{"title":"Analysis of BTI Induced Input Buffer Aging Based on 32nm CMOS Process","authors":"Jinmei Shi, Jiajing Cai, Henan Wu","doi":"10.1109/ICCSN52437.2021.9463664","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463664","url":null,"abstract":"This paper makes a breakthrough to accurately estimate and comprehensively analyze the transmission delay of input buffer caused by BTI aging via establishing aging model and comparing with standard logic unit. It presents the BTI aging for traditional input buffer within 10 years, designed in 32nm CMOS technology, and simulated with LTSPICE software. The use of Schmitt flip-flops as input buffers enables the circuit to increase noise tolerance and drive capability. The simulation results show that when the power supply voltage is 0.8V-1.1V, the transmission delay of input buffer will increase by 60% after 10 years under the influence of BTI aging, compared with 31% delay increment of CMOS 11-cascaded inverters under the same technology. In order to improve the reliability, the proposed technique named ICMT is introduced, which contributes to reducing 34% propagation delay for the input buffer.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122549128","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}
Bowen Yang, Pengchao Han, Chuan Feng, Yejun Liu, Lei Guo
{"title":"Service Migration with High-Order MDP in Mobile Edge Computing","authors":"Bowen Yang, Pengchao Han, Chuan Feng, Yejun Liu, Lei Guo","doi":"10.1109/ICCSN52437.2021.9463603","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463603","url":null,"abstract":"Mobile Edge Computing (MEC) has gained a lot of popularity for supporting newly emerging services with low latency by deploying servers in base stations (BSs). For a moving user, the Quality of Service (QoS) needs to be guaranteed through service migration among edge servers. To avoid service interruption, determining when and where to migrate services is critical and challenging for users with unknown future trajectories. Besides, frequent service migration incurs unexpected high network resource consumption, resulting in a trade-off between QoS and resource cost. In this paper, we focus on the problem of service migration in MEC networks aiming at minimizing the total resource cost while guaranteeing the QoS of moving users. We innovatively model the service migration of a user using k-order Markov Decision Process (MDP), where the correlation of user’s historical locations is taken in account to help better decision. The optimal correlation coefficient k is obtained through analyzing the real-world dataset of taxi trajectories. An online algorithm based on Deep Q-Network (DQN) is proposed to solve the service migration problem to minimize the long-term communication and migration costs. Compared with the widely-used benchmarks, our algorithm shows a better performance in reducing communication and migration costs under different parameter settings.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A 5G-Oriented LDPC Encoder Based on Byte-Parallel Configurable Cyclic Shift","authors":"Yisong Sun, Huang-Babg Li, Chen Guo, Donglin Wang","doi":"10.1109/ICCSN52437.2021.9463607","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463607","url":null,"abstract":"In this paper, we propose a Byte-Parallel Configurable Cyclic Shift (BP-CCS) algorithm, which converts the cyclic shift into a byte-parallel form. This method alleviates the low efficiency of cyclic shift calculation in Low Density Parity Check (LDPC) encoding under the 5G protocol effectively. Besides, we also expand the instruction set of self-developed DSP Universal Communication Processor (UCP) to cope with the hardware implementation bottleneck of BP-CCS algorithm. This allows the implementation of a BP-CCS-based LDPC encoder on UCP, which has been verified on the taped-out chip. Experimental results show that the time consumed by the BP-CCS-based LDPC encoder is about 1/50 of the time specified in 5G communication protocol standard, and the encoder architecture can be easily reconstructed in real time through parameter configuration.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126072581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and Implementation of Fault Diagnosis System for Power Communication Network Based on CNN","authors":"Yang Shan, D. Liang, Deng Guoru, Liu Yuan","doi":"10.1109/ICCSN52437.2021.9463600","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463600","url":null,"abstract":"In order to solve the problem of fast fault location in power communication network, a fault diagnosis system for power communication network based on CNN is designed. Firstly, the model structure and visual function module of the fault diagnosis system are designed, then the key technologies and processes of model realization and visual realization of fault diagnosis are expounded, and the system implementation environment is built and optimized. Finally, the overall operation of the system is introduced and demonstrated. The system designed in this paper can use CNN-based fault diagnosis algorithm to locate and diagnose network faults quickly, and realize the visualization process of network topology and fault diagnosis process. It supports the management and classification of different networks, and has the advantages of high efficiency and flexibility.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129102884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on Knowledge Storage and Query Technology Based on General Graph Data Processing Framework","authors":"Bihui Yu, Yabiao Zhang, Huajun Sun","doi":"10.1109/ICCSN52437.2021.9463640","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463640","url":null,"abstract":"With the development of the Semantic Web, more and more data is currently managed in the form of knowledge graphs. Different knowledge storage and query modes have their own advantages, but also have shortcomings, and there is no unified standard. Aiming at the current deficiencies in knowledge storage and knowledge query technology, this paper proposes a knowledge storage and query scheme based on TinkerPop graph computing framework, a general graph data processing framework that combines Neo4j massive graph data storage capabilities and SPARQL semantic query capabilities.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127582193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on Electronic Nose Drift Suppression Algorithm based on Classifier Integration and Active Learning","authors":"Qiang Li, Pengchao Wu, Zhifang Liang, Yang Tao","doi":"10.1109/ICCSN52437.2021.9463654","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463654","url":null,"abstract":"In the field of electronic nose(E-nose) research, the underlying gas sensor is affected by environmental changes, aging of its own devices, sensor poisoning and other factors, which will cause the detection value to drift. Besides, the need for a large number of labeled samples in the pattern recognition algorithm will lead to excessively high model training costs. In order to solve the problems mentioned above, a method that combines classifier integration and active learning to reduce the model training cost by reducing the number of labeled samples is proposed in this paper. Using this method, the trend of sensor drift is captured by classifier integration, the number of single-labeled samples is dynamically adjusted, and finally the drift of the gas sensor array is suppressed. From the experiment results, it can be found that the sensor drift can be satisfactorily solved by the proposed method.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128381027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pedestrian Traffic Lights Classification Using Transfer Learning in Smart City Application","authors":"Somaiya Khan, Yinglei Teng, Jianuo Cui","doi":"10.1109/ICCSN52437.2021.9463615","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463615","url":null,"abstract":"Traffic accidents have become a serious issue in cities. Millions of people die in traffic accidents annually and among them the major cause is the pedestrian jaywalking. To solve this traffic issue and ensure efficient traffic monitoring, we introduced the surveillance system using AI powered UAVs in Internet of flying things based smart city scenario. To accurately classify the pedestrian traffic lights, we use the computer vision technology. We have created our own local dataset containing 809 images where 441 images belong to red signal class while 368 images belong to green signal class. We explore the power of transfer learning based on DNNs to overcome the limitation of dataset for pedestrian traffic lights classification. In this approach, we use the pre-trained MobileNetV2 model and freeze the weights. By leveraging the pre-trained convolutional base, we add our own fully connected layers on top of the model for classification. To handle the problem of limited data, we also perform the data augmentation. The task is formulated as binary classification problem. By using the MobileNetV2 on challenging and very diverse dataset, we achieve the accuracy of 94.92%, 91.84% specificity and 97.10% sensitivity.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130004420","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}
Qifan Yang, K. Dong, Junlei Song, F. Jin, W. Mo, Y. Hui
{"title":"sA Weak Signal Detection Method Based on Memristor-Based Duffing-Van der pol Chaotic Synchronization System","authors":"Qifan Yang, K. Dong, Junlei Song, F. Jin, W. Mo, Y. Hui","doi":"10.1109/ICCSN52437.2021.9463633","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463633","url":null,"abstract":"Aiming at the deficiencies of the existing chaotic detection methods, a new weak signal detection method based on chaotic synchronization system is proposed in this paper. This detection system is achieved by a memristor-based Duffing-Van der pol chaotic system, and the drive-response method is used to construct a synchronization system. By analyzing the synchronization error of the detection system, the amplitude estimate method of the test signal is proposed. This method only needs the chaotic system run in the chaotic state and avoids solving the running state. It can effectively solve the problems of complex parameter setting, long state transition time and difficulty in state determination in traditional detection methods. Experimental results indicate that this new method can effectively estimate the parameter information of the test signal.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132629319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on Node Localization of Underwater Sensor Networks Based on Node Dynamic Selection and Movement Prediction","authors":"Rui Li, Hongxi Yin, Jianying Wang, Lianyou Jing","doi":"10.1109/ICCSN52437.2021.9463657","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463657","url":null,"abstract":"A node positioning method based on dynamic node selection and mobile prediction (NDSMP) for underwater wireless sensor networks is proposed, which can effectively copy with the issues of network edge and network void. The NDSMP can predict the location of a node after its movement based on its past location and dynamically select reference nodes. It is shown by our simulation experiments that the NDSMP is superior to the existing positioning algorithms in terms of localization coverage and localization average error, especially when the network is relatively sparse and the number of nodes is relatively small.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"307 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132949492","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}
Xueying Han, Yuhan Zhao, K. Yu, Xiaohong Huang, Kun Xie, Hua Wei
{"title":"Utility-Optimized Resource Allocation in Computing-Aware Networks","authors":"Xueying Han, Yuhan Zhao, K. Yu, Xiaohong Huang, Kun Xie, Hua Wei","doi":"10.1109/ICCSN52437.2021.9463597","DOIUrl":"https://doi.org/10.1109/ICCSN52437.2021.9463597","url":null,"abstract":"The rapid development of 5G and Artificial Intelligence technologies has brought various applications with specific requirements in both computing performance and network performance. At the same time, ubiquitous computing devices are interconnected to the Internet Service Provider’s network. Computing-aware networking, as the integration of networking and computing, has become a hot topic in both academia and industries. Motivated by this new network architecture, we present a Computing-aware Bandwidth Allocation method based on utility optimization, called CABA. The proposed method enables the network to schedule eligible computing nodes to serve the requested service, and coordinate network resources (e.g., network cost, bandwidth) so that the traffic can be routed along the desirable path. Experimental results show that our proposed method can achieve high utility in relation to bandwidth allocation and provide service scheduling scheme leveraging both computing capability and network cost.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115626326","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}