","authors":"S. S, R. S, S. K. G, S. S","doi":"10.1080/00051144.2023.2246246","DOIUrl":"https://doi.org/10.1080/00051144.2023.2246246","url":null,"abstract":"The creation of a network of tiny sensors installed in, on or around the human body has been facilitated by advancements in wireless communications and wearable devices. Because of its potential to transform healthcare delivery, Wireless Body Area Network (WBAN) has been increasingly important in modern medical systems over the last decade. Individual nodes (sensors and actuators) embedded in a person's clothing, body, or skin form a WBAN. Both academia and industry have increased their efforts in WBAN research and development. The wearable antenna, whether on or off the human body, is a critical component of contact with particular design in WBAN networks. Ultra-wideband (UWB) technology can provide high-capacity, short-range communications with minimal energy consumption, which is appropriate for wireless body area networks. The human body's involvement in such a device creates significant challenges for both the wearable antenna's construction and the broadcast paradigm. To achieve many functionalities, multi-band and broadband antennas are better solutions. The proposed multi-band antenna is constructed from a FR4 substrate with dimensions of (24 × 25 × 1.6) mm3. The proposed design was successfully tested with different configurations and enhanced with a broad impedance bandwidth of over 100 percent, where the UWB frequency spectrum encompassed the range from 3 to 9 GHz with a reflective coefficient of −15 dB and gain of 2.5 dBi, as well as fair radiation patterns in the Federal Communications Commission range. The SAR value of the devised antenna with and without SRR being 2 W/kg, 3.5 W/kg, respectively. This solution may be a worthy contender for meeting the UWB demands as a result, could be an excellent fit for wireless body technologies.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42424532","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 : 2023-08-17DOI: 10.1080/00051144.2023.2241770
Noora V. T., S. V. Jinny
The efficacy of Wireless Sensor Networks (WSNs), a subset of Wireless Ad-hoc Networks, is significantly impacted by application, lifetime, storage capacity, processing power, topology changes, communication medium, and bandwidth. These constraints necessitate a robust data transport control in WSNs that considers service quality, energy efficiency, and congestion management. Congestion is a significant issue for wireless networks. Congestion in WSNs has deleterious effects on loss rate, channel quality, link utilization, number of retransmissions, traffic flow, network lifetime, latency, energy, and throughput. The predominance of WSNs necessitates the development of more efficient congestion control algorithms. Since it has been demonstrated that the routing problem is NP-hard and that heuristic-based methods outperform their traditional counterparts, routing is one of the most prevalent techniques for reducing the energy consumption of nodes and increasing throughput in WSNs. This study presents Rate Aware Congestion Control (RACC), an efficient method for avoiding congestion that improves network performance by employing Modified Harris Hawks Optimisation (MHHO). Initially, nodes are clustered utilizing the DBSCAN clustering algorithm. The simulation results of the developed technique indicate superior service, low latency, high energy, a high packet delivery ratio and an increasing number of living nodes when compared to existing approaches.
{"title":"Software Defined Networking Controller (SDNC): a robust security architecture for SDN-based 5G networks","authors":"Noora V. T., S. V. Jinny","doi":"10.1080/00051144.2023.2241770","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241770","url":null,"abstract":"The efficacy of Wireless Sensor Networks (WSNs), a subset of Wireless Ad-hoc Networks, is significantly impacted by application, lifetime, storage capacity, processing power, topology changes, communication medium, and bandwidth. These constraints necessitate a robust data transport control in WSNs that considers service quality, energy efficiency, and congestion management. Congestion is a significant issue for wireless networks. Congestion in WSNs has deleterious effects on loss rate, channel quality, link utilization, number of retransmissions, traffic flow, network lifetime, latency, energy, and throughput. The predominance of WSNs necessitates the development of more efficient congestion control algorithms. Since it has been demonstrated that the routing problem is NP-hard and that heuristic-based methods outperform their traditional counterparts, routing is one of the most prevalent techniques for reducing the energy consumption of nodes and increasing throughput in WSNs. This study presents Rate Aware Congestion Control (RACC), an efficient method for avoiding congestion that improves network performance by employing Modified Harris Hawks Optimisation (MHHO). Initially, nodes are clustered utilizing the DBSCAN clustering algorithm. The simulation results of the developed technique indicate superior service, low latency, high energy, a high packet delivery ratio and an increasing number of living nodes when compared to existing approaches.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47063481","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 : 2023-08-15DOI: 10.1080/00051144.2023.2243144
K. Roslin Dayana, P. Shobha rani
Cloud data storage lets customers store vast amounts of data cheaply on demand. Cryptographic role-based access control (RBAC) systems preserve cloud data privacy by restricting access to users. This study develops a trust model to reason about and improve data security in cryptographic RBAC cloud storage systems. The trust degrees of the user determine the access rights to the data and are performed by User Activity Monitoring Agent (UAMA). Two different misconducts of users such as access policy violation and data leakage affect the trust degree of the user, which in turn upgrades the access policy. In addition, the user has to decrypt the data for gaining information from it, which is a second line of security. The performance of trust based RBAC scheme is evaluated with respect to different parameters such as illegitimate user detection, memory consumption, data storage with retrieval time and the proposed work performs better.
{"title":"Trust aware cryptographic role based access control scheme for secure cloud data storage","authors":"K. Roslin Dayana, P. Shobha rani","doi":"10.1080/00051144.2023.2243144","DOIUrl":"https://doi.org/10.1080/00051144.2023.2243144","url":null,"abstract":"Cloud data storage lets customers store vast amounts of data cheaply on demand. Cryptographic role-based access control (RBAC) systems preserve cloud data privacy by restricting access to users. This study develops a trust model to reason about and improve data security in cryptographic RBAC cloud storage systems. The trust degrees of the user determine the access rights to the data and are performed by User Activity Monitoring Agent (UAMA). Two different misconducts of users such as access policy violation and data leakage affect the trust degree of the user, which in turn upgrades the access policy. In addition, the user has to decrypt the data for gaining information from it, which is a second line of security. The performance of trust based RBAC scheme is evaluated with respect to different parameters such as illegitimate user detection, memory consumption, data storage with retrieval time and the proposed work performs better.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43046430","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 : 2023-08-15DOI: 10.1080/00051144.2023.2243142
S. Lekashri, K. Madhusudhan, A. Sivasangari, P. Gururama Senthilvel
An adaptive real-time gate scheduling scheme for time perceptive stream or packet flow is proposed to improve the standards of Ultra Low Latency during data transmission. For highly dynamic network conditions, the conventional configuration scheme is not suitable and therefore an adaptive real-time gate scheduling method is proposed for time perceptive streams. This dynamicity reconfiguration is difficult and the scheduling problem is formulated using Field Programmable Gate Array – Boolean Satisfiability Problem (FPGA-BSP) solver. This proposed scheme highly helps in network dynamicity conditions with good bandwidth utilization and high flexibility. End-to-end latency is required to be on sub-milliseconds order deal with the applications such as Industrial Internet of Things, 5G and 6G mobile, tactile internet and so on. Simulation analysis is carried out to prove the efficiency of the proposed model.
{"title":"Adaptive real-time reconfiguration gate scheduling scheme using time perceptive stream","authors":"S. Lekashri, K. Madhusudhan, A. Sivasangari, P. Gururama Senthilvel","doi":"10.1080/00051144.2023.2243142","DOIUrl":"https://doi.org/10.1080/00051144.2023.2243142","url":null,"abstract":"An adaptive real-time gate scheduling scheme for time perceptive stream or packet flow is proposed to improve the standards of Ultra Low Latency during data transmission. For highly dynamic network conditions, the conventional configuration scheme is not suitable and therefore an adaptive real-time gate scheduling method is proposed for time perceptive streams. This dynamicity reconfiguration is difficult and the scheduling problem is formulated using Field Programmable Gate Array – Boolean Satisfiability Problem (FPGA-BSP) solver. This proposed scheme highly helps in network dynamicity conditions with good bandwidth utilization and high flexibility. End-to-end latency is required to be on sub-milliseconds order deal with the applications such as Industrial Internet of Things, 5G and 6G mobile, tactile internet and so on. Simulation analysis is carried out to prove the efficiency of the proposed model.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44224265","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 : 2023-08-15DOI: 10.1080/00051144.2023.2246242
Immanuvel Arokia James K., M. P., G. G, K. A.
Cooperative communication has gained a lot of popularity recently. Through a variety of shortest path methods, this article's paradigm may efficiently reduce the amount of power consumed and hop transmission. In this research, we construct the Minimum Power Least Cost Routing (MPLCR) algorithm and evaluate its performance. The design of the proposed algorithm took into account link computation, sequential scanning algorithm approach, and balance (residual) energy. To prevent connection failures and lessen network traffic, the link calculation is used to choose the best route (relay node). In order to reduce network power consumption, a sequential scanning technique was used to find the shortest path with the fewest hops. And also discuss relay nodes and their characteristics in order to improve the transmission stream's quality of service. An ideal path is one that ensures end-to-end transmission while using the least amount of transmitted power. The minimum power least cost routing algorithm uses cooperative communications to help build the smallest power route. When compared to the current algorithms, the proposed approach uses less energy by more than 30%.
{"title":"Energy efficient optimal hop transmission using minimum power least cost algorithm in cooperative routing for wireless sensor network","authors":"Immanuvel Arokia James K., M. P., G. G, K. A.","doi":"10.1080/00051144.2023.2246242","DOIUrl":"https://doi.org/10.1080/00051144.2023.2246242","url":null,"abstract":"Cooperative communication has gained a lot of popularity recently. Through a variety of shortest path methods, this article's paradigm may efficiently reduce the amount of power consumed and hop transmission. In this research, we construct the Minimum Power Least Cost Routing (MPLCR) algorithm and evaluate its performance. The design of the proposed algorithm took into account link computation, sequential scanning algorithm approach, and balance (residual) energy. To prevent connection failures and lessen network traffic, the link calculation is used to choose the best route (relay node). In order to reduce network power consumption, a sequential scanning technique was used to find the shortest path with the fewest hops. And also discuss relay nodes and their characteristics in order to improve the transmission stream's quality of service. An ideal path is one that ensures end-to-end transmission while using the least amount of transmitted power. The minimum power least cost routing algorithm uses cooperative communications to help build the smallest power route. When compared to the current algorithms, the proposed approach uses less energy by more than 30%.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47748675","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 : 2023-08-11DOI: 10.1080/00051144.2023.2241792
R. Krishnan, E. G. Julie
ABSTRACT The support rendered by artificial intelligence in plant disease diagnosis and with drastic progression in the agricultural technology, it is necessary to do pertinent research for the cause of long-term agricultural development. Numerous diseases like early and late blight have a significant influence on the quality and quantity of potatoes. Manual interpretation turns out to be a time-consuming process in sorting out leaf diseases. In order to classify various diseases like fungal, viral and bacterial infections in the potato leaf, an enhanced Convolution Neural Network based on VGG16 is used for potato leaf disease classification. Improved Median filter is also used which eradicates the noise to a greater extent. The convolution layers of VGG16 along with the Inception and the SE block are used in this research for classification. The global average pooling layer is used to reduce model training parameters, layer and Squeeze and Excitation Network attention mechanism is used to improve the model’s ability to extract features. The approximate calculations can be done by using soft computing. Compared with other traditional convolutional neural networks, the proposed model achieved the highest classification accuracy of 99.3%
{"title":"Computer aided detection of leaf disease in agriculture using convolution neural network based squeeze and excitation network","authors":"R. Krishnan, E. G. Julie","doi":"10.1080/00051144.2023.2241792","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241792","url":null,"abstract":"ABSTRACT The support rendered by artificial intelligence in plant disease diagnosis and with drastic progression in the agricultural technology, it is necessary to do pertinent research for the cause of long-term agricultural development. Numerous diseases like early and late blight have a significant influence on the quality and quantity of potatoes. Manual interpretation turns out to be a time-consuming process in sorting out leaf diseases. In order to classify various diseases like fungal, viral and bacterial infections in the potato leaf, an enhanced Convolution Neural Network based on VGG16 is used for potato leaf disease classification. Improved Median filter is also used which eradicates the noise to a greater extent. The convolution layers of VGG16 along with the Inception and the SE block are used in this research for classification. The global average pooling layer is used to reduce model training parameters, layer and Squeeze and Excitation Network attention mechanism is used to improve the model’s ability to extract features. The approximate calculations can be done by using soft computing. Compared with other traditional convolutional neural networks, the proposed model achieved the highest classification accuracy of 99.3%","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42064067","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 : 2023-08-02DOI: 10.1080/00051144.2023.2241774
M. S. Karthika Devi, R. Baskaran
Digital transition has started to change the way people read news articles more through a digital device and less on paper. Youngsters today do not spend enough time reading news articles. In this work, a knowledge-driven news story generation using collaborative learning to represent the gist of news is proposed. The entire work focuses on two major concerns. Initially, the dialogues associated with the corresponding speaker are extracted from the news. Secondly, the audio of the mapped dialogues is incorporated into the final video. Logistic Regression is deployed to identify the theme the news. Deep learning techniques are employed to identify the main characters in a supervised manner using Named Entity Recognition (NER) tagging algorithm, suitable cartoon dispositions and their semantic relations. This approach improves not the reader's comprehension and creativity but also improves mutual goals, opportunities for peer discussion and engaging the underachievers to think reflexively. In addition, it also improves the learner’s motivation and participation. The proposed framework outperforms an accuracy of 83.98% when compared with conventional methods also suggests that the readers found the packages interesting and informative on digital devices. Moreover, this method can be used efficiently in real-time for various applications.
{"title":"Newsgist: video generation from news stories","authors":"M. S. Karthika Devi, R. Baskaran","doi":"10.1080/00051144.2023.2241774","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241774","url":null,"abstract":"Digital transition has started to change the way people read news articles more through a digital device and less on paper. Youngsters today do not spend enough time reading news articles. In this work, a knowledge-driven news story generation using collaborative learning to represent the gist of news is proposed. The entire work focuses on two major concerns. Initially, the dialogues associated with the corresponding speaker are extracted from the news. Secondly, the audio of the mapped dialogues is incorporated into the final video. Logistic Regression is deployed to identify the theme the news. Deep learning techniques are employed to identify the main characters in a supervised manner using Named Entity Recognition (NER) tagging algorithm, suitable cartoon dispositions and their semantic relations. This approach improves not the reader's comprehension and creativity but also improves mutual goals, opportunities for peer discussion and engaging the underachievers to think reflexively. In addition, it also improves the learner’s motivation and participation. The proposed framework outperforms an accuracy of 83.98% when compared with conventional methods also suggests that the readers found the packages interesting and informative on digital devices. Moreover, this method can be used efficiently in real-time for various applications.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43755556","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 : 2023-08-02DOI: 10.1080/00051144.2023.2236857
Abdul Rahman Samewoi, Norsinnira Zainul Azlan, Md. Raisuddin Khan
The previous regressor-based control method to control two cooperative manipulators in handling a deformable object leads to complex calculations and complicated programming in experimental hardware tests. There is an existing lack of studies about the development of the controller based on a partial differential equation (PDE)-based model and considering the model’s uncertainties. Previous studies have shown fewer experimental validations regarding two cooperative manipulators that handle deformable objects under uncertain model parameters. This study proposes a composite controller comprising a function approximation technique (FAT)-based adaptive control (FATAC) for a slow subsystem and a velocity feedback control (VFC) for a fast subsystem. The proposed FATAC is used for trajectory tracking, and VFC is used to suppress the vibration of the deformable object. Lyapunov stability analysis has been carried out to design controllers that stabilize a non-linear system of two cooperative manipulators handling the flexible object. Simulation and hardware experimental tests have been carried out to validate the performance of proposed controllers. The results verified that the proposed composite controller comprising the FATAC has successfully driven the cooperative manipulators to handle the deformable object so that it follows the desired trajectories. The VFC has successfully suppressed the transverse vibration of the deformable object.
{"title":"FAT-based adaptive and velocity feedback control of cooperative manipulators handling a flexible object","authors":"Abdul Rahman Samewoi, Norsinnira Zainul Azlan, Md. Raisuddin Khan","doi":"10.1080/00051144.2023.2236857","DOIUrl":"https://doi.org/10.1080/00051144.2023.2236857","url":null,"abstract":"The previous regressor-based control method to control two cooperative manipulators in handling a deformable object leads to complex calculations and complicated programming in experimental hardware tests. There is an existing lack of studies about the development of the controller based on a partial differential equation (PDE)-based model and considering the model’s uncertainties. Previous studies have shown fewer experimental validations regarding two cooperative manipulators that handle deformable objects under uncertain model parameters. This study proposes a composite controller comprising a function approximation technique (FAT)-based adaptive control (FATAC) for a slow subsystem and a velocity feedback control (VFC) for a fast subsystem. The proposed FATAC is used for trajectory tracking, and VFC is used to suppress the vibration of the deformable object. Lyapunov stability analysis has been carried out to design controllers that stabilize a non-linear system of two cooperative manipulators handling the flexible object. Simulation and hardware experimental tests have been carried out to validate the performance of proposed controllers. The results verified that the proposed composite controller comprising the FATAC has successfully driven the cooperative manipulators to handle the deformable object so that it follows the desired trajectories. The VFC has successfully suppressed the transverse vibration of the deformable object.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226764","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 : 2023-08-01DOI: 10.1080/00051144.2023.2241766
Narmadha A. S., M. S, D. S. N.
Mobile Ad-hoc Networks (MANETs) are wireless networks formed dynamically by connecting or leaving nodes to and from the network without any fixed infrastructure. These categories of wireless networks are susceptible to different attacks based on their dynamic topological structure. Due to this, security is a primary constraint in MANETs to preserve communication between mobile nodes. A Deep Neural Learned Projective Pursuit Regression-based Watchdog Malicious Node Detection and Isolation (DNLPPR-WMNDI) technique is proposed and modelled in this paper to improve the security feature of MANETs. The newly proposed DNLPPR-WMNDI technique initially selects the neighbouring nodes by applying the projection pursuit regression function. In multicasting, the route paths are established through the intermediate node with the help of control commands named RREQ and RREP. After then, Watchdog Malicious Node Detection and Isolation (WMNDI) technique is applied to detect malicious nodes based on the data packet forwarding time. Basically, a malicious node is affected by a node isolation attack. For better communication, a malicious node is isolated from the network and multicast routing is carried out by selecting the next neighbouring node and this improves the communication security. Simulation is done for the developed technique based on different performance metrics.
{"title":"Watchdog malicious node detection and isolation using deep learning for secured communication in MANET","authors":"Narmadha A. S., M. S, D. S. N.","doi":"10.1080/00051144.2023.2241766","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241766","url":null,"abstract":"Mobile Ad-hoc Networks (MANETs) are wireless networks formed dynamically by connecting or leaving nodes to and from the network without any fixed infrastructure. These categories of wireless networks are susceptible to different attacks based on their dynamic topological structure. Due to this, security is a primary constraint in MANETs to preserve communication between mobile nodes. A Deep Neural Learned Projective Pursuit Regression-based Watchdog Malicious Node Detection and Isolation (DNLPPR-WMNDI) technique is proposed and modelled in this paper to improve the security feature of MANETs. The newly proposed DNLPPR-WMNDI technique initially selects the neighbouring nodes by applying the projection pursuit regression function. In multicasting, the route paths are established through the intermediate node with the help of control commands named RREQ and RREP. After then, Watchdog Malicious Node Detection and Isolation (WMNDI) technique is applied to detect malicious nodes based on the data packet forwarding time. Basically, a malicious node is affected by a node isolation attack. For better communication, a malicious node is isolated from the network and multicast routing is carried out by selecting the next neighbouring node and this improves the communication security. Simulation is done for the developed technique based on different performance metrics.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"14 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41296910","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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