2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)最新文献
Pub Date : 2019-10-01DOI: 10.1109/iucc/dsci/smartcns.2019.00017
{"title":"Message from the TCG 2019 Workshop Chairs","authors":"","doi":"10.1109/iucc/dsci/smartcns.2019.00017","DOIUrl":"https://doi.org/10.1109/iucc/dsci/smartcns.2019.00017","url":null,"abstract":"","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123457461","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00065
Jingdong Liu, Won-Ho Choi, Fei Hao
With the continuous development of China's social economy, people's living standards continue to improve, the people's investment in leisure and entertainment continues to increase, among which film has become one of the people's first choice for leisure and entertainment. In recent years, the domestic film market has been expanding, at the same time, western films represented by Hollywood have also produced a fierce impact on domestic films. How to improve the local film quality, improve the local film box office level has become a hot issue. In this paper, 152 domestic films in 2018 are selected as research objects, and Ordinary Least Square and TQAR models are adopted to analyze the factors affecting the box office of films, so as to provide effective references for effectively reducing the cost of film investment and improving the market value of domestic films.
{"title":"Research on the Influencing Factors of Film Box Office Based on Ordinary Least Square and Threshold Quantile Autoregressive Model","authors":"Jingdong Liu, Won-Ho Choi, Fei Hao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00065","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00065","url":null,"abstract":"With the continuous development of China's social economy, people's living standards continue to improve, the people's investment in leisure and entertainment continues to increase, among which film has become one of the people's first choice for leisure and entertainment. In recent years, the domestic film market has been expanding, at the same time, western films represented by Hollywood have also produced a fierce impact on domestic films. How to improve the local film quality, improve the local film box office level has become a hot issue. In this paper, 152 domestic films in 2018 are selected as research objects, and Ordinary Least Square and TQAR models are adopted to analyze the factors affecting the box office of films, so as to provide effective references for effectively reducing the cost of film investment and improving the market value of domestic films.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124344251","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00143
Chengye Lu, Jinzhou Li, Miao Wang, Jinfeng Hu
This paper presents an improved MaximumLikelihood (ML) estimation method for maneuvering target parameters of over-the-horizon radar (OTHR). To avoid the matrix inversion involved in traditional ML function, the ML problem is reduced to "over-determined" non-linear least squares problem. Genetic algorithm is used to estimate maneuvering target parameters with high accuracy under low signal-to-noise ratio (SNR). In addition, the Cramer-Rao Bound (CRB) for parameter estimation in OTHR is derived. Compared with the existing methods, the proposed algorithm has the following advantages: (1) higher estimation accuracy; (2) lower input SNR; (3) simultaneous estimation of parameters of multiple maneuvering targets. The simulation results show the superiority of the algorithm.
{"title":"Parameter Estimation for Maneuvering Target in OTHR Relying on Improved Maximum-Likelihood Algorithm","authors":"Chengye Lu, Jinzhou Li, Miao Wang, Jinfeng Hu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00143","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00143","url":null,"abstract":"This paper presents an improved MaximumLikelihood (ML) estimation method for maneuvering target parameters of over-the-horizon radar (OTHR). To avoid the matrix inversion involved in traditional ML function, the ML problem is reduced to \"over-determined\" non-linear least squares problem. Genetic algorithm is used to estimate maneuvering target parameters with high accuracy under low signal-to-noise ratio (SNR). In addition, the Cramer-Rao Bound (CRB) for parameter estimation in OTHR is derived. Compared with the existing methods, the proposed algorithm has the following advantages: (1) higher estimation accuracy; (2) lower input SNR; (3) simultaneous estimation of parameters of multiple maneuvering targets. The simulation results show the superiority of the algorithm.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128257407","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00059
Teng Wang, Lin Ye
Aiming at the problem that the pixel matching cost is difficult to accurately calculate in complex images, a matching cost calculation model based on multi-scale convolutional neural network is proposed in this paper. The proposed calculation model optimizes the existing model based on feature fusion idea. This model improves the feature extraction ability by extracting and fusing different scale feature information. The experiment results show that the pixel matching accuracy of the matching cost calculation model based on multi-scale convolutional neural network is 8% higher than the existing matching cost calculation model.
{"title":"Matching Cost Calculation Model Based on Multi-Scale Convolutional Neural Network","authors":"Teng Wang, Lin Ye","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00059","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00059","url":null,"abstract":"Aiming at the problem that the pixel matching cost is difficult to accurately calculate in complex images, a matching cost calculation model based on multi-scale convolutional neural network is proposed in this paper. The proposed calculation model optimizes the existing model based on feature fusion idea. This model improves the feature extraction ability by extracting and fusing different scale feature information. The experiment results show that the pixel matching accuracy of the matching cost calculation model based on multi-scale convolutional neural network is 8% higher than the existing matching cost calculation model.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128391872","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00098
Zhihui Wang, Jianrui Chen, Bo Wang
Collaborative filtering recommendation algorithm is one of the most widely used personalized recommendation algorithms in e-commerce websites. The traditional collaborative filtering recommendation algorithm has a high recommendation complexity and low accuracy with the increasing number of users and items in recent years. The previous differential clustering evolution process only recommended a single clustering results of users or items. Besides, the node state of network was only a scalar, which ignored the integration of user layer and item layer and could not better represent the attribute characteristics of users and items. This paper proposes an effective collaborative filtering recommendation algorithm for the above three problems. We fully explore the changes of interests of users and their attention to the items over time. Firstly, a time-weighted scoring matrix is constructed by combining the forgetting function. According to the new scoring matrix, the user-item attention matrix is obtained. Then, according to the differential equations, users and items with high relevance are gathered to obtain the user communities and item communities. Stabilizing the same user status values mean that they have similar interests and then they are assigned to the same community. Finally, the real time prediction results are obtained through improved prediction method and dynamic similarity measurement in each community. The effectiveness of the proposed algorithm is verified by comparison with several better algorithms.
{"title":"Dynamic Clustering Recommendation Algorithm For Two-Layer Graph Attention Network","authors":"Zhihui Wang, Jianrui Chen, Bo Wang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00098","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00098","url":null,"abstract":"Collaborative filtering recommendation algorithm is one of the most widely used personalized recommendation algorithms in e-commerce websites. The traditional collaborative filtering recommendation algorithm has a high recommendation complexity and low accuracy with the increasing number of users and items in recent years. The previous differential clustering evolution process only recommended a single clustering results of users or items. Besides, the node state of network was only a scalar, which ignored the integration of user layer and item layer and could not better represent the attribute characteristics of users and items. This paper proposes an effective collaborative filtering recommendation algorithm for the above three problems. We fully explore the changes of interests of users and their attention to the items over time. Firstly, a time-weighted scoring matrix is constructed by combining the forgetting function. According to the new scoring matrix, the user-item attention matrix is obtained. Then, according to the differential equations, users and items with high relevance are gathered to obtain the user communities and item communities. Stabilizing the same user status values mean that they have similar interests and then they are assigned to the same community. Finally, the real time prediction results are obtained through improved prediction method and dynamic similarity measurement in each community. The effectiveness of the proposed algorithm is verified by comparison with several better algorithms.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129502277","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00096
Hongjian Li, Luoying Hao, Qieshi Zhang, Xiping Hu, Jun Cheng
In this paper, we proposed a practical and efficient algorithm based on conventional semi-direct monocular visual odometry (SVO) algorithm, which mainly aims at the future application of the Simultaneous Localization and Mapping (SLAM) for embedded or mobile platforms such as robots and wearable devices. By applying the velocity momentum during the initial pose estimation, we present a novel algorithm for obtaining the initial pose, which is closer to the true value and more effective to solving the limitation of non-convergence in most existing approaches. A sparse image alignment module is also proposed to rectify the pose offset occurred at the corner, by elaborately resetting the relative pose at the location with large photometric error. The proposed lifted semi-direct monocular visual odometry has been extensively evaluated on benchmark dataset. The experimental result demonstrates that our method can explicitly generate the accurate initial poses without reducing the speed.
{"title":"A Lifted Semi-Direct Monocular Visual Odometry","authors":"Hongjian Li, Luoying Hao, Qieshi Zhang, Xiping Hu, Jun Cheng","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00096","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00096","url":null,"abstract":"In this paper, we proposed a practical and efficient algorithm based on conventional semi-direct monocular visual odometry (SVO) algorithm, which mainly aims at the future application of the Simultaneous Localization and Mapping (SLAM) for embedded or mobile platforms such as robots and wearable devices. By applying the velocity momentum during the initial pose estimation, we present a novel algorithm for obtaining the initial pose, which is closer to the true value and more effective to solving the limitation of non-convergence in most existing approaches. A sparse image alignment module is also proposed to rectify the pose offset occurred at the corner, by elaborately resetting the relative pose at the location with large photometric error. The proposed lifted semi-direct monocular visual odometry has been extensively evaluated on benchmark dataset. The experimental result demonstrates that our method can explicitly generate the accurate initial poses without reducing the speed.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782705","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}
Human multi-target tracking in video is an important issue in the field of computer vision. It is necessary to detect the target on each frame, and to connect the targets of all frames into a target sequence. For target matching among different frames, we propose a tracking algorithm for constructing object pose sequence(COPS) based on Openpose. The position status and the ORB feature of the target pose are dynamically weighted and fused into new features. Target pose is searched in the corresponding target pose sequence by comparing the new features between the target pose in the sequence and every pose in current frame. When the target pose is matched, the influence of the position feature on the pose similarity could be enhanced when the target motion is continuously detected. When the target scale changes too much, the method can expand the contribution of the ORB feature to the pose similarity comparison. The experiments of human multitarget tracking algorithm are carried out on the PoseTrack and MOT datasets, and the results show that the proposed tracking algorithm overcomes the problem of target matching between frames.
{"title":"Pose-Based Multi-Target Tracking","authors":"Xiangbin Shi, Xiaoyu Yang, Deyuan Zhang, Jing Bi, Zhaokui Li, Fang Liu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00087","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00087","url":null,"abstract":"Human multi-target tracking in video is an important issue in the field of computer vision. It is necessary to detect the target on each frame, and to connect the targets of all frames into a target sequence. For target matching among different frames, we propose a tracking algorithm for constructing object pose sequence(COPS) based on Openpose. The position status and the ORB feature of the target pose are dynamically weighted and fused into new features. Target pose is searched in the corresponding target pose sequence by comparing the new features between the target pose in the sequence and every pose in current frame. When the target pose is matched, the influence of the position feature on the pose similarity could be enhanced when the target motion is continuously detected. When the target scale changes too much, the method can expand the contribution of the ORB feature to the pose similarity comparison. The experiments of human multitarget tracking algorithm are carried out on the PoseTrack and MOT datasets, and the results show that the proposed tracking algorithm overcomes the problem of target matching between frames.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124405327","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00113
Yunqing Guan, Qingsheng Li, Y. Tian
This paper designs and develops an Environmental Data News Generation (EDNG) system of Internet of things data acquisition and generation that can automatically collect data such as environmental temperature, humidity and light intensity in a region and automate broadcast by data news for healthcare. The system is based on digital data collection, Internet of things, embedded development and other technologies. Through designing hardware and software such as the design of networking data acquisition devices, the establishment of cloud forwarding servers, the development of terminal WeChat mini-programs and data news acquisition systems, the problem of automatic data collection, fusion generation and accurate and efficient reporting of regional environmental data news is solved. At the same time, through the research of regional environmental data news gathering and generation technology, the functions of automation of environmental data collection and real evolution of news broadcast were realized. The accuracy of data acquisition and the speed of news reporting are improved, and an effective strategy is provided for the automatic generation of other data news.
{"title":"IoT-Based Environmental Data News Generation System for Healthcare","authors":"Yunqing Guan, Qingsheng Li, Y. Tian","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00113","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00113","url":null,"abstract":"This paper designs and develops an Environmental Data News Generation (EDNG) system of Internet of things data acquisition and generation that can automatically collect data such as environmental temperature, humidity and light intensity in a region and automate broadcast by data news for healthcare. The system is based on digital data collection, Internet of things, embedded development and other technologies. Through designing hardware and software such as the design of networking data acquisition devices, the establishment of cloud forwarding servers, the development of terminal WeChat mini-programs and data news acquisition systems, the problem of automatic data collection, fusion generation and accurate and efficient reporting of regional environmental data news is solved. At the same time, through the research of regional environmental data news gathering and generation technology, the functions of automation of environmental data collection and real evolution of news broadcast were realized. The accuracy of data acquisition and the speed of news reporting are improved, and an effective strategy is provided for the automatic generation of other data news.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804333","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 : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00115
Xiangbin Shi, Jingyuan Tan, Deyuan Zhang
The indoor wheeled robot is widely used in research, industrial manufacturing, and service industries. For the positioning process of indoor wheeled mobile robots, the data from a single sensor is not reliable and accurate. The traditional solution to this problem is to use the extended Kalman filter (EKF) method, which suffers from linearization error and accumulation error. To tackle these problems, we propose Linear transformation error elimination extended Kalman filter(TEKF) to fuse multiple sensors. Firstly, the data of the sensors of the odometer, Inertial measurement unit(IMU) and lidar are collected and preprocessed, and a complementary filtering method is proposed to obtain the angular velocity. Secondly, the second-order Taylor series expansion is performed on the state and the observation equation, which overcomes the linearization error and improves the accuracy of data fusion. Finally, the backtracking processing method is adopted to eliminate the accumulated error and enhance the environmental adaptability. The experimental results of the real indoor wheeled robot shows that TEKF can effectively improve the accuracy of data fusion and ensure that the indoor wheeled robot can be more accurately positioned.
{"title":"Indoor Wheeled Robot Positioning Algorithm Based on Extended Kalman Filter","authors":"Xiangbin Shi, Jingyuan Tan, Deyuan Zhang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00115","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00115","url":null,"abstract":"The indoor wheeled robot is widely used in research, industrial manufacturing, and service industries. For the positioning process of indoor wheeled mobile robots, the data from a single sensor is not reliable and accurate. The traditional solution to this problem is to use the extended Kalman filter (EKF) method, which suffers from linearization error and accumulation error. To tackle these problems, we propose Linear transformation error elimination extended Kalman filter(TEKF) to fuse multiple sensors. Firstly, the data of the sensors of the odometer, Inertial measurement unit(IMU) and lidar are collected and preprocessed, and a complementary filtering method is proposed to obtain the angular velocity. Secondly, the second-order Taylor series expansion is performed on the state and the observation equation, which overcomes the linearization error and improves the accuracy of data fusion. Finally, the backtracking processing method is adopted to eliminate the accumulated error and enhance the environmental adaptability. The experimental results of the real indoor wheeled robot shows that TEKF can effectively improve the accuracy of data fusion and ensure that the indoor wheeled robot can be more accurately positioned.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126902118","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}
Wireless sensor networks (WSNs) for industrial manufacturing nowadays are demanding faster delivery of important data than ordinary data. Thus Medium Access Control (MAC) protocols are required to provide low delay media access for traffic of the important data. Successive Interference Cancellation (SIC), which enables multiple-packet reception, gives an opportunity to decrease access delay. Nevertheless, existing MAC protocls are either differetiate access delay for various traffic types without using SIC, or only exploit SIC for unique traffic type. To cover this gap, we propose a distributed MAC protocol that employ SIC to lower access delay for different traffic types in industrial WSNs. By analyzing performance of this protocol, we find a heuristic method to improve adaptability of the proposed protocol and prove the convergence of this heuristic approach. The major contributions of our work are: first, a twostage contention process is adopted in our protocol, which allows multiple transmitters to access edia simutaneously. Second, we analyze performance of the proposed protocol and find a heuristic method to improve it. With the heuristic method, our protocol is available in networks where status of traffic types is unkown. We also prove the convergence of this heuristic method. Simulation results reveal that our protocols performs better on access delay and packet loss rate than the existing good performing priority based distributed MAC protocols.
{"title":"A Heuristic Approach for Low Delay Distributed MAC using Successive Interference Cancellation in Priority-Based Industrial Wireless Network","authors":"Yida Xu, Qi Wang, Jianmin Liu, Chentao He, Boyu Diao, Yongjun Xu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00121","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00121","url":null,"abstract":"Wireless sensor networks (WSNs) for industrial manufacturing nowadays are demanding faster delivery of important data than ordinary data. Thus Medium Access Control (MAC) protocols are required to provide low delay media access for traffic of the important data. Successive Interference Cancellation (SIC), which enables multiple-packet reception, gives an opportunity to decrease access delay. Nevertheless, existing MAC protocls are either differetiate access delay for various traffic types without using SIC, or only exploit SIC for unique traffic type. To cover this gap, we propose a distributed MAC protocol that employ SIC to lower access delay for different traffic types in industrial WSNs. By analyzing performance of this protocol, we find a heuristic method to improve adaptability of the proposed protocol and prove the convergence of this heuristic approach. The major contributions of our work are: first, a twostage contention process is adopted in our protocol, which allows multiple transmitters to access edia simutaneously. Second, we analyze performance of the proposed protocol and find a heuristic method to improve it. With the heuristic method, our protocol is available in networks where status of traffic types is unkown. We also prove the convergence of this heuristic method. Simulation results reveal that our protocols performs better on access delay and packet loss rate than the existing good performing priority based distributed MAC protocols.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123109897","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}
2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)
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