Graph-based or multidimensional blockchains have been proposed to improve the scalability and efficiency of existing blockchain applications. However, when implemented in mobile Internet of Things (mIoT) networks, the...
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The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will...
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ISBN:
(纸本)9781665439299
The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-RDG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.
In this paper, a graph signal denoising method based on heat kernel smoothing (HKS) and its distributed implementation structures are investigated. First, the graph signal denoising problem and HKS method are briefly ...
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ISBN:
(数字)9781665402798
ISBN:
(纸本)9781665402798
In this paper, a graph signal denoising method based on heat kernel smoothing (HKS) and its distributed implementation structures are investigated. First, the graph signal denoising problem and HKS method are briefly described. Because HKS method needs to perform eigen-decomposition of graph Laplacian matrix for computing matrix exponential, it is only suitable for centralized implementation. To obtain a distributed or decentralized implementation of HKS method, three implementation methods are then presented in this study including product expansion method, Taylor series expansion method and numerical differentiation approximation method. Finally, irregular data collected from sensor network and social network are used to demonstrate the effectiveness of the graph signal denoising methods based on heat kernel smoothing.
The proceedings contain 34 papers. The topics discussed include: select-them-repair-them: automatically optimize pseudocode-to-code data;distributed or centralized: an experimental study on spatial database systems fo...
ISBN:
(纸本)9798350310764
The proceedings contain 34 papers. The topics discussed include: select-them-repair-them: automatically optimize pseudocode-to-code data;distributed or centralized: an experimental study on spatial database systems for processing big trajectory data;engineering large wearable sensor data towards digital measures;multi-task federated learning medical analysis algorithm integrated into adapter;style semantic disentangle network for multi-source domain generalization;how does big data in tax administration limited corporate earnings management;generalized Weierstrass-Mandelbrot with disturbance for big data applications in economic and financial systems;research on basic clinical treatment pattern mining based on electronic medical record big data;and a survey on application of blockchain technology in drug supply chain management.
The acquisition of position and attitude data in the flight state of birds is important for the study of group interaction based on the analysis of bird flight position data. In this paper, we introduce a distributed ...
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Pressure sensors are widely employed in a variety of industries, including the automotive, medical, pneumatic, and military professions. The piezoresistive type of pressure sensor is the most used transduction mechani...
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Microservices break down monolithic applications into smaller components and have become a popular model for application deployment. In this model, load balancing has moved from the server to the request side where a ...
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ISBN:
(数字)9781665451420
ISBN:
(纸本)9781665451420
Microservices break down monolithic applications into smaller components and have become a popular model for application deployment. In this model, load balancing has moved from the server to the request side where a load balancer resides with each upstream service. Least Connection, a derivative of the Join the Shortest Queue (JSQ), is a popular algorithm used in the microservice architecture. Despite JSQ being proven to be nearly optimal in certain scenarios, Least Connection significantly underperforms in microservices and edge environments. My thesis aims to adapt load balancing to the microservices environment such that they can autonomously choose from a collection of approaches to mitigate widening of response time distributions.
We have devoted efforts to the development and deployment of a new low-cost ionospheric sensor over mid-latitudes (Rodrigues and Moraes, 2019;Gomez Socola and Rodrigues, 2022). The latest version of this sensor is cal...
In this paper, a data-driven approach is presented to calibrate and compensate for degradation effects in conductive textile sensors on microcontrollers. An experimental setup was constructed to control the elongation...
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Aiming at the decoupling problem of the calibration of the six-axis force sensor, the coupling relationship is established according to the calibration experiment results of the six- axis force sensor. The basic princ...
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