TS-REPLICA: A novel replica placement algorithm based on the entropy weight TOPSIS method in spark for multimedia data analysis

Liu, Jun; Xie, Mingyue; Chen, Shuyu; Xu, Guangxia; Wu, Tianshu; Li, Wei

doi:10.1016/j.ins.2023.01.049

Cited by 13 publications

(4 citation statements)

References 37 publications

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“…Entropy was first introduced into information theory by Shannon, and has been very widely used in various fields (Liu et al 2023). Entropy weight method is a method that applies information entropy theory to multi-indicator decision-making problems.…”

Section: Entropy Methodsmentioning

confidence: 99%

Research on Evaluation of Resilience and Improvement Strategy of Changchun Transportation System Based on Natural Hazard Risk Assessment

Wan,

Lang,

Zhang

et al. 2023

Preprint

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Urban transportation systems play a vital role in the development of modern cities. However, urban transportation systems face many natural disaster challenges. In this paper, the natural disaster risk assessment theory is used to evaluate the resilience of the transportation system in Changchun City, and 22 indicators are selected through the four aspects of hazard, vulnerability, exposure and disaster prevention and mitigation capacity, and the combination weights of the indicators are obtained by using the three-scalar hierarchical analysis method combined with the entropy weight method. At the same time, GIS was used to process and visualize these data, and the final toughness zoning was obtained by superposition analysis, which proved that the method has high accuracy and feasibility through example verification, and can provide scientific basis for the improvement and optimization of urban transportation system. Combined with these results, the spatial distribution characteristics of the transportation system toughness are found through the introduction of traffic flow indicators and spatial analysis, and relevant improvement measures are proposed. This paper comprehensively analyzes and evaluates the transportation system toughness in Changchun, which provides an important reference for the improvement of the transportation system.

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Section: Entropy Methodsmentioning

confidence: 99%

Research on Evaluation of Resilience and Improvement Strategy of Changchun Transportation System Based on Natural Hazard Risk Assessment

Wan,

Lang,

Zhang

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…For combining numerous trait weights, the entropy weight method is presented. Next, copy location is based on the complete load values of each Spark cluster data node, rack, and cluster [20].…”

Section: Literature Surveymentioning

confidence: 99%

A New Integrated Approach for Cloud Service Composition and Sharing Using a Hybrid Algorithm

J.,

R.,

2024

Mathematical Problems in Engineering

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The concept of a “Smart City” emphasizes the need to employ information and communication technologies to strengthen the quality, connectivity, and efficiency of various municipal services. Cloud computing and the Internet of Things are shaping future tech. Both ideas greatly impact smart city application and solution development. Cloud computing is amazing at managing and storing remote service access. Several companies have switched to cloud leasing to reduce local resource burden. Due to the intricacy and flexibility of cloud-maintained services, selecting jobs that best suit client needs should be optimized. Quality of service criteria for each cloud service are the best tools for choosing and optimizing cloud carriers. Genetic algorithms (GAs) and ant colony optimization (ACO) are combined to make cloud computing. It is discovered that the recommended ACO + GA obtains an accuracy of 82% when compared to existing methods of energy- and reliability-aware multiobjective optimization method and the hybrid cuckoo particles swarm, artificial bee colony optimization (CPS + ABCO) where accuracy is 68% and 75%, respectively.

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“…Li and Lin (2020) proposed the concept of soft likelihood function based on Picture fuzzy set and applied it to the evidential reasoning of computer network crime. Technique for order preference by similarity to ideal solution (TOPSIS) is adapted to a wide range of application scenarios of multi-attribute decision making (Liu et al, 2023). Lin et al (2019) proposed a novel TOPSIS method for linguistic PFS based on correlation coefficient and entropy measure.…”

Section: Ijicc 164mentioning

confidence: 99%

Interval multi-objective grey wolf optimization algorithm based on fuzzy system

Lin

2023

IJICC

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PurposeThe interval multi-objective optimization problems (IMOPs) are universal and vital uncertain optimization problems. In this study, an interval multi-objective grey wolf optimization algorithm (GWO) based on fuzzy system is proposed to solve IMOPs effectively.Design/methodology/approachFirst, the classical genetic operators are embedded into the interval multi-objective GWO as local search strategies, which effectively balanced the global search ability and local development ability. Second, by constructing a fuzzy system, an effective local search activation mechanism is proposed to save computing resources as much as possible while ensuring the performance of the algorithm. The fuzzy system takes hypervolume, imprecision and number of iterations as inputs and outputs the activation index, local population size and maximum number of iterations. Then, the fuzzy inference rules are defined. It uses the activation index to determine whether to activate the local search process and sets the population size and the maximum number of iterations in the process.FindingsThe experimental results show that the proposed algorithm achieves optimal hypervolume results on 9 of the 10 benchmark test problems. The imprecision achieved on 8 test problems is significantly better than other algorithms. This means that the proposed algorithm has better performance than the commonly used interval multi-objective evolutionary algorithms. Moreover, through experiments show that the local search activation mechanism based on fuzzy system proposed in this study can effectively ensure that the local search is activated reasonably in the whole algorithm process, and reasonably allocate computing resources by adaptively setting the population size and maximum number of iterations in the local search process.Originality/valueThis study proposes an Interval multi-objective GWO, which could effectively balance the global search ability and local development ability. Then an effective local search activation mechanism is developed by using fuzzy inference system. It closely combines global optimization with local search, which improves the performance of the algorithm and saves computing resources.

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TS-REPLICA: A novel replica placement algorithm based on the entropy weight TOPSIS method in spark for multimedia data analysis

Cited by 13 publications

References 37 publications

Research on Evaluation of Resilience and Improvement Strategy of Changchun Transportation System Based on Natural Hazard Risk Assessment

Research on Evaluation of Resilience and Improvement Strategy of Changchun Transportation System Based on Natural Hazard Risk Assessment

A New Integrated Approach for Cloud Service Composition and Sharing Using a Hybrid Algorithm

Interval multi-objective grey wolf optimization algorithm based on fuzzy system

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