A fixed clustering protocol based on random relay strategy for EHWSN

Luo, Xianquan; Zhang, Chunjiong; Bai, Longju

doi:10.1016/j.dcan.2022.09.005

Cited by 19 publications

(10 citation statements)

References 25 publications

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“…Te voltage outer-loop fuzzy controller and current inner-loop fuzzy controller have the same control rules except that the corresponding input and output variables are diferent, so the two fuzzy PI controllers have similar structures. Based on the fact that a fuzzy control system is composed of input and output variables, fuzzifcation, rule base, fuzzy inference, and defuzzifcation, the adaptive fuzzy PI controller design will be carried out from the following parts [26,27].…”

Section: Dual Closed-loop Flow Control Strategy Based Onmentioning

confidence: 99%

Intelligent Control System Design of Ring Light via IOT Mobile Robot

Kang¹,

Teng²

2023

Journal of Robotics

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In the Internet of Things (IoT) era, the combination of mobile robots and IoT technology has realized the complementary advantages of the IoT and robots, which has brought new challenges and opportunities for the development and application of the IoT and mobile robots. In this study, a mobile robot positioning system based on the wireless positioning technology of the IoT is first designed, and an adaptive federated filtering algorithm based on the confidence of the sensor measurement data is given, and the data fusion processing is carried out for the positioning system to achieve the accurate positioning of the mobile robot. Then, we embed the intelligent control system of the ring lamp and propose an adaptive fuzzy PI double closed loop equalization control strategy, which can automatically identify the number of interlaced parallel and ensure its equalization effect. The experimental results show that the equalization strategy designed in this study has a good equalization effect in the loop interleaving parallel topology, strong adaptive parameter adjustment ability, good robustness, and anti-interference.

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Section: Dual Closed-loop Flow Control Strategy Based Onmentioning

confidence: 99%

Intelligent Control System Design of Ring Light via IOT Mobile Robot

Kang¹,

Teng²

2023

Journal of Robotics

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“…The constraint from Equation (7) guarantees that the remaining amount of RAM in m j exceeds the requested amount of RAM required by task t i (TP j is the list of tasks running in m j ). The constraint from Equation (8) ensures there is enough storage in m j to store the required datasets for t i in the case of data migration (t k is in progress in m j ) and when d l is a remote dataset.…”

Section: Objective Functionmentioning

confidence: 99%

“…the aforementioned time metrics (response time, migration time, waiting time, etc.). For that, we fix the number of machines M to 100 and the number of required data RD varying within the range of [1][2][3][4][5][6][7][8][9][10], while the number of incoming tasks T takes the values 500, 1000, 1500, and 2000.…”

Section: Degree Of Imbalance (Di)mentioning

confidence: 99%

“…As a result, managing big data tasks and supporting dataintensive applications is now possible using cloud data centers [2]. Most of the big data applications [3][4][5][6][7] are in the form of online task processing. However, it is clear that these tasks are both computation-and data-intensive [8], hence it becomes a challenge to efficiently handle them.…”

Section: Introductionmentioning

confidence: 99%

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Online Task Scheduling of Big Data Applications in the Cloud Environment

2023

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The development of big data has generated data-intensive tasks that are usually time-consuming, with a high demand on cloud data centers for hosting big data applications. It becomes necessary to consider both data and task management to find the optimal resource allocation scheme, which is a challenging research issue. In this paper, we address the problem of online task scheduling combined with data migration and replication in order to reduce the overall response time as well as ensure that the available resources are efficiently used. We introduce a new scheduling technique, named Online Task Scheduling algorithm based on Data Migration and Data Replication (OTS-DMDR). The main objective is to efficiently assign online incoming tasks to the available servers while considering the access time of the required datasets and their replicas, the execution time of the task in different machines, and the computational power of each machine. The core idea is to achieve better data locality by performing an effective data migration while handling replicas. As a result, the overall response time of the online tasks is reduced, and the throughput is improved with enhanced machine resource utilization. To validate the performance of the proposed scheduling method, we run in-depth simulations with various scenarios and the results show that our proposed strategy performs better than the other existing approaches. In fact, it reduces the response time by 78% when compared to the First Come First Served scheduler (FCFS), by 58% compared to the Delay Scheduling, and by 46% compared to the technique of Li et al. Consequently, the present OTS-DMDR method is very effective and convenient for the problem of online task scheduling.

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“…The Supreme People's Procuratorate's "Procuratorial Big Data Resource Database" plan is in full progress, and the "Similar Case Guidance Project" established by the Anhui Provincial High Court has been On the basis of mining and analysis of big data, it is possible to quantitatively analyze a large number of judgment documents with the goal of the same judgment in similar cases. The application of judicial big data will make judgment prediction truly possible, thus The development process of particle swarm optimization analysis and legal judgment prediction [16][17][18]. The main development directions are as follows [19].…”

Section: Introductionmentioning

confidence: 99%

Problem Analysis and Application Research in Legal Judgment Prediction Based on Data Mining

2024

jes

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The judgments of some hot cases that exceeded public expectations seem to confirm this. Although the legal certainty is questioned, the judgment remains predictable. The predictability of judgments is a way to enhance judicial authority and maintain judicial credibility. It is also a way to achieve overlapping consensus between the judiciary and the public, provide stable value guidance and behavioral expectations for the public, and promote the generation and development of public rational trust. To enhance public legal trust by improving the predictability of judgments, it is necessary to increase the burden of reasoning for judicial judgments, avoid randomness and contingency, and ensure the adequate provision and substantial disclosure of previous judgment information, so that judgment prediction in the era of big data can truly become possible. The research is to use the optimized particle swarm algorithm as the underlying model to carry out joint modeling and prediction research on the analysis and application of problems in the prediction of legal judgments. According to experimental calculations, the optimized particle swarm algorithm can significantly improve the accuracy and universality of legal judgment prediction. After optimization, the convergence speed is increased by about 5%, and the value of the acceleration factor is more significant.

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A fixed clustering protocol based on random relay strategy for EHWSN

Cited by 19 publications

References 25 publications

Intelligent Control System Design of Ring Light via IOT Mobile Robot

Intelligent Control System Design of Ring Light via IOT Mobile Robot

Online Task Scheduling of Big Data Applications in the Cloud Environment

Problem Analysis and Application Research in Legal Judgment Prediction Based on Data Mining

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