Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.10059176
Faisal Alanazi
{"title":"Throughput optimization with Wind Energy harvesting","authors":"Faisal Alanazi","doi":"10.1504/ijahuc.2023.10059176","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.10059176","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135496958","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.130467
Kaouther Mansour
Frame aggregation technique opts for optimising channel usage efficiency for 802.11-based networks by amortising the transmission overhead over several aggregated packets. Despite its potential benefit, the gain achieved by this technique is still far from the expected levels. The underlying causes are attributed to certain deficiencies in the specification as well as the implementation of the conventional frame aggregation scheme. Throughout this paper, we focus on MAC protocol data unit aggregation (A-MPDU) technique. We provide a simple, yet, highly accurate mathematical model for the conventional A-MPDU technique that reflects the effect of the block acknowledgement (Block Ack) window limit on the maximum aggregation size. The effectiveness of our model is validated by ns-3 simulator. An analytical-based study is further conducted to compare the performance of the greedy A-MPDU aggregation scheme and that of the conservative scheme supported by most of wireless fidelity (Wi-Fi) card drivers.
{"title":"A two dimensional Markov chain model for aggregation-enabled 802.11 networks","authors":"Kaouther Mansour","doi":"10.1504/ijahuc.2023.130467","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.130467","url":null,"abstract":"Frame aggregation technique opts for optimising channel usage efficiency for 802.11-based networks by amortising the transmission overhead over several aggregated packets. Despite its potential benefit, the gain achieved by this technique is still far from the expected levels. The underlying causes are attributed to certain deficiencies in the specification as well as the implementation of the conventional frame aggregation scheme. Throughout this paper, we focus on MAC protocol data unit aggregation (A-MPDU) technique. We provide a simple, yet, highly accurate mathematical model for the conventional A-MPDU technique that reflects the effect of the block acknowledgement (Block Ack) window limit on the maximum aggregation size. The effectiveness of our model is validated by ns-3 simulator. An analytical-based study is further conducted to compare the performance of the greedy A-MPDU aggregation scheme and that of the conservative scheme supported by most of wireless fidelity (Wi-Fi) card drivers.","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135637432","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.10052678
Xiaodong Liu, Jixiang Gan, Lei Zeng, Qi Liu
{"title":"A survey of intelligent load monitoring in IoT-enabled distributed smart grids","authors":"Xiaodong Liu, Jixiang Gan, Lei Zeng, Qi Liu","doi":"10.1504/ijahuc.2023.10052678","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.10052678","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"47 1","pages":"12-29"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89201399","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2022.10046481
Malvika Singh, S. Sangeetha, B. Mehtre
{"title":"Insider threat detection and prevention using semantic score and dynamic multi-fuzzy classifier","authors":"Malvika Singh, S. Sangeetha, B. Mehtre","doi":"10.1504/ijahuc.2022.10046481","DOIUrl":"https://doi.org/10.1504/ijahuc.2022.10046481","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"18 1","pages":"95-112"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74390236","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2022.10052920
Manel Kolli
{"title":"A bigraphical approach to model and verify ontology alignment","authors":"Manel Kolli","doi":"10.1504/ijahuc.2022.10052920","DOIUrl":"https://doi.org/10.1504/ijahuc.2022.10052920","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"49 1","pages":"127-143"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81780843","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2022.10050801
N. Patel, B. Mehtre, R. Wankar
{"title":"Intrusion detection system using resampled dataset - a comparative study","authors":"N. Patel, B. Mehtre, R. Wankar","doi":"10.1504/ijahuc.2022.10050801","DOIUrl":"https://doi.org/10.1504/ijahuc.2022.10050801","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"267 1","pages":"243-257"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76386426","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.10053539
V. K. Kaliappan, Rajasekaran Thangaraj, P. Pandiyan, K. M. Sundaram, S. Anandamurugan, Dugki Min
The COVID-19 pandemic has infected tens of millions of individuals around the world, and it is currently posing a worldwide health calamity. Wearing a face mask in public places is one of the most effective protection strategies, according to the World Health Organization (WHO). Moreover, their effectiveness has declined due to incorrect use of the face mask. In this scenario, effective recognition systems are anticipated to ensure that people's faces are covered with masks in public locations. Many people do not correctly wear the masks due to inadequate practices, undesirable behaviour, or individual vulnerabilities. As a result, there has been an increase in demand for automatic real-time face mask detection and mask position detection to substitute manual reminders. This proposed work classifies people into three categories such as with mask, without mask and mask with incorrect position. The dataset is tested using three different variants of object detection models, namely YOLOv4, Tiny YOLOv4, and YOLOv5. The experimental result shows that YOLOv5 model outperforms with the highest mAP value of 99.40% compared to the other two models.
{"title":"Real-time face mask position recognition system using YOLO models for preventing COVID-19 disease spread in public places","authors":"V. K. Kaliappan, Rajasekaran Thangaraj, P. Pandiyan, K. M. Sundaram, S. Anandamurugan, Dugki Min","doi":"10.1504/ijahuc.2023.10053539","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.10053539","url":null,"abstract":"The COVID-19 pandemic has infected tens of millions of individuals around the world, and it is currently posing a worldwide health calamity. Wearing a face mask in public places is one of the most effective protection strategies, according to the World Health Organization (WHO). Moreover, their effectiveness has declined due to incorrect use of the face mask. In this scenario, effective recognition systems are anticipated to ensure that people's faces are covered with masks in public locations. Many people do not correctly wear the masks due to inadequate practices, undesirable behaviour, or individual vulnerabilities. As a result, there has been an increase in demand for automatic real-time face mask detection and mask position detection to substitute manual reminders. This proposed work classifies people into three categories such as with mask, without mask and mask with incorrect position. The dataset is tested using three different variants of object detection models, namely YOLOv4, Tiny YOLOv4, and YOLOv5. The experimental result shows that YOLOv5 model outperforms with the highest mAP value of 99.40% compared to the other two models.","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"19 1","pages":"73-82"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83878067","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.127766
Ramraj Dangi, Praveen Lalwani, Manas Kumar Mishra
In fifth generation (5G), traffic forecasting is one of the target areas for research to offer better service to the users. In order to enhance the services, researchers have provided deep learning models to predict the normal traffic, but these suggested models are failing to predict the traffic load during the festivals time due to sudden changes in traffic conditions. In order to address this issue, a hybrid model is proposed which is the combination of autoregressive integrated moving average (ARIMA), convolutional neural network (CNN) and long short-term memory (LSTM), called as ARIMA-CNN-LSTM, where we forecast the cumulative network traffic over specific intervals to scale up and correctly predict the availability of 5G network resources. In the comparative analysis, the ARIMA-CNN-LSTM is evaluated with well-known existing models, namely, ARIMA, CNN and LSTM. It is observed that the proposed model outperforms the other tested deep learning models in predicting the output in both usual and unusual traffic conditions.
{"title":"5G network traffic control: a temporal analysis and forecasting of cumulative network activity using machine learning and deep learning technologies","authors":"Ramraj Dangi, Praveen Lalwani, Manas Kumar Mishra","doi":"10.1504/ijahuc.2023.127766","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.127766","url":null,"abstract":"In fifth generation (5G), traffic forecasting is one of the target areas for research to offer better service to the users. In order to enhance the services, researchers have provided deep learning models to predict the normal traffic, but these suggested models are failing to predict the traffic load during the festivals time due to sudden changes in traffic conditions. In order to address this issue, a hybrid model is proposed which is the combination of autoregressive integrated moving average (ARIMA), convolutional neural network (CNN) and long short-term memory (LSTM), called as ARIMA-CNN-LSTM, where we forecast the cumulative network traffic over specific intervals to scale up and correctly predict the availability of 5G network resources. In the comparative analysis, the ARIMA-CNN-LSTM is evaluated with well-known existing models, namely, ARIMA, CNN and LSTM. It is observed that the proposed model outperforms the other tested deep learning models in predicting the output in both usual and unusual traffic conditions.","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136008722","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.10053812
Mahfuzulhoq Chowdhury
{"title":"Transcend: an ownership-based resource allocation strategy for service function chaining in NFV empowered 6G network using latency and user cost-awareness","authors":"Mahfuzulhoq Chowdhury","doi":"10.1504/ijahuc.2023.10053812","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.10053812","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"105 1","pages":"206-223"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72971274","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}
Pub Date : 2023-01-01DOI: 10.1504/ijahuc.2023.10053535
Naveen Kumar, Anwar Ahmad
{"title":"Knowledge-based flexible resource allocation optimisation strategy for multi-tenant radio access network slicing in 5G and B5G","authors":"Naveen Kumar, Anwar Ahmad","doi":"10.1504/ijahuc.2023.10053535","DOIUrl":"https://doi.org/10.1504/ijahuc.2023.10053535","url":null,"abstract":"","PeriodicalId":50346,"journal":{"name":"International Journal of Ad Hoc and Ubiquitous Computing","volume":"2 1","pages":"124-135"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80673808","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}
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