Minimizing Delay Recovery in Migrating Data between Physical Server and Cloud Computing Using Reed-Solomon Code

Alkhonaini, Mimouna; El-Sayed, Hoda

doi:10.1109/hpcc/smartcity/dss.2018.00124

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…However, statistical schemes do not distinguish between trains, stations, sections, etc., and the resulting scheme is thus not targeted. In recent years, scholars in different countries have studied the problem of delay recovery [24][25][26], and, based on random delays in arrivals and departures, the method of rearranging redundant time to improve the utilization of the supplement time has been gradually recognized [27,28].…”

Section: Literature Reviewmentioning

confidence: 99%

Delay recovery model for high-speed trains with compressed train dwell time and running time

et al. 2020

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Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of dispatchers. In this study, the effects of two train operation adjustment actions on train delay recovery were explored using train operation records from scheduled and actual train timetables. First, the modeling data were sorted to extract the possible influencing factors under two typical train operation adjustment actions, namely the compression of the train dwell time at stations and the compression of the train running time in sections. Stepwise regression methods were then employed to determine the importance of the influencing factors corresponding to the train delay recovery time, namely the delay time, the scheduled supplement time, the running interval, the occurrence time, and the place where the delay occurred, under the two train operation adjustment actions. Finally, the gradient-boosted regression tree (GBRT) algorithm was applied to construct a delay recovery model to predict the delay recovery effects of the train operation adjustment actions. A comparison of the prediction results of the GBRT model with those of a random forest model confirmed the better performance of the GBRT prediction model.

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Section: Literature Reviewmentioning

confidence: 99%

Delay recovery model for high-speed trains with compressed train dwell time and running time

et al. 2020

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“…The following is the arrangement of status for a single file transmission from server to cloud storage. • Data Segmentation [10]: Data segmentations split-up the bigger data units into smaller controllable data slices. In our data segmentation, we will be using an algorithm that will take the shortest time possible to segment larger volumes of data packets, while optimizing the memory efficiency of the working machines.…”

Section: General Concept Of the Modelmentioning

confidence: 99%

Performance Evaluation and Examination of Data Transfer: A Review of Parallel Migration in Cloud Storage

Alkhonaini¹,

El-Sayed²

2020

Adv. sci. technol. eng. syst. j.

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Recent years have seen a continued pattern of development in the cloud computing field. Numerous approaches to maximize file transfer capacity are still completely standing for use on cloud computing storage; however, they do not maximize the advantage of data migration scalability and elasticity in cloud storage. One potential problem is that elasticity takes time; however, the scalability attributes that have not been fully exploited include multicore chips and parallelization that can further be leveraged to enhance the overall data transfer performance and efficiency. In that regard, considerable effort has been directed to multiprocessors. Such systems involve a plurality of processors or functioning units capable of independent operation to process separate tasks in parallel. Nevertheless, the penalization is complicated when a task requires several resources or signals to proceed with meaningful computation. Thus, accommodating equitable priority among tasks further complicates operations. In this paper, we propose a parallel server to cloud storage transfer system in which parallelism method can only be utilized in case of transferring a large number of files and applied in order to increase the transfer throughput. The data is transmitted into several chunks via TCP network within the same period slot in a single data path which indicates dataflow on parallelism. Our target in this system is that increasing number of processors and the problem size will simultaneously maintain the efficiency of the data transfer system. The proposed model is based on the combination of dynamic segmentation, CRS, AES, and hashing. In summary, the proposed model shows the potential to enhance the performance by increasing the data transferability. The performance of the proposed model will be measured with the help of comparing the average execution time with the number of processors and speedup of the entire parallel system.

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“…The block can make use of output shortened codewords if the shortened message length, S is given and that is specified as well. Just like encoder, the decoder also uses symbols for the code that the Reed-Solomon reads are in k data symbol and also it is a code in an integer between 0 and 2M-1 and these elements are of the finite field GF (2M) [11,12]. Also like encoder, the decoder has the input and output are integer-valued signals that represent codewords and messages, respectively or messages representing codewords or vice versa or even both or one of them.…”

Section: Description Of the Systemmentioning

confidence: 99%

Development of a Reed-Solomon Error Detection and Correction System

Africa¹

2020

IJETER

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This project scopes into the Reed-Solomon (RS) Code as one of the optimal error detection and correction schemes. RS codes are codes in which adding unnecessary bits to a data in order for it to be reliably recovered even though the presence of errors in transferal, cache, and retrieval, is executed. The encoder for this specific code differs from a binary encoder in that it operates on the multiple bits rather than individual bits giving it the ability to precisely detect and correct error compared to other error and correction schemes. Its unique algorithm may be used in any analog or digital communication system because of it having the highest efficient use of redundancy, ability to adjust block length has a wide range of code rate and is an efficient coding technique perfect for accurate and precise code error detection. Storage devices, wireless communication, satellite communication, digital television, and high-speed modems are constructs of Reed-Solomon.

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Minimizing Delay Recovery in Migrating Data between Physical Server and Cloud Computing Using Reed-Solomon Code

Cited by 3 publications

References 17 publications

Delay recovery model for high-speed trains with compressed train dwell time and running time

Delay recovery model for high-speed trains with compressed train dwell time and running time

Performance Evaluation and Examination of Data Transfer: A Review of Parallel Migration in Cloud Storage

Development of a Reed-Solomon Error Detection and Correction System

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