Differential-Clustering Compression Algorithm for Real-Time Aerospace Telemetry Data

Shi, Xuesen; Shen, Yuyao; Wang, Yongqing; Bai, Li

doi:10.1109/access.2018.2872778

Cited by 18 publications

(24 citation statements)

References 17 publications

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“…In [ 1 ], the authors proposed a differential clustering (D-CLU) compression technique for lossless compression of real-time aeronautical telemetry data. Due to correlation, it was discovered that utilizing a differential compression model successfully enhanced compression performance.…”

Section: Introductionmentioning

confidence: 99%

Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Ramalingam

Mehbodniya

Webber

et al. 2022

Computational Intelligence and Neuroscience

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Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data effectively and efficiently with a high compression ratio and a short processing time. Telemetric information can be packed to control the extra room and association data transmission. In spite of the fact that different examinations on the pressure of telemetric information have been conducted, the idea of telemetric information makes pressure incredibly troublesome. The purpose of this study is to offer a subsampled and balanced recurrent neural lossless data compression (SB-RNLDC) approach for increasing the compression rate while decreasing the compression time. This is accomplished through the development of two models: one for subsampled averaged telemetry data preprocessing and another for BRN-LDC. Subsampling and averaging are conducted at the preprocessing stage using an adjustable sampling factor. A balanced compression interval (BCI) is used to encode the data depending on the probability measurement during the LDC stage. The aim of this research work is to compare differential compression techniques directly. The final output demonstrates that the balancing-based LDC can reduce compression time and finally improve dependability. The final experimental results show that the model proposed can enhance the computing capabilities in data compression compared to the existing methodologies.

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Section: Introductionmentioning

confidence: 99%

Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Ramalingam

Mehbodniya

Webber

et al. 2022

Computational Intelligence and Neuroscience

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“…Real-time database systems (RTDBSs) have been widely applied in many areas. Examples of such applications include industrial control [1], vehicular control [2], aerospace control [3], health monitoring [4] and robot control [5]. There are many transactions in a RTDBS.…”

Section: Introductionmentioning

confidence: 99%

Guarantee the Quality-of-Service of Control Transactions in Real-Time Database Systems

Deng

Zhou

et al. 2020

IEEE Access

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Temporal consistency analysis is an important problem in Real-Time Database Systems (RTDBSs). Most of existing works on hybrid transaction co-scheduling focus on exploring effective deadline and period assignment methods which can guarantee the temporal consistency of data objects and the schedulability of transactions. To the best of our knowledge, all existing researches have not yet invested sufficient efforts on guaranteeing the Quality of Service (QoS) of control transactions and allow control transactions finish their execution after the data obtained by these control transactions expire. In this paper, we define a new problem of how to schedule a hybrid transaction set under the guarantee on QoS of control transactions. Two deadline and period assignment methods for addressing the defined problem are proposed in this work. Both the proposed methods support the Earliest Deadline First (EDF) scheduling. Extensive experiments are conducted to evaluate the performances of the proposed methods in terms of acceptance ratio, processor workload and efficiency. INDEX TERMS Real-time database systems, QoS of control transactions, hybrid transaction set, the EDF scheduling, deadline and period assignment.

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“…Along with the recent widespread expansion of aerospace applications, the demand for a variety of wireless communication technologies is gradually increasing in rocket launch events [1][2][3]. The wireless communication systems are generally used for collecting the information about the rocket status [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Method for Estimating Optimal Position of S-Band Relay Station through Path Loss Analysis in an Outdoor Environment

et al. 2020

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This article investigates a novel estimation method to optimize the position of a relay station of the S-band telemetry system in outdoor environments. To determine an optimal relay station position, complex terrain surface and buildings near the Naro Space Center are included in the EM (Electromagnetic) simulation. The optimal relay station position is then determined using the estimation method by comparing the path losses from the rocket to the main station and some candidate positions of the relay station. To better understand the path loss, the ray analysis is also conducted, and the result demonstrates that once the rocket altitude to be covered by the relay station is determined, it is possible to find the optimum position of the relay station.

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Differential-Clustering Compression Algorithm for Real-Time Aerospace Telemetry Data

Cited by 18 publications

References 17 publications

Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Guarantee the Quality-of-Service of Control Transactions in Real-Time Database Systems

Method for Estimating Optimal Position of S-Band Relay Station through Path Loss Analysis in an Outdoor Environment

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