Wireless Personal Communications最新文献_第8页

Employing an optimisation algorithm to design an evolutionary topological structure for non-misbehaving nodes with optimal path selection 采用优化算法为非行为不端节点设计具有最优路径选择的进化拓扑结构

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-18 DOI: 10.1007/s11277-024-11305-x

S. Kanmani, M. Murali

引用次数: 0

Enhancing the LoRaWAN Publish/Subscribe IoT Data Sharing Model Using Middleman for Smart Grid Application 利用中间人增强 LoRaWAN 发布/订阅物联网数据共享模型，用于智能电网应用

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-17 DOI: 10.1007/s11277-024-11376-w

Sapna S. Khapre, R. Ganeshan

{"title":"Enhancing the LoRaWAN Publish/Subscribe IoT Data Sharing Model Using Middleman for Smart Grid Application","authors":"Sapna S. Khapre, R. Ganeshan","doi":"10.1007/s11277-024-11376-w","DOIUrl":"https://doi.org/10.1007/s11277-024-11376-w","url":null,"abstract":"The power grid, manufacturing, and industrial automation are just a few Internet of Things (IoT) settings where publish/subscribe (p/s) systems are increasingly prevalent. These systems may handle a wide range of middleware and communication protocols, ensuring compatibility. The most well-liked publish/subscribe protocol is the Message Queue Telemetry Transport Protocol (MQTT), which uses an agent to transfer information between publishers and subscribers on certain subjects. MQTT can be quickly and simply deployed for IoT settings using a popular wireless MAC layer protocol like Long Range Wide Area Network (LoRaWAN), however, this has not been properly validated. MQTT can be readily set up in cloud environments to do research experiments. To provide an MQTT-based publication design that can handle the LoRaWAN proactive steps, the authors design and provide a simulation framework in NS-3 in this study. To do this, the authors make use of the LoRaWAN library from NS-3 and include connecting it with a middleman that links to numerous publications as well as clients. The authors support many topics at the broker while enabling unicast capabilities from the broker to LoRaWAN end devices. In other words, the proposed work activates the unicast capability from the middleman to LoRaWAN peripheral devices while handling multiple topics at the mediator. To illustrate the viability of our IoT architecture and evaluate its performance at scale, the authors performed several scenarios under it.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"20 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of Resource Distribution on Performance of Fog Computing Infrastructure 资源分配对雾计算基础设施性能的影响

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-17 DOI: 10.1007/s11277-024-11272-3

Sara Jamil, Rehan Qureshi, Sohaib Ahmed, Osama Rehman

{"title":"Impact of Resource Distribution on Performance of Fog Computing Infrastructure","authors":"Sara Jamil, Rehan Qureshi, Sohaib Ahmed, Osama Rehman","doi":"10.1007/s11277-024-11272-3","DOIUrl":"https://doi.org/10.1007/s11277-024-11272-3","url":null,"abstract":"The data being produced by the devices connected to the Internet is ever growing. The large volume of data is also required to be processed and stored. Cloud computing provides data processing and storage services by using IT resources at gegraphically distributed locations. However, the cloud computing resources are usually far away from the sites where data is produced and processing is needed, which results in communication latencies that may not be acceptable for some appliations. This issue is addressed by Fog computing by brining data processing closer to the edge of the Internet. As fog infrastructures are significantly different from cloud in terms of scale, processing capacity, bandwidth etc.; more focused analysis is needed to explore avenues for performance improvement. In this paper, we analyze effects of resource distribution in small-scale fog computing infrastructure on its performance and resource utilization. We examine different topological arrangements of fog devices with varying resources. Our results show that the topological arrangement of fog nodes has a significant impact on the overall performance of fog computing infrastructure.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"72 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deterministic Rabin Cryptosystem Using Cubic Congruence and Chinese Remainder Theorem 利用立方全等和中文余数定理的确定性拉宾密码系统

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-17 DOI: 10.1007/s11277-024-11416-5

Maroti Deshmukh, Kanchan Bisht, Arjun Singh Rawat

{"title":"Deterministic Rabin Cryptosystem Using Cubic Congruence and Chinese Remainder Theorem","authors":"Maroti Deshmukh, Kanchan Bisht, Arjun Singh Rawat","doi":"10.1007/s11277-024-11416-5","DOIUrl":"https://doi.org/10.1007/s11277-024-11416-5","url":null,"abstract":"The Rabin Cryptosystem is a public-key cryptosystem known for providing security levels comparable to RSA but with reduced computational overhead. Despite these advantages, it has not been widely adopted for practical use due to its lack of a deterministic nature. This paper addresses this limitation by introducing a new Deterministic Rabin Cryptosystem (DRCS). The DRCS framework includes processes for key generation, encryption, and decryption, leveraging the concept of cubic congruence and the Chinese Remainder Theorem to ensure the decryption process is unambiguous and deterministic. This design not only retains the computational efficiency of the original Rabin Cryptosystem but also enhances its security. Our comparative analysis shows that the DRCS achieves similar performance to the traditional Rabin system in terms of computational overhead. While the encryption process in DRCS is less demanding, its decryption process is more complex, and overall, it maintains a polynomial time complexity. Furthermore, a detailed security analysis indicates that the DRCS is significantly harder to factorize compared to previous models, underscoring its improved security features.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"10 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of Deep Learning Techniques for Neurological Disorders Detection 深度学习技术在神经系统疾病检测中的应用综述

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-14 DOI: 10.1007/s11277-024-11464-x

Akhilesh Kumar Tripathi, Rafeeq Ahmed, Arvind Kumar Tiwari

{"title":"Review of Deep Learning Techniques for Neurological Disorders Detection","authors":"Akhilesh Kumar Tripathi, Rafeeq Ahmed, Arvind Kumar Tiwari","doi":"10.1007/s11277-024-11464-x","DOIUrl":"https://doi.org/10.1007/s11277-024-11464-x","url":null,"abstract":"Neurological disease is one of the most common types of dementia that predominantly concerns the elderly. In clinical approaches, identifying its premature stages is complicated, and no biomarker is comprehended to be thorough in witnessing neurological disorders in their earlier stages. Deep learning approaches have attracted much attention in the scientific community using scanned images. They differ from simple machine learning (ML) algorithms in that they study the most favorable depiction of untreated images. Deep learning is helpful in the neuroimaging analysis of neurological diseases with subtle and dispersed changes because it can discover abstract and complicated patterns. The current study discusses a vital part of deep learning and looks at past work that has been used to switch between different ML algorithms that can predict neurological diseases. Convolution Neural Networks, Generative Adversarial Network, Recurrent Neural Network, Deep Belief Network, Auto Encoder, and other algorithms for Alzheimer’s illness prediction have been considered. Many publications on preprocessing methods, such as scaling, correction, stripping, and normalizing, have been evaluated.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"55 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy Efficient Routing in Cluster Based Heterogeneous Wireless Sensor Network Using Hybrid GWO and Firefly Algorithm 使用混合 GWO 算法和萤火虫算法在基于集群的异构无线传感器网络中实现高能效路由选择

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-14 DOI: 10.1007/s11277-024-11447-y

Jayashree Dev, Jibitesh Mishra

{"title":"Energy Efficient Routing in Cluster Based Heterogeneous Wireless Sensor Network Using Hybrid GWO and Firefly Algorithm","authors":"Jayashree Dev, Jibitesh Mishra","doi":"10.1007/s11277-024-11447-y","DOIUrl":"https://doi.org/10.1007/s11277-024-11447-y","url":null,"abstract":"Object tracking application is one of the important as well as challenging application of energy constrained Wireless Sensor Network (WSN).Timely and accurate action is required whenever the presence of object is sensed in the area of interest (AOI).This requires a lot of data collection from surrounding environment, routing of these data to base station (BS) and data processing. Large volume of data processing challenges the long survival of the WSN. In other way, expecting accurate tracking result with less data is quite impossible. Early exhaustion of node energy leads to early node death which affects the tracking quality. Therefore, it is required to maintain the accuracy in tracking result while not affecting the longevity of the network. Use of heterogeneous sensor nodes and cluster architecture of the network are two of the many factors that can enhance the lifetime of the network to some extent. Lifetime of the network can be further enhanced using optimum data routing procedure. This paper proposes a novel swarm intelligence based routing algorithm called HGWO-Firefly algorithm for routing of information to BS in a WSN with cluster architecture. Proposed algorithm consists of two broad steps. In first step, potential cluster head (CH) selection is done using hybrid K-means and Grey Wolf Optimization (GWO) algorithm. In second step, selection of energy efficient route in between BS and sensor node is done using Firefly algorithm. When the performance of the proposed algorithm is compared with existing PSO-based routing algorithm and FIGWO algorithm, it is found that the performance of the proposed algorithm is better.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"9 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EFTVG: An Energy Efficient Fuzzy–Timer Clustering Approach in an Adaptive Virtual Grid Cluster Based WSN EFTVG：基于自适应虚拟网格集群的 WSN 中的高能效模糊定时器聚类方法

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-13 DOI: 10.1007/s11277-024-11453-0

Armin Mazinani, Sayyed Majid Mazinani, Mohammed Jasim Mohammed Alyasiri

{"title":"EFTVG: An Energy Efficient Fuzzy–Timer Clustering Approach in an Adaptive Virtual Grid Cluster Based WSN","authors":"Armin Mazinani, Sayyed Majid Mazinani, Mohammed Jasim Mohammed Alyasiri","doi":"10.1007/s11277-024-11453-0","DOIUrl":"https://doi.org/10.1007/s11277-024-11453-0","url":null,"abstract":"Clustering is an effective way that improves WSN lifetime. In this paper, unlike the other approaches, an adaptive virtual grid is conducted to form cluster boundaries during a network lifetime. Using the adaptive virtual grid not only shrinks the size of clusters but also determines network configuration based on the location of the base station. In EFTVG, compared to the previous clustering methods which used a specific cluster head selection procedure for the entire network lifetime, we propose a consecutive clustering (fuzzy-timer) approach. Authors divide the network lifetime into two parts. Firstly, a fuzzy clustering is applied to address uncertainty in a semi-distributed manner. Then a timer-based clustering is used in the second part to tackle sharp energy consumption in a fully-distributed manner. A local threshold is applied in each cluster to specify whether cluster head selection is required or not. Using this novelty, the network may encounter new cluster heads in some clusters, while we trust the ex-cluster head in others. Applying this policy results in energy saving. Finally, we present a novel hybrid routing to reduce energy consumption in WSN. EFTVG is compared with MOFCA, EAFCA, EAUCF, FLECH, DECUC, FUCA, DUCF, FSCVG and FMCR-CT approaches in four different scenarios.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"33 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNNMND) Protocol For Internet of Things 基于迭代卷积神经网络的物联网恶意节点检测（ICNNMND）协议

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-11 DOI: 10.1007/s11277-024-11459-8

Moemedi Moka, Karabo Serome, Rajalakshmi Selvaraj

{"title":"An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNNMND) Protocol For Internet of Things","authors":"Moemedi Moka, Karabo Serome, Rajalakshmi Selvaraj","doi":"10.1007/s11277-024-11459-8","DOIUrl":"https://doi.org/10.1007/s11277-024-11459-8","url":null,"abstract":"At present Internet of Things is widely used in various products and parts in our daily life. In the future, its uses and requirements will increase. However, there are several issues with the IoT network, one of which is secure data transmission. Also, malicious nodes in the IoT network are very difficult to identify accurately and quickly, whereas it is very important to do so. In the current context, several solutions are being proposed as there is a need to focus on setting up secure IoT frameworks, and as well as the protocols that runs on them. This research proposes a secure protocol called iterative Convolutional Neural Network based Malicious Node Detection protocol that uses the erroneous assumption learning problematic technique. This protocol will make changes in the application layer, the network layer and the physical layer in order to achieve secure data transmission in IoT. The proposed ICNNMND protocol will be able to detect attacks and eliminate them hence providing maximum data accuracy in IoT. For this, machine learning method will be used and the changes in the characteristics of the malicious nodes will be learned and their boundaries be explored. Then its error variation will be calculated and the malicious nodes be differentiated.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"46 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Hotel Rating Prediction from Reviews Using Ensemble Learning Technique 利用集合学习技术从评论中高效预测酒店评级

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-11 DOI: 10.1007/s11277-024-11457-w

Mukesh Kumar, Chhotelal Kumar, Naween Kumar, S. Kavitha

{"title":"Efficient Hotel Rating Prediction from Reviews Using Ensemble Learning Technique","authors":"Mukesh Kumar, Chhotelal Kumar, Naween Kumar, S. Kavitha","doi":"10.1007/s11277-024-11457-w","DOIUrl":"https://doi.org/10.1007/s11277-024-11457-w","url":null,"abstract":"Predicting hotel ratings from reviews involves natural language processing techniques to extract sentiment and features from text data, then applying machine learning (ML) models like regression or classification to estimate the corresponding rating based on these features. This study proposes an ensemble learning approach for predicting hotel ratings from user reviews. By integrating multiple ML algorithms trained on various textual features, including linguistic, semantic, and sentiment-based attributes, our model achieves superior predictive accuracy. The primary aim of this study is to predict user experience ratings with high accuracy. To achieve this, this research utilizes an Ensemble learning approach known as majority voting to make these predictions effectively. In this investigation, initially, the dataset undergoes cleaning and is subsequently subjected to a series of pre-processing steps using Natural Language Processing (NLP) techniques. The research includes a comparative analysis of various classifiers along with different embedding methods. Seven different types of classifiers are used alongside three embedding techniques i.e., Term Frequency-Inverse Document Frequency (TF-IDF), Bag of Words (BoW), and Word2Vec. The classifiers include, Logistic Regression without Cross Validation (LR), LR with Cross Validation (LRCV), Decision Tree Classifier (DTC), Stochastic Gradient Descent Classifier (SGDC), Random Forest Classifier (RFC), Support Vector Classifier (SVC) and K-Nearest Neighbour (KNN). Our proposed methodology demonstrates higher accuracy and robust performance. Accuracy and frequency are utilized as performance metrics for assessing and validating both classifiers and embedding techniques. As per the simulation results, TF-IDF in combination with LRCV achieves an accuracy rate of 61%.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"4 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Analysis of Computational Intelligence Correction 计算智能校正的性能分析

IF 2.2 4区计算机科学

Wireless Personal Communications Pub Date : 2024-07-11 DOI: 10.1007/s11277-024-11399-3

Nalineekumari Arasavali, Sasibhushana Rao Gottapu

{"title":"Performance Analysis of Computational Intelligence Correction","authors":"Nalineekumari Arasavali, Sasibhushana Rao Gottapu","doi":"10.1007/s11277-024-11399-3","DOIUrl":"https://doi.org/10.1007/s11277-024-11399-3","url":null,"abstract":"Kalman filter (KF) is a widely used navigation algorithm, especially for precise positioning applications. However, the exact filter parameters must be defined a priori to use standard Kalman filters for coping with low error values. But for the dynamic system model, the covariance of process noise is a priori entirely undefined, which results in difficulties and challenges in the implementation of the conventional Kalman filter. Kalman Filter with recursive covariance estimation applied to solve those complicated functional issues, which can also be used in many other applications involving Kalaman filtering technology, a modified Kalman filter called MKF-RCE. While this is a better approach, KF with SAR tuned covariance has been proposed to resolve the problem of estimation for the dynamic model. The data collected at (x: 706,970.9093 m, y: 6,035,941.0226 m, z: 1,930,009.5821 m) used to illustrate the performance analysis of KF with recursive covariance and KF with computational intelligence correction by means of SAR (Search and Rescue) tuned covariance, when the covariance matrices of process and measurement noises are completely unknown in advance.","PeriodicalId":23827,"journal":{"name":"Wireless Personal Communications","volume":"54 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0