Secure data transmission is one of the most difficult challenges of Mobile Ad hoc Networks (MANET), it is a group of wireless mobile nodes that creates a temporary network without the help of a centralized system, infrastructure, or access point. Location-Aided Routing (LAR) protocols limit the ad hoc network's search for a new route to a limited "request zone." For safe message transmission in the current Location Aided Routing protocol, the Secure Location Aided Routing algorithm (SLAR) is proposed in this paper. The LAR is a geographic routing protocol that establishes the route discovery region between the source and distance before forwarding the route request packets. SLAR is an extension of LAR where the performance of LAR is compared in the presence and absence of malicious nodes, and the security of LAR is improved by putting cryptographic features in it. SLAR has significantly improved throughput, end-to-end delay, and packet delivery ratio compared to LAR.
{"title":"Two-level data packet security mechanism – secure location-aided routing (SLAR)","authors":"S. Christy, Gladence L. Mary","doi":"10.26634/jmt.9.2.19316","DOIUrl":"https://doi.org/10.26634/jmt.9.2.19316","url":null,"abstract":"Secure data transmission is one of the most difficult challenges of Mobile Ad hoc Networks (MANET), it is a group of wireless mobile nodes that creates a temporary network without the help of a centralized system, infrastructure, or access point. Location-Aided Routing (LAR) protocols limit the ad hoc network's search for a new route to a limited \"request zone.\" For safe message transmission in the current Location Aided Routing protocol, the Secure Location Aided Routing algorithm (SLAR) is proposed in this paper. The LAR is a geographic routing protocol that establishes the route discovery region between the source and distance before forwarding the route request packets. SLAR is an extension of LAR where the performance of LAR is compared in the presence and absence of malicious nodes, and the security of LAR is improved by putting cryptographic features in it. SLAR has significantly improved throughput, end-to-end delay, and packet delivery ratio compared to LAR.","PeriodicalId":443344,"journal":{"name":"i-manager's Journal on Mobile Applications and Technologies","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128354575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"EVOLUTION OF BLUETOOTH TECHNOLOGY","authors":"Reddy Satish","doi":"10.26634/jmt.8.1.18461","DOIUrl":"https://doi.org/10.26634/jmt.8.1.18461","url":null,"abstract":"","PeriodicalId":443344,"journal":{"name":"i-manager's Journal on Mobile Applications and Technologies","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134131026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"RIDE LIKE A PRO: A PROPOSAL FOR CARPOOLING MOBILE APP","authors":"E. Susmitha, Bindu M. HIMA","doi":"10.26634/jmt.8.2.16774","DOIUrl":"https://doi.org/10.26634/jmt.8.2.16774","url":null,"abstract":"","PeriodicalId":443344,"journal":{"name":"i-manager's Journal on Mobile Applications and Technologies","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125108666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to explore Machine Learning-based traffic prediction in 5G networks using the QualNet simulator and the Spatio-Temporal Long Short-Term Memory (STLSTM) model. The study evaluated the performance of the STLSTM model by comparing it with other models such as Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN). The evaluation metrics used for the simulation experiments included Packet Delivery Ratio (PDR), throughput, end-to-end delay, and jitter. The results showed that the STLSTM model outperformed the other models in terms of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R-squared, and achieved improved accuracy in predicting traffic in 5G networks. The findings of this study can help network operators to effectively manage traffic and optimize network performance.
{"title":"Exploring machine learning-based traffic prediction in 5G networks using a QualNet simulator and STLSTM","authors":"R. Rathna, D. Vinod","doi":"10.26634/jmt.9.2.19317","DOIUrl":"https://doi.org/10.26634/jmt.9.2.19317","url":null,"abstract":"This paper aims to explore Machine Learning-based traffic prediction in 5G networks using the QualNet simulator and the Spatio-Temporal Long Short-Term Memory (STLSTM) model. The study evaluated the performance of the STLSTM model by comparing it with other models such as Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN). The evaluation metrics used for the simulation experiments included Packet Delivery Ratio (PDR), throughput, end-to-end delay, and jitter. The results showed that the STLSTM model outperformed the other models in terms of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R-squared, and achieved improved accuracy in predicting traffic in 5G networks. The findings of this study can help network operators to effectively manage traffic and optimize network performance.","PeriodicalId":443344,"journal":{"name":"i-manager's Journal on Mobile Applications and Technologies","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124481040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Smart home systems have gained a lot of popularity in recent decades as it increases the comfort and quality of life. The most amazing home systems are due to mobile phones and microcontrollers. Mobile control-based apps have screen limitations but are easy to manage. An insightful look at the smart home, broken down into different applications based on the Internet of Things (IoT). This IoT framework establishes a set of sensors, actuators, a system manager, platforms, and associated control devices. This paper discusses the four-layer IoT architecture, IoT paradigms, issues, and challenges.
{"title":"Smart home systems based on the internet of things","authors":"Singh Vimlesh, Kaur Amrinder, Dheeraj Kumar Merugu, Srinivas Reddy Kaluva","doi":"10.26634/jmt.9.1.18901","DOIUrl":"https://doi.org/10.26634/jmt.9.1.18901","url":null,"abstract":"Smart home systems have gained a lot of popularity in recent decades as it increases the comfort and quality of life. The most amazing home systems are due to mobile phones and microcontrollers. Mobile control-based apps have screen limitations but are easy to manage. An insightful look at the smart home, broken down into different applications based on the Internet of Things (IoT). This IoT framework establishes a set of sensors, actuators, a system manager, platforms, and associated control devices. This paper discusses the four-layer IoT architecture, IoT paradigms, issues, and challenges.","PeriodicalId":443344,"journal":{"name":"i-manager's Journal on Mobile Applications and Technologies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116814471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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