Pub Date : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100595
Farouk Boumehrez, A. Sahour, N. Doghmane
Checking the quality of video transmitted over a wireless network is critical to improving network performance. In this paper, we evaluate the HEVC/H.265 video coding standard in terms of quantization parameters (QP), video content, and the degradation impact of transmission channels on quality. Additionally, studying Quality of Service (QoS) and Quality of Experience (QoE) will allow us to study multimedia applications in wireless ad hoc networks. This paper presents (1) the performance evaluation of QP value variation for different video contents on HEVC/H265, (2) the investigation of the impact of packet loss and jitter on the QoS of transmission sequences, and (3) the fuzzy logic model proposed to evaluate the performance of transmission sequences. The results show that using different QP values can counteract the effects of packet loss and jitter and improve the received video quality.
{"title":"Fuzzy logic inference system based quality prediction model for HD HEVC video streaming over wireless networks","authors":"Farouk Boumehrez, A. Sahour, N. Doghmane","doi":"10.1109/NTIC55069.2022.10100595","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100595","url":null,"abstract":"Checking the quality of video transmitted over a wireless network is critical to improving network performance. In this paper, we evaluate the HEVC/H.265 video coding standard in terms of quantization parameters (QP), video content, and the degradation impact of transmission channels on quality. Additionally, studying Quality of Service (QoS) and Quality of Experience (QoE) will allow us to study multimedia applications in wireless ad hoc networks. This paper presents (1) the performance evaluation of QP value variation for different video contents on HEVC/H265, (2) the investigation of the impact of packet loss and jitter on the QoS of transmission sequences, and (3) the fuzzy logic model proposed to evaluate the performance of transmission sequences. The results show that using different QP values can counteract the effects of packet loss and jitter and improve the received video quality.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131365208","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100400
Raid Boudi, Z. Aliouat, Chirihane Gherbi
A network in which the items use a variety of different technologies is known as the Internet of Things (IoT). Wireless sensors networks are the most common objects in the IoT. It has numerous low-power sensors that detect environmental conditions, perform data processing. These sensors work together to perform complex tasks via wireless communication. In this context, we have proposed TDMA CADH (TDMA Cross-layer Approach Aware Delay in Heterogeneous WSN) approach based on routing information. The goal is to ensure the constraint of energy consumption and therefore, network lifetime. The main concept is to minimize delays and optimize distribution channel. In order to validate the improvements made by our approach, we carried out a simulation using a network simulator NS3 (Network Simulator NS3), in which the performances of our proposal are evaluated and compared with the already existing approaches, namely, Rand-LO (Random Leaves Ordering), Depth-LO (Depth Leaves Ordering) and Depth-ReLO (Depth Remaining Leaves Ordering).
{"title":"TDMA-CADH Cross-Layer Approach for IoT Performance Aspects","authors":"Raid Boudi, Z. Aliouat, Chirihane Gherbi","doi":"10.1109/NTIC55069.2022.10100400","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100400","url":null,"abstract":"A network in which the items use a variety of different technologies is known as the Internet of Things (IoT). Wireless sensors networks are the most common objects in the IoT. It has numerous low-power sensors that detect environmental conditions, perform data processing. These sensors work together to perform complex tasks via wireless communication. In this context, we have proposed TDMA CADH (TDMA Cross-layer Approach Aware Delay in Heterogeneous WSN) approach based on routing information. The goal is to ensure the constraint of energy consumption and therefore, network lifetime. The main concept is to minimize delays and optimize distribution channel. In order to validate the improvements made by our approach, we carried out a simulation using a network simulator NS3 (Network Simulator NS3), in which the performances of our proposal are evaluated and compared with the already existing approaches, namely, Rand-LO (Random Leaves Ordering), Depth-LO (Depth Leaves Ordering) and Depth-ReLO (Depth Remaining Leaves Ordering).","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132780544","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}
Retinal fundus images are images of color representing the inner surface of the human eye; they provide the anatomical structure of retinal blood vessels. Early diagnosis of eye-related diseases is crucial in order to take precautionary protocols to prevent major vision loss. In this study, a Machine learning-based approach for blood vessel segmentation is pro-posed. To this end, two different supervised Machine learning algorithms were implemented to analyze their performance and efficiency on blood vessel segmentation. These two algorithms are based on U-net modeling and ResNet50. A comparative analysis between the developed models and the state-of-the-art was conducted to determine a suitable solution for accurate blood vessel segmentation.
{"title":"Comparative Analysis for Blood Vessel Segmentation based on CNN Models","authors":"Meriem Mouzai, Faiza Farhi, Zaid Bousmina, Aouache Mustapha, Ilyes Keskas","doi":"10.1109/NTIC55069.2022.10100537","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100537","url":null,"abstract":"Retinal fundus images are images of color representing the inner surface of the human eye; they provide the anatomical structure of retinal blood vessels. Early diagnosis of eye-related diseases is crucial in order to take precautionary protocols to prevent major vision loss. In this study, a Machine learning-based approach for blood vessel segmentation is pro-posed. To this end, two different supervised Machine learning algorithms were implemented to analyze their performance and efficiency on blood vessel segmentation. These two algorithms are based on U-net modeling and ResNet50. A comparative analysis between the developed models and the state-of-the-art was conducted to determine a suitable solution for accurate blood vessel segmentation.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642137","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100590
B. Boudaa, Imen Bestani, Noureddine Benadjrouda
Recommender systems provide useful item suggestions (products or services) to users as part of their decision-making processes. The effectiveness of recommender systems is now clearly confirmed in various fields of application (e.g., YouTube, Amazon, Facebook, ResearchGate). In the literature, many research works have addressed the application of recommendations in the field of health in what are called health recommender systems (HRS). HRS is an innovative alternative when it comes to providing information to help doctors in the diagnosis/treatment of diseases, as well as helping patients with recommendations on how to maintain their well-being. However, the proposed development approaches in this field are limited to traditional models that lack the accuracy and effectiveness, which are vital in healthcare. This paper presents a design model for collaborative filtering-based health recommender systems using graph neural networks (GNN) via its promising Graph Convolutional Network (GCN) architecture. In this model, the convolution layer works with a simplified and efficient GCN algorithm named LightGCN. GCN-based methods are among the new cutting-edge approaches in recommender systems, and LightGCN has proven its superiority in recommendation accuracy.
{"title":"Graph Convolutional Networks for Designing Collaborative Filtering-Based Health Recommender Systems","authors":"B. Boudaa, Imen Bestani, Noureddine Benadjrouda","doi":"10.1109/NTIC55069.2022.10100590","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100590","url":null,"abstract":"Recommender systems provide useful item suggestions (products or services) to users as part of their decision-making processes. The effectiveness of recommender systems is now clearly confirmed in various fields of application (e.g., YouTube, Amazon, Facebook, ResearchGate). In the literature, many research works have addressed the application of recommendations in the field of health in what are called health recommender systems (HRS). HRS is an innovative alternative when it comes to providing information to help doctors in the diagnosis/treatment of diseases, as well as helping patients with recommendations on how to maintain their well-being. However, the proposed development approaches in this field are limited to traditional models that lack the accuracy and effectiveness, which are vital in healthcare. This paper presents a design model for collaborative filtering-based health recommender systems using graph neural networks (GNN) via its promising Graph Convolutional Network (GCN) architecture. In this model, the convolution layer works with a simplified and efficient GCN algorithm named LightGCN. GCN-based methods are among the new cutting-edge approaches in recommender systems, and LightGCN has proven its superiority in recommendation accuracy.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"685 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988832","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100531
Messaouda Ayachi, Hassina Nacer, Hachem Slimani
At present, cloud computing has attracted a serious deal of research interest and attention in multiple domains. One of the core challenges in this environment is to achieve interoperability among heterogeneous cloud service providers (heterogeneous resources, APIs (Application Programming Interface), SLA(Service-level agreement) policy, etc.) to keep up with the increasing demand of cloud services and the growing requirements of user’s applications. For that, we provide in this paper an overview of the existing approaches and proposed solutions. In this setting, we aim to clarify: Who has posed the Cloud Computing Interoperability (CCI) problem? What does CCI mean? When and Why CCI is needed? Where does CCI problem arise? And the key question that is: How to resolve CCI problem? For this latter, we propose a taxonomy where we distinguish between the considered factors before resolving the CCI problem, and the obtained characteristics of the proposed solutions after resolving the CCI problem. Then we study existing works of CCI according to this proposed taxonomy, where we have generated three graphs allowing us to discuss CCI solution approach VS consumer-centric, CCI solution architecture VS consumer-centric, and CCI solution approach VS CCI solution type. We have concluded that: 1) the application service model is more highlighted in the literature then the management and platform levels, 2) the provider-centric solutions use generally model based approaches and are deployed as middleware or brokers, 3) the user-centric solutions are based on the adapting methodologies and deployed as brokers, 4) the hybrid solutions are based on the adapting methodologies and offer standard or broker architectures, 5) the type of CCI solution in model based approaches is mainly corresponding to framework products, 6) the final product of adapting methodologies can be a service or a library type.
{"title":"Cloud Computing Interoperability : An overview","authors":"Messaouda Ayachi, Hassina Nacer, Hachem Slimani","doi":"10.1109/NTIC55069.2022.10100531","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100531","url":null,"abstract":"At present, cloud computing has attracted a serious deal of research interest and attention in multiple domains. One of the core challenges in this environment is to achieve interoperability among heterogeneous cloud service providers (heterogeneous resources, APIs (Application Programming Interface), SLA(Service-level agreement) policy, etc.) to keep up with the increasing demand of cloud services and the growing requirements of user’s applications. For that, we provide in this paper an overview of the existing approaches and proposed solutions. In this setting, we aim to clarify: Who has posed the Cloud Computing Interoperability (CCI) problem? What does CCI mean? When and Why CCI is needed? Where does CCI problem arise? And the key question that is: How to resolve CCI problem? For this latter, we propose a taxonomy where we distinguish between the considered factors before resolving the CCI problem, and the obtained characteristics of the proposed solutions after resolving the CCI problem. Then we study existing works of CCI according to this proposed taxonomy, where we have generated three graphs allowing us to discuss CCI solution approach VS consumer-centric, CCI solution architecture VS consumer-centric, and CCI solution approach VS CCI solution type. We have concluded that: 1) the application service model is more highlighted in the literature then the management and platform levels, 2) the provider-centric solutions use generally model based approaches and are deployed as middleware or brokers, 3) the user-centric solutions are based on the adapting methodologies and deployed as brokers, 4) the hybrid solutions are based on the adapting methodologies and offer standard or broker architectures, 5) the type of CCI solution in model based approaches is mainly corresponding to framework products, 6) the final product of adapting methodologies can be a service or a library type.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127979818","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100459
Sabah Lecheheb, Soufiane Boulehouache, Said Brahimi
Monitoring, Analyzing, Planning, and Execution share knowledge and build a favorable approach in the form of a loop (MAPE-K). However, this proposed reference model is not efficient for large self-adaptations. Moreover, the failure of the analyzer component to keep up with the current expansion of data is one of the reasons that making the MAPE-K loop consumes a lot of time and resources. We suggest a hybrid learning dataflow design for the analysis phase that combines Machine and Deep Learning techniques to enhance the accuracy of the Analyzer component in less time.
{"title":"Improving Self-Adaptation by Combining MAPE-K, Machine and Deep Learning","authors":"Sabah Lecheheb, Soufiane Boulehouache, Said Brahimi","doi":"10.1109/NTIC55069.2022.10100459","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100459","url":null,"abstract":"Monitoring, Analyzing, Planning, and Execution share knowledge and build a favorable approach in the form of a loop (MAPE-K). However, this proposed reference model is not efficient for large self-adaptations. Moreover, the failure of the analyzer component to keep up with the current expansion of data is one of the reasons that making the MAPE-K loop consumes a lot of time and resources. We suggest a hybrid learning dataflow design for the analysis phase that combines Machine and Deep Learning techniques to enhance the accuracy of the Analyzer component in less time.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130999123","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100394
Nassima Bougueroua, S. Mazouzi
It is important to incorporate modern approaches in that sequence to enhance the efficiency and quality of computer attacks identification. Recent years, machine learning methods are widely applied in Intrusion Detection Systems (IDS). We propose in this study compares two machine learning methods, namely Support Vector Machine (SVM) and Reinforcement Learning (RL). An analysis of existing techniques and their comparison regarding speed and precision, in addition to other factors may aid future researchers in understanding the recent advancements in IDS field as well as in creating innovations to satisfy needs and requirements in terms of computer security. The experimental results using the intrusion detection from NSL-KDD dataset show that the proposed integration is well suited for enhancing IDS performances.
{"title":"Comparison towards of Integration of Machine Learning Methods for Intrusion Detection Systems","authors":"Nassima Bougueroua, S. Mazouzi","doi":"10.1109/NTIC55069.2022.10100394","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100394","url":null,"abstract":"It is important to incorporate modern approaches in that sequence to enhance the efficiency and quality of computer attacks identification. Recent years, machine learning methods are widely applied in Intrusion Detection Systems (IDS). We propose in this study compares two machine learning methods, namely Support Vector Machine (SVM) and Reinforcement Learning (RL). An analysis of existing techniques and their comparison regarding speed and precision, in addition to other factors may aid future researchers in understanding the recent advancements in IDS field as well as in creating innovations to satisfy needs and requirements in terms of computer security. The experimental results using the intrusion detection from NSL-KDD dataset show that the proposed integration is well suited for enhancing IDS performances.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131319459","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100355
Roumaysa Bousselidj, Soufiane Boulehouache, Said Brahimi
Self-adaptation planning is a challenging task being time and resource consuming. It can be affected by multiple sources of uncertainty as it deals with frequently changing contexts. In addition, it requires real-time information, which is unpredictable at design time, to offer high quality adaptation solution. To deal with these issues, a wide range of studies proposed techniques to optimize the adaptation planning process regarding two aspects namely: planning timeliness and the quality of the provided adaptation solution. However, these two criteria are conflicting in nature i.e. improving the performance of the planning in terms of response time deteriorates the quality of the adaptation solution and vice-versa. Therefore, the adaptation research community witnesses the emergence of multiple studies of which the ultimate goal is to obtain a tradeoff between the two aspects. In this paper, we aim to highlight the key design objectives that affect the planning design and implementation. Moreover, we present the planning optimization techniques proposed in the literature and categorize them to give an understandable view of this specific area of Self-Adaptive Systems (SASs).
{"title":"A Survey on Self-adaptation Planning Optimization Techniques","authors":"Roumaysa Bousselidj, Soufiane Boulehouache, Said Brahimi","doi":"10.1109/NTIC55069.2022.10100355","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100355","url":null,"abstract":"Self-adaptation planning is a challenging task being time and resource consuming. It can be affected by multiple sources of uncertainty as it deals with frequently changing contexts. In addition, it requires real-time information, which is unpredictable at design time, to offer high quality adaptation solution. To deal with these issues, a wide range of studies proposed techniques to optimize the adaptation planning process regarding two aspects namely: planning timeliness and the quality of the provided adaptation solution. However, these two criteria are conflicting in nature i.e. improving the performance of the planning in terms of response time deteriorates the quality of the adaptation solution and vice-versa. Therefore, the adaptation research community witnesses the emergence of multiple studies of which the ultimate goal is to obtain a tradeoff between the two aspects. In this paper, we aim to highlight the key design objectives that affect the planning design and implementation. Moreover, we present the planning optimization techniques proposed in the literature and categorize them to give an understandable view of this specific area of Self-Adaptive Systems (SASs).","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124677744","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100479
A. Amrouche, Nabil Hezil, Youssouf Bentrcia, Ahcène Abed
Object Detection (OD) techniques have emerged as the key to dealing with the most complex computer vision problems in recent years. Vehicle License Plate Detection (VLPD) is the most important stage of any vehicle license plate recognition system (VLPR) because changes in its size, orientation, color, and background, contrast, and resolution have a direct impact on the system’s robustness and accuracy. The purpose of this paper is to present an object detector for detecting vehicle license plates in real-world scenes. We developed a new dataset of vehicle license plate numbers and used it to train our custom model. In YOLO-v3 layers, we decreased the number of classes to one in order to improve the detector. When we evaluated the system, we achieved precision, recall, and overall accuracy metrics of 0.95, 0.96, and 92.83 percent, respectively.
{"title":"Real-Time Detection of Vehicle License Plates Numbers","authors":"A. Amrouche, Nabil Hezil, Youssouf Bentrcia, Ahcène Abed","doi":"10.1109/NTIC55069.2022.10100479","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100479","url":null,"abstract":"Object Detection (OD) techniques have emerged as the key to dealing with the most complex computer vision problems in recent years. Vehicle License Plate Detection (VLPD) is the most important stage of any vehicle license plate recognition system (VLPR) because changes in its size, orientation, color, and background, contrast, and resolution have a direct impact on the system’s robustness and accuracy. The purpose of this paper is to present an object detector for detecting vehicle license plates in real-world scenes. We developed a new dataset of vehicle license plate numbers and used it to train our custom model. In YOLO-v3 layers, we decreased the number of classes to one in order to improve the detector. When we evaluated the system, we achieved precision, recall, and overall accuracy metrics of 0.95, 0.96, and 92.83 percent, respectively.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126895853","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 : 2022-12-21DOI: 10.1109/NTIC55069.2022.10100549
Amel Dembri, M. Redjimi
In this paper, we propose a model driven approach to facilitate the integration of Nets within Nets (NWN) modeling language in CINCO modeling tool. Despite that, NWN has a sophisticated modeling-simulation tool called Renew, moving NWN models from a platform to another has been a challenge for programmers. The development of our tool is heavily benefits from being implemented with CINCO; a full generation of the application code is provided, a powerful tool is developed with a few efforts and facilities are provided to add semantic to the platform. Combine formal method with a sophisticated model driven tool simplifies the prototypical of domain specific systems, promotes the interoperability capabilities between different technologies and assists designer in the validation of the correctness of the modeled system.
{"title":"Towards a model driven approach for integrating NWN models in CINCO","authors":"Amel Dembri, M. Redjimi","doi":"10.1109/NTIC55069.2022.10100549","DOIUrl":"https://doi.org/10.1109/NTIC55069.2022.10100549","url":null,"abstract":"In this paper, we propose a model driven approach to facilitate the integration of Nets within Nets (NWN) modeling language in CINCO modeling tool. Despite that, NWN has a sophisticated modeling-simulation tool called Renew, moving NWN models from a platform to another has been a challenge for programmers. The development of our tool is heavily benefits from being implemented with CINCO; a full generation of the application code is provided, a powerful tool is developed with a few efforts and facilities are provided to add semantic to the platform. Combine formal method with a sophisticated model driven tool simplifies the prototypical of domain specific systems, promotes the interoperability capabilities between different technologies and assists designer in the validation of the correctness of the modeled system.","PeriodicalId":403927,"journal":{"name":"2022 2nd International Conference on New Technologies of Information and Communication (NTIC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128795655","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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