Radar sensor network resource allocation for fused target tracking: A brief review

Yan, Junkun; Jiao, Hao; Pu, Wenqiang; Shi, Chenguang; Dai, Jinhui; Liu, Hongwei

doi:10.1016/j.inffus.2022.06.009

Cited by 112 publications

(37 citation statements)

References 123 publications

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“…e multiple objective functions in (8) are termed as the minimization function that represents SCADA parametric values to be much lower than values in operational cases. All the formulated equations are derived using a basic set of formulations from SCADA parametric real and reactive power phase [24][25][26][27]. us in order to increase the accuracy of SCADA measurements in industrial systems, an optimization algorithm is integrated and it is described in the subsequent section.…”

Section: Scada For Industrial Applications: An Analytical Modelmentioning

confidence: 99%

“…Hence a learning algorithm is chosen for preprocessing all the necessary data where the appliances in industries are protected without any external intrusion attacks [28,29]. In addition, SCADA system requires the input data to start from the initial state, thus providing multiple solutions for controlling a particular problem [27,30,31]. Since multiple solutions are provided, optimal paths are chosen at the output end for handling distinct alert situations, and one of the major advantages of reinforcement learning algorithm is that all decisions are made in a sequential manner and thus the next state output is determined using previous case problems.…”

Section: Optimization Algorithmmentioning

confidence: 99%

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Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

Khadidos

Manoharan³

et al. 2022

International Transactions on Electrical Energy Systems

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e process of ensuring automatic operation for industrial appliances using both supervision and control techniques is a challenging task.erefore, this article focuses on implementing Supervisory Control and Data Acquisition (SCADA) for controlling all industrial appliances. e design process of implementation case is performed using an analytical framework by examining the primary energy sources at the initial state; thus, a smart network is supported. e designed mathematical model is integrated with a learning technique that allocates resources at proper quantities. Further, the complex manual tuning of individual appliances is avoided in the projected method as the input variables are driven in a direct way at reduced loss state. In addition, the data processing state of individual appliances is carried out using central data controller where all parametric values are stored. In case any errors are observed, then SCADA network fixes the error in an automated way, reducing end-to-end delays in all appliances. To validate the effectiveness of the proposed method, five scenarios are examined and simulated where outcomes prove that SCADA network using learning models provides optimal results on an average of 84 percent as compared to the existing models without learning algorithm.

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Section: Scada For Industrial Applications: An Analytical Modelmentioning

confidence: 99%

Section: Optimization Algorithmmentioning

confidence: 99%

Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

Khadidos

Manoharan³

et al. 2022

International Transactions on Electrical Energy Systems

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“…In fact, the current Internet of ings only realizes the interconnection between specific devices in specific scenarios. In the future, with the continuous development of Internet of ings technology, the Internet of Everything can be truly realized [24][25][26].…”

Section: Internet Of Ingsmentioning

confidence: 99%

Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology

Diao

Sun

2022

Mathematical Problems in Engineering

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The key identification element of the smart factory is the interconnection between devices, which solves the production method and development dilemma of the factory under Industry 3.0 and previous models. The new article published by Xinhua News Agency on January 16, 2022, advocates the idea of industry+ Internet, and its main goal is to realize intelligent production. At present, smart factories have become the main development direction of industrial enterprises in the world. 5G technology has been rapidly deployed with the development of mobile communication, and its performance has also been greatly improved compared to previous communication technologies. After China put forward the smart manufacturing 2025 plan, although a large number of enterprises are still lingering in the process of research, learning, and exploration, the idea of Industry 4.0 has taken root in various intelligent manufacturing enterprises, and the development route of Chinese manufacturing enterprises in the future has been ahead of schedule. Direction. Based on the basic theory of Industry 4.0, 5G wireless communication, Internet of Things, and smart factories, this paper firstly distributed questionnaires to 20 enterprises with smart factories by means of network and interview and reanalyzed the collected questionnaires by regression analysis method and then used the questionnaire scale analysis method to analyze the reliability and validity of the questionnaire and combined with the results of the questionnaire analysis to analyze the problems existing in the current smart factory. Finally, based on the background of Industry 4.0 and 5G communication technology, combined with the Internet of Things technology, the development layout of the smart factory is designed; that is, based on the elliptic curve encryption algorithm, the signature mechanism of mutual trust of all electronic devices in the IoT smart factory is set to improve the smart factory.

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“…Resource sharing is possible in the community cloud. en there is the service-based category to consider, which can be categorized into three parts, namely IaaS, PaaS, and SaaS [31][32][33][34]. IaaS is mainly for infrastructure like disk and servers (virtual), PaaS is mainly for a platform like databases and execution frameworks [35], and SaaS is mainly for the software resources like mailing services and application services.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Client Cloud Environment to Secure Data Communication with Alert Protocol

Soni

Srivastava

Bhatt³

et al. 2022

Mathematical Problems in Engineering

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Cloud computing is a technology that provides resources and utility services based on user demand. Due to this demand, efficient cloud security protocols are highly required, especially at the time of data communication for user authentication and data aggregation. The data communication scenarios are majorly affected by the security threats in the cloud computing environment. This article provides a practical approach to developing an efficient and empirical cloud framework in terms of cloud protocol. The framework uses fuzzy c-means (FCM) algorithm to group data, and calculation is done individually or associatively to rank the text data. Uploaded data are passed to a simple additive weighting (SAW) algorithm for ranking and making decision selection. The framework executes in three phases, namely data preprocessing, clustering, and automatic data security with an alert mechanism. The process is completely automated so there is no need of considering the individual files for the processing and the data held will be appropriately correlated with the sharing inter-cloud environment. To inspect security issues, the proposed framework is secured by three different security algorithms. The encryption process is completed by Rivest Cipher 6 (RC6); the substitution process is done by Advanced Encryption Standard (AES); and key generation is done by RC6, AES, and Rivest-Shamir-Adleman (RSA) approaches collectively. Based on the given situations, these standard approaches were automatically applied separately or collectively. Unauthorized access trapping and data deletion mechanism are also provided in the proposed framework. The experimental results with a comparative study depicted the effectiveness of the proposed work.

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Radar sensor network resource allocation for fused target tracking: A brief review

Cited by 112 publications

References 123 publications

Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm

Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology

An Empirical Client Cloud Environment to Secure Data Communication with Alert Protocol

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