Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257974
Randa Osama, N. Ashraf, Amina Yasser, Salma AbdelFatah, Noha ElMasry, Ashraf AbdelRaouf
Agriculture is considered the main source of economic development in the world. Agriculture is also the main supply of the world’s food and fabrics. Diseases affecting plants in the agriculture process is considered a crisis since it is a threat to the basic human food supply. Early detection of these diseases will save a large amount of the crops. Our proposed approach aims to detect plant’s diseases grown in greenhouses. This is done by monitoring a greenhouse model using an automated intelligent system. The proposed system is used to speed up the plant growth and detect the plant’s diseases. We used tomatoes to test our proposed system. The detected diseases are early blight, late blight, leaf mold, spider mites, target spot, mosaic virus, septoria, bacterial spot, and yellow leaf curl virus. These diseases usually appear on the leaves of the plants and it is hard to differentiate between them by the naked eye. A deep learning library Fast.ai, is used in building a training model from the given dataset of the diseases to get the highest accuracy. The proposed approach achieved 94.8% accuracy in detecting different types of tomato’s diseases. A Web application is developed to track greenhouse’s growth statistics and get notified if there is any disease found on their plant inside the greenhouse.
{"title":"Detecting plant’s diseases in Greenhouse using Deep Learning","authors":"Randa Osama, N. Ashraf, Amina Yasser, Salma AbdelFatah, Noha ElMasry, Ashraf AbdelRaouf","doi":"10.1109/NILES50944.2020.9257974","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257974","url":null,"abstract":"Agriculture is considered the main source of economic development in the world. Agriculture is also the main supply of the world’s food and fabrics. Diseases affecting plants in the agriculture process is considered a crisis since it is a threat to the basic human food supply. Early detection of these diseases will save a large amount of the crops. Our proposed approach aims to detect plant’s diseases grown in greenhouses. This is done by monitoring a greenhouse model using an automated intelligent system. The proposed system is used to speed up the plant growth and detect the plant’s diseases. We used tomatoes to test our proposed system. The detected diseases are early blight, late blight, leaf mold, spider mites, target spot, mosaic virus, septoria, bacterial spot, and yellow leaf curl virus. These diseases usually appear on the leaves of the plants and it is hard to differentiate between them by the naked eye. A deep learning library Fast.ai, is used in building a training model from the given dataset of the diseases to get the highest accuracy. The proposed approach achieved 94.8% accuracy in detecting different types of tomato’s diseases. A Web application is developed to track greenhouse’s growth statistics and get notified if there is any disease found on their plant inside the greenhouse.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130247070","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257937
Yomna A. Moussa, Wassim Alexan
This paper proposes an advanced scheme of message security in 3D cover images using multiple layers of security. Cryptography using AES–256 is implemented in the first layer. In the second layer, edge detection is applied. Finally, LSB steganography is executed in the third layer. The efficiency of the proposed scheme is measured using a number of performance metrics. For instance, mean square error (MSE), peak signal–to–noise ratio (PSNR), structural similarity index measure (SSIM), mean absolute error (MAE) and entropy.
{"title":"Message Security Through AES and LSB Embedding in Edge Detected Pixels of 3D Images","authors":"Yomna A. Moussa, Wassim Alexan","doi":"10.1109/NILES50944.2020.9257937","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257937","url":null,"abstract":"This paper proposes an advanced scheme of message security in 3D cover images using multiple layers of security. Cryptography using AES–256 is implemented in the first layer. In the second layer, edge detection is applied. Finally, LSB steganography is executed in the third layer. The efficiency of the proposed scheme is measured using a number of performance metrics. For instance, mean square error (MSE), peak signal–to–noise ratio (PSNR), structural similarity index measure (SSIM), mean absolute error (MAE) and entropy.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134093697","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257907
H. Amer, Dina Rateb, R. Daoud, G. Alkady
In this paper, the machine repair cycle in the manufacturing industry is explored in the context of developing countries. The scope of this paper is the failure of electronic components in the machine along with its software. A Markov model is developed to take into account the different types of failures (hardware or software) and the repair procedures while focusing on the effect of training the maintenance personnel as well as that of stocking spare parts onsite. It is shown that the Steady State Availability obtained when using the proposed enhanced model is occasionally different than that obtained when using more conventional models. The proposed model can be used to support decision making regarding the appropriate amount of training for the maintenance personnel and the factory’s spare part stocking policy. Finally, the Payoff is analyzed in relation to the cost of Downtime versus the Uptime.
{"title":"Enhanced Modeling of Machine Repair Cycle to Maximize Uptime in Developing Countries","authors":"H. Amer, Dina Rateb, R. Daoud, G. Alkady","doi":"10.1109/NILES50944.2020.9257907","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257907","url":null,"abstract":"In this paper, the machine repair cycle in the manufacturing industry is explored in the context of developing countries. The scope of this paper is the failure of electronic components in the machine along with its software. A Markov model is developed to take into account the different types of failures (hardware or software) and the repair procedures while focusing on the effect of training the maintenance personnel as well as that of stocking spare parts onsite. It is shown that the Steady State Availability obtained when using the proposed enhanced model is occasionally different than that obtained when using more conventional models. The proposed model can be used to support decision making regarding the appropriate amount of training for the maintenance personnel and the factory’s spare part stocking policy. Finally, the Payoff is analyzed in relation to the cost of Downtime versus the Uptime.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116750787","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257981
Salma Abd El Monem, A. Khalafallah, S. Shaheen
The route leaks problem is considered one of the unsolved Border Gateway Protocol problems for more than fifteen years ago. It has a large negative impact on global internet stability and reliability. This problem is hard to be prevented due to human errors and misconfigurations, and hard to be detected due to the confidentiality of autonomous systems relationships.The paper proposes a new taxonomy to the different types of route leaks depending on their effects on the Border Gateway Protocol traffic, the first real route leaks incidents dataset, and a complete real-time detection system based on a supervised learning classification method. The work compares three classifiers (Decision Tree, Random Forest Trees, and Support Vector Machines). The proposed system prototype can detect and classify route leaks from normal updates with an accuracy of 87% and time complexity of O(NM), where N is the number of prefixes each with M prefix length.
{"title":"BGP Route Leaks Detection Using Supervised Machine Learning Technique","authors":"Salma Abd El Monem, A. Khalafallah, S. Shaheen","doi":"10.1109/NILES50944.2020.9257981","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257981","url":null,"abstract":"The route leaks problem is considered one of the unsolved Border Gateway Protocol problems for more than fifteen years ago. It has a large negative impact on global internet stability and reliability. This problem is hard to be prevented due to human errors and misconfigurations, and hard to be detected due to the confidentiality of autonomous systems relationships.The paper proposes a new taxonomy to the different types of route leaks depending on their effects on the Border Gateway Protocol traffic, the first real route leaks incidents dataset, and a complete real-time detection system based on a supervised learning classification method. The work compares three classifiers (Decision Tree, Random Forest Trees, and Support Vector Machines). The proposed system prototype can detect and classify route leaks from normal updates with an accuracy of 87% and time complexity of O(NM), where N is the number of prefixes each with M prefix length.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115768042","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257978
S. Sharroush
Multi-threshold-voltage complementary metal-oxide semiconductor (MTCMOS) technology finds a wide variety of applications in reducing the subthreshold-leakage current in both combinational and sequential circuits. This is due to the fact that slightly increasing the threshold voltage causes a dramatic decrease in the subthreshold-leakage current. However, the decision on the sizing of the sleep transistor is a critical issue because there are various trade-offs that the designer must face with this respect. In this paper, the area, the static and dynamic-power consumption, and the time delay are investigated with respect to the aspect ratio of the sleep transistor with compact-form expressions derived for them. Accordingly, the optimal size of the sleep transistor is determined quantitatively. The results are discussed for NAND and NOR gates. The results obtained are based on adopting the Berkeley predictive technology model (BPTM) of the 22 nm CMOS technology with a power-supply voltage, VDD, equal to 0.8 V.
{"title":"Optimum Sizing of the Sleep Transistor in MTCMOS Technology","authors":"S. Sharroush","doi":"10.1109/NILES50944.2020.9257978","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257978","url":null,"abstract":"Multi-threshold-voltage complementary metal-oxide semiconductor (MTCMOS) technology finds a wide variety of applications in reducing the subthreshold-leakage current in both combinational and sequential circuits. This is due to the fact that slightly increasing the threshold voltage causes a dramatic decrease in the subthreshold-leakage current. However, the decision on the sizing of the sleep transistor is a critical issue because there are various trade-offs that the designer must face with this respect. In this paper, the area, the static and dynamic-power consumption, and the time delay are investigated with respect to the aspect ratio of the sleep transistor with compact-form expressions derived for them. Accordingly, the optimal size of the sleep transistor is determined quantitatively. The results are discussed for NAND and NOR gates. The results obtained are based on adopting the Berkeley predictive technology model (BPTM) of the 22 nm CMOS technology with a power-supply voltage, VDD, equal to 0.8 V.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116507279","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257914
Ayman Gaber, Mohamed Adel ElBahaay, A. M. Mohamed, M. Zaki, Ahmed Samir Abdo, Nashwa Abdelbaki
Development of 5G system as a global telecommunication infrastructure is accelerating to realize the concept of a unified network infrastructure incorporating all access technologies. The potential of Low Earth Orbit (LEO) constellation systems has emerged to support wide range of services. This could help to achieve 5G key service requirements for enhanced Mobile Broadband (eMBB), Massive Machine-Type Communications (mMTC), and Ultra-Reliable Low-Latency Communication (URLLC). The integration of satellite communications with the 5G New Radio (NR) is stimulated by technology advancement to support challenging service requirements and demand for ubiquitous connectivity with the best possible quality of service. In this paper, we surveyed the opportunities of integrating terrestrial mobile and satellite networks, key technical challenges and proposed solutions. We also introduced a mobility management scheme that reduces signaling overhead and minimizes service interruption during inter satellite handover process.
{"title":"5G and Satellite Network Convergence: Survey for Opportunities, Challenges and Enabler Technologies","authors":"Ayman Gaber, Mohamed Adel ElBahaay, A. M. Mohamed, M. Zaki, Ahmed Samir Abdo, Nashwa Abdelbaki","doi":"10.1109/NILES50944.2020.9257914","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257914","url":null,"abstract":"Development of 5G system as a global telecommunication infrastructure is accelerating to realize the concept of a unified network infrastructure incorporating all access technologies. The potential of Low Earth Orbit (LEO) constellation systems has emerged to support wide range of services. This could help to achieve 5G key service requirements for enhanced Mobile Broadband (eMBB), Massive Machine-Type Communications (mMTC), and Ultra-Reliable Low-Latency Communication (URLLC). The integration of satellite communications with the 5G New Radio (NR) is stimulated by technology advancement to support challenging service requirements and demand for ubiquitous connectivity with the best possible quality of service. In this paper, we surveyed the opportunities of integrating terrestrial mobile and satellite networks, key technical challenges and proposed solutions. We also introduced a mobility management scheme that reduces signaling overhead and minimizes service interruption during inter satellite handover process.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130289542","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257941
A. Ibrahim, Rania M. Hassan, Andrew E. Tawfiles, T. Ismail, M. Darweesh
This paper aims to help self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems in real life. Crash avoidance is a complex system that depends on many parameters. The forward-collision warning system is simplified into four main objectives: detecting cars, depth estimation, assigning cars into lanes (lane assign) and tracking technique. The presented work targets the software approach by using YOLO (You Only Look Once), which is a deep learning object detector network to detect cars with an accuracy of up to 93%. Therefore, apply a depth estimation algorithm that uses the output boundary box’s dimensions (width and height) from YOLO. These dimensions used to estimate the distance with an accuracy of 80.4%. In addition, a real-time computer vision algorithm is applied to assign cars into lanes. However, a tracking proposed algorithm is applied to evaluate the speed limit to keep the vehicle safe. Finally, the real-time system achieved for all algorithms with streaming speed 23 FPS (frame per second).
本文旨在帮助自动驾驶汽车和自动驾驶车辆系统安全地与道路环境融合，并确保这些系统在现实生活中的可靠性。防撞系统是一个复杂的系统，它依赖于许多参数。将前碰撞预警系统简化为四个主要目标:检测车辆、深度估计、车道分配(车道分配)和跟踪技术。所提出的工作通过使用YOLO (You Only Look Once)来瞄准软件方法，YOLO是一种深度学习对象检测器网络，可以以高达93%的准确率检测汽车。因此，应用深度估计算法，该算法使用来自YOLO的输出边界框的尺寸(宽度和高度)。这些尺寸用于估计距离，精度为80.4%。此外，采用实时计算机视觉算法对车辆进行车道分配。然而，为了保证车辆的安全，提出了一种跟踪算法来评估限速。最后，系统实现了所有算法的实时流速度为23 FPS(帧/秒)。
{"title":"Real-Time Collision Warning System Based on Computer Vision Using Mono Camera","authors":"A. Ibrahim, Rania M. Hassan, Andrew E. Tawfiles, T. Ismail, M. Darweesh","doi":"10.1109/NILES50944.2020.9257941","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257941","url":null,"abstract":"This paper aims to help self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems in real life. Crash avoidance is a complex system that depends on many parameters. The forward-collision warning system is simplified into four main objectives: detecting cars, depth estimation, assigning cars into lanes (lane assign) and tracking technique. The presented work targets the software approach by using YOLO (You Only Look Once), which is a deep learning object detector network to detect cars with an accuracy of up to 93%. Therefore, apply a depth estimation algorithm that uses the output boundary box’s dimensions (width and height) from YOLO. These dimensions used to estimate the distance with an accuracy of 80.4%. In addition, a real-time computer vision algorithm is applied to assign cars into lanes. However, a tracking proposed algorithm is applied to evaluate the speed limit to keep the vehicle safe. Finally, the real-time system achieved for all algorithms with streaming speed 23 FPS (frame per second).","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122639474","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257902
Ahmed M. Radwan, I. E. A. Rahman, Ahmed W. Roshdy, I. Fahim
This study presents proposed solutions for increasing the productivity of a production line in the perfumes industry in Egypt using lean manufacturing methodology. Enhancing efficiency is a major significant objective to consider in a typical manufacturing firm to improve the overall performance. Increasing productivity is achieved through applying an extensive lean program implementing appropriate lean tools to solve problems identified as wastage in materials and activities as well as bottlenecks increasing lead time. Information of current problems and gaps are gathered through visits and interviews. Problems are showed and analyzed using some lean tools and charts as bottleneck analysis, workflow sequence and fishbone diagrams. Lean methodology is selected to be applied due to its ability to achieve desired results, solve current gaps and maintain outstanding performance and continuous improvement enabling competitiveness within marketplace. Proposed lean tools and the fully lean manufacturing system are presented to increase efficiency and solve problems identified. Expected results showed decreased inventories by 20-30% as well as reduction in costs by 10-20%.
{"title":"Improving Productivity of A Production Line in Perfumes Industry in Egypt Using Lean Manufacturing Methodology","authors":"Ahmed M. Radwan, I. E. A. Rahman, Ahmed W. Roshdy, I. Fahim","doi":"10.1109/NILES50944.2020.9257902","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257902","url":null,"abstract":"This study presents proposed solutions for increasing the productivity of a production line in the perfumes industry in Egypt using lean manufacturing methodology. Enhancing efficiency is a major significant objective to consider in a typical manufacturing firm to improve the overall performance. Increasing productivity is achieved through applying an extensive lean program implementing appropriate lean tools to solve problems identified as wastage in materials and activities as well as bottlenecks increasing lead time. Information of current problems and gaps are gathered through visits and interviews. Problems are showed and analyzed using some lean tools and charts as bottleneck analysis, workflow sequence and fishbone diagrams. Lean methodology is selected to be applied due to its ability to achieve desired results, solve current gaps and maintain outstanding performance and continuous improvement enabling competitiveness within marketplace. Proposed lean tools and the fully lean manufacturing system are presented to increase efficiency and solve problems identified. Expected results showed decreased inventories by 20-30% as well as reduction in costs by 10-20%.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124980868","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257886
Samaa Khaled, Omar M. Shehata, E. I. Morgan
Intersection management is one of the big challenges in traffic control. Autonomous vehicles are becoming more realistic. A lot of research efforts has been done to develop control systems for the autonomous vehicles in order to guarantee safety and reduce the average travel time and fuel Consumption while increasing the intersection throughput. This paper applies the concept of Control barrier function on a four way intersection. Several parametric studies were conducted to validate the the Control barrier function approach. Moreover, in order to evaluate the efficiency of the proposed approach , it is compared to a baseline scenario where the conventional vehicles operate under traffic lights. It shows better performance in terms of the average travel time and the intersection throughput. The average travel time is reduced by 14.91 to 15.11%. The intersection throughput is increased by almost 173%.
{"title":"Intersection Control for Autonomous Vehicles Using Control Barrier Function Approach","authors":"Samaa Khaled, Omar M. Shehata, E. I. Morgan","doi":"10.1109/NILES50944.2020.9257886","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257886","url":null,"abstract":"Intersection management is one of the big challenges in traffic control. Autonomous vehicles are becoming more realistic. A lot of research efforts has been done to develop control systems for the autonomous vehicles in order to guarantee safety and reduce the average travel time and fuel Consumption while increasing the intersection throughput. This paper applies the concept of Control barrier function on a four way intersection. Several parametric studies were conducted to validate the the Control barrier function approach. Moreover, in order to evaluate the efficiency of the proposed approach , it is compared to a baseline scenario where the conventional vehicles operate under traffic lights. It shows better performance in terms of the average travel time and the intersection throughput. The average travel time is reduced by 14.91 to 15.11%. The intersection throughput is increased by almost 173%.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123319236","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257972
Randa Bakr, A. El-Banna, Sami A. A. El-Shaikh, A. S. Eldien
Cognitive Radio Sensor Networks (CRSNs) have become an integral portion of the new generation of smart Wireless Sensor Networks (WSNs) technology. Moreover, efficient clustering and routing could enhance the network performance by taking into account the stability and connectivity of the network that expands the network's lifetime. In this paper, we propose a scheme that aims to construct an energy-efficient clustering for CRSNs through saving the intra-communication energy between nodes into the cluster, in addition to the inter-communication energy between Cluster Head (CH) nodes to the Base Station (BS). The scheme utilizes evaluation criteria to define the CH node for each cluster by calculating a weight value for each node, and depending on the maximum weight value for nodes, the CH is picked. Moreover, to establish a route between CHs, we consider common channels between them plus the shortest distance from cluster heads to the sink. In this way, clustering and routing could enhance the network performance and extend the lifetime. To corroborate the proposed scheme, extensive simulations in MATLAB were carried out and the results of the simulation showed the superiority of the proposed technique over other algorithms in terms of the network’s lifetime.
{"title":"Energy Efficient Spectrum Aware Distributed Cluster-Based Routing in Cognitive Radio Sensor Networks","authors":"Randa Bakr, A. El-Banna, Sami A. A. El-Shaikh, A. S. Eldien","doi":"10.1109/NILES50944.2020.9257972","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257972","url":null,"abstract":"Cognitive Radio Sensor Networks (CRSNs) have become an integral portion of the new generation of smart Wireless Sensor Networks (WSNs) technology. Moreover, efficient clustering and routing could enhance the network performance by taking into account the stability and connectivity of the network that expands the network's lifetime. In this paper, we propose a scheme that aims to construct an energy-efficient clustering for CRSNs through saving the intra-communication energy between nodes into the cluster, in addition to the inter-communication energy between Cluster Head (CH) nodes to the Base Station (BS). The scheme utilizes evaluation criteria to define the CH node for each cluster by calculating a weight value for each node, and depending on the maximum weight value for nodes, the CH is picked. Moreover, to establish a route between CHs, we consider common channels between them plus the shortest distance from cluster heads to the sink. In this way, clustering and routing could enhance the network performance and extend the lifetime. To corroborate the proposed scheme, extensive simulations in MATLAB were carried out and the results of the simulation showed the superiority of the proposed technique over other algorithms in terms of the network’s lifetime.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123583117","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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