Mobile-edge computing framework with data compression for wireless network in energy internet

Liu, Luning; Chen, Xin; Lu, Zhaoming; Wang, Luhan; Wen, Xiangming

doi:10.26599/tst.2018.9010124

Cited by 39 publications

(22 citation statements)

References 14 publications

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“…Zhang et al [9][10][11] researched related data mining techniques such as business service recommendation and service quality query, Chen et al [12][13] researched data for business intelligence and business service computing. Data mining technology is also widely used in e-commerce, media, energy services, automotive engineering and other fields [14][15][16][17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

Artificial Immune Network Clustering Based on a Cultural Algorithm

Deng

Yang

Liu

2020

Preprint

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Data mining technology has been applied in many fields. Prototype-based cluster analysis is an important data mining method, but its ability to discover knowledge is limited because of the need to know the number of target data categories and cluster prototypes in advance. Artificial immune evolutionary network clustering is a clustering method based on network structure. Compared with prototype-based cluster analysis, it has the advantage of realizing unsupervised learning and clustering without any prior knowledge of data. However, artificial immune evolutionary network clustering also has problems such as a lack of guidance in the clustering process, fuzzy boundary sensitivity, and difficulty in determining parameters. To solve these problems, an artificial immune network clustering algorithm based on a cultural algorithm is proposed. First, three kinds of knowledge are constructed: normative knowledge is used to regulate the spatial range of population initialization to avoid blindness; state knowledge is used to distinguish the type of antigen, and immune defense measures are taken to prevent the network structure caused by noise and boundaries from being unclear; topology knowledge is used to guide the antigen for optimal antibody search. Second, topology knowledge in the cultural algorithm is used to characterize the distribution of antigens and antibodies in space, and elite learning is used to improve the traditional clone mutation operator. Based on the shadow set theory, a method for adaptively determining the compression threshold is proposed. Finally, the results of simulation experiments show that the proposed algorithm can effectively overcome the above problems, and the clustering performances on a synthetic dataset and an actual dataset are satisfactory.

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Section: Introductionmentioning

confidence: 99%

Artificial Immune Network Clustering Based on a Cultural Algorithm

Deng

Yang

Liu

2020

Preprint

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“…Astronomical data have certain characteristics, such as large amounts of data, real-time requirements [11], complicated calculation processes [12], heterogeneous calculation nodes [13], diverse storage models, various data access patterns [14], high expansibility, etc. High performance computing, distributed computing, parallel computing, uniform resource management, container technology and telescope observation control system technology are needed [15].…”

Section: Introductionmentioning

confidence: 99%

Data Processing Scheme Based on Blockchain

Xu²,

Huang

et al. 2020

Preprint

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In the white paper written on Bitcoin, a chain of blocks was proposed by Satoshi Nakamoto. Since then, blockchain has been rapidly developed. Blockchain is not only limited to the field of cryptocurrency but also has been extensively applied to the Internet of Things (IoT), supply chain finance, electronic evidence storage, data sharing, and e-government fields. Both the public chain and the alliance chain have been extensively developed. In the data processing field, blockchain has a particularly good application potential. The Square Kilometre Array (SKA) is a proposal consisting of a joint venture of more than ten countries, resulting in the world’s largest synthetic aperture radio telescope. In the SKA, the processing scale of the data is large, and it consists of several data processing nodes. The data will be processed in the cloud computing mode. Taking the SKA under consideration, this report proposes a data processing scheme based on blockchain for the anti-counterfeiting, anti-tampering and traceability of data. Furthermore, the authenticity and integrity of the data are assured. The primary aspects include data distribution, data operation and data sharing, which correspond to the data reception, data algorithm processing and result sharing of data operation in the SKA. With this process, the integrity, reliability and authenticity of the data are guaranteed. Additionally, smart contracts, homomorphic hashing, secure containers, aggregate signatures and one-way encrypted channels are implemented to ensure the intelligence, security and high performance of the process.

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“…researched data for business intelligence and business service computing. Data mining technology is also widely used in e-commerce, media, energy services, automotive engineering and other fields [14][15][16][17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

Artificial Immune Network Clustering Based on a Cultural Algorithm

Deng

Yang

Liu

2020

Preprint

View full text Add to dashboard Cite

There are some problems in evolutionary immune network clustering, such as the lack of guidance in the clustering process, the sensitivity of the fuzzy boundary and the difficulty in determining parameters. To solve these problems, an artificial immune network clustering algorithm based on a cultural algorithm is proposed. Three kinds of knowledge are constructed: normative knowledge is used to standardize the spatial scope of population initialization, avoiding blindness; state knowledge is used to distinguish antigens and take immune defense measures to prevent noise and unclear network structure caused by boundary; topology knowledge is used to guide the optimal antibody search. The clone mutation operation of the traditional method is improved, and a compression threshold adaptive determination method is proposed based on the shadow sets theory. The experimental results show that the proposed method can effectively overcome the above problems, and the clustering performance on a synthetic dataset and an actual dataset is satisfactory.

show abstract

Mobile-edge computing framework with data compression for wireless network in energy internet

Cited by 39 publications

References 14 publications

Artificial Immune Network Clustering Based on a Cultural Algorithm

Artificial Immune Network Clustering Based on a Cultural Algorithm

Data Processing Scheme Based on Blockchain

Artificial Immune Network Clustering Based on a Cultural Algorithm

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