Building an Improved Internet of Things Smart Sensor Network Based on a Three-Phase Methodology

Wang, Jinhai; Yeh, Wei-Chang; Xiong, Naixue; Wang, Jing; He, Xiangjian; Huang, Chia‐Ling

doi:10.1109/access.2019.2925044

Cited by 17 publications

(11 citation statements)

References 35 publications

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“…However, the two-subset reliability is not sufficient to measure the network performance and the roles of components in making a correct decision. For example, a decision-maker is always needed to find which of the four locations is the most reliable for building a supply chain in the transportation system [13]; which five bases have the best reliable connection after considering network resiliency in telecom systems [10,11]; which three nodes have less reliable communication in the wireless sensor network [8,9,10,16], which six grids need to enhance their connection to have a better reliable smart grid [5,20]; and which five points have the weakest signal transmission in the Internet of Things systems [15,38].…”

Section: Introductionmentioning

confidence: 99%

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Yeh

2021

Reliability Engineering & System Safety

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Various real-life applications, for example, Internet of Things, wireless sensor networks, smart grids, transportation networks, communication networks, social networks, and computer grid systems, are always modeled as network structures. The binary-state network composed of binarystate (e.g., functioning or failed) components (arcs and/or nodes) is one of the most popular network structures. The two-terminal network reliability is a success probability that the network is still functioning and can be calculated by verifying the connectivity between two specific nodes, and is an effective and popular technique for evaluating the performance of all types of networks. To obtain complete information for a making better decisions, a multi-terminal network reliability extends the two specific nodes to a specific node subset in which all nodes are connected. In this study, a new algorithm called the all-multiterminal BAT is proposed by revising the binary-addition-tree algorithm (BAT) and the layered-search algorithm (LSA) to calculate all multi-terminal reliabilities. The efficiency and effectiveness of the proposed all-multiterminal BAT are analyzed from the perspective of time complexity and explained via numerical experiments to solve the all-multiterminal network reliability problems.

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Section: Introductionmentioning

confidence: 99%

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Yeh

2021

Reliability Engineering & System Safety

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“…Consequently, it is more helpful to approximate network reliability in managing and evaluating network reliability [1]- [15], [17], [19], [20], [35], [43]- [48]. This study thus only focuses on determining exact network reliability.…”

Section: There Are Different Methods Used For Calculating Networkmentioning

confidence: 99%

“…Network reliability has been a research topic of interest since the early days of reliability engineering, and it has been a popular tool to evaluate and validate the performance of many real-world modern systems [1]- [40] such as grid and cloud computing [9], computer and communication systems [10], sensor networks [11], [12], traffic service networks [13], [14], the Internet of Things [15], [16], system design [17]- [19], and production systems [20].…”

Section: Introductionmentioning

confidence: 99%

A New Node-Based Concept for Solving the Minimal Path Problem in General Networks

et al. 2019

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The validation and evaluation of network reliability are significant issues in the planning, design, and control of systems. The minimal path (MP, an edge set) set is one of the main tools used in measuring network reliability. A new node-based concept to find all MPs is proposed by simply searching all of the ordered node subsets with a time complexity O(ne n), where n is the number of nodes. The proposed concept is implemented in a newly proposed node-based MP algorithm using depth-first search (DFS). Because O(m) = O(n 2), where m is the number of edges, the proposed node-based MP algorithm is theoretically more efficient than conventional edge-based algorithms, which all use time complexity O(n2 m) to search for all MPs. Finally, a series of numerical experiments is implemented to test the performance of the proposed algorithm. INDEX TERMS General networks, reliability, minimal path (MP), node-based concept.

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“…The key to modeling with SVM is to choose the kernel function. Radial basis function (RBF) is the most widely used kernel function [37]. RBF kernel functions are applicable regardless of the number of samples or the dimensions.…”

Section: A Support Vector Machinementioning

confidence: 99%

Energy Management Optimization of Open-Pit Mine Solar Photothermal-Photoelectric Membrane Distillation Using a Support Vector Machine and a Non-Dominated Genetic Algorithm

Zhang

Jiang

et al. 2020

IEEE Access

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As a distributed energy source, open-pit mine solar photothermal-photoelectric membrane distillation can convert solar energy into heat and electrical energy to provide power for membrane distillation water purification system. In mine sewage treatment, the solar membrane distillation system has the advantages of high desalination rate, good water quality and low cost. However, this system has not been widely promoted and applied because of its high energy consumption and low membrane flux. Different operating parameters have a greater impact on the operating efficiency of the solar membrane distillation system. In this study, a natural cooling film distillation system was built, and the response surface method was used to analyze it, and a multi-objective optimization algorithm was used to optimize the operating conditions and improve the energy efficiency of the system. In our experiment, the hot end feed temperature, hot end feed flow rate, cold end cooling water flow rate, and membrane area were used as variables, and the membrane flux, thermal efficiency, and energy consumption values were investigated as target values. We used a support vector machine (SVM) with improved fitting, and substituted the fitting prediction model into the response surface method for the relationship between the variable and the target value collaborative analysis was followed by substituting the model into a non-dominated sorting genetic algorithm-II (NSGA-II). After the optimization operation, the optimal working conditions were obtained to improve the operating efficiency of the solar membrane distillation system, which will enable open-pit mine prosumers to realize intelligent management of solar energy generation, storage and consumption simultaneously.

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Building an Improved Internet of Things Smart Sensor Network Based on a Three-Phase Methodology

Cited by 17 publications

References 35 publications

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

A New Node-Based Concept for Solving the Minimal Path Problem in General Networks

Energy Management Optimization of Open-Pit Mine Solar Photothermal-Photoelectric Membrane Distillation Using a Support Vector Machine and a Non-Dominated Genetic Algorithm

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