2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)最新文献

A Secure Routing Mechanism for Industrial Wireless Networks Based on SDN 基于SDN的工业无线网络安全路由机制

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.000-2

Jie Li, Zhiping Yang, Xiu-shuang Yi, Tao Hong, Xingwei Wang

{"title":"A Secure Routing Mechanism for Industrial Wireless Networks Based on SDN","authors":"Jie Li, Zhiping Yang, Xiu-shuang Yi, Tao Hong, Xingwei Wang","doi":"10.1109/MSN.2018.000-2","DOIUrl":"https://doi.org/10.1109/MSN.2018.000-2","url":null,"abstract":"With the integration of industrialization and informatization, there are a large number of embedded industrial wireless physical devices that are susceptible to malicious intrusion by malicious nodes within the industrial wireless networks, which leads to perform unique internal attacks, such as DOS attacks, selfish attacks, Sinkhole attacks and black hole attacks. In order to detect and resist external attacks, the SDN technology is introduced into the existing industrial wireless network and the network equipment is managed by a centralized controller. At the same time, the controller shields the differences between network devices in the network bottom layer. Open control enables network users to define their own network routing and forwarding strategies, making the network more flexible and intelligent. Moreover, SDN controller can make global routing strategy according to the global state of the network and the underutilized resources in the network we introduce SDN paradigm into the industrial wireless network and propose a secure routing mechanism for industrial wireless networks based on SDN. The internal malicious nodes are detected by computing the node comprehensive trust value of node. We design a biologic heuristic algorithm based on the foraging principle of physarum as a network security routing algorithm to calculate the network security transmission path. The performance of packet delivery rate and average end to end delay are compared and analyzed. The result shows that the routing mechanism depicted in the thesis has better performance, and the security of data transmission is greatly improved.","PeriodicalId":264541,"journal":{"name":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124930599","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}

引用次数: 3

About MSN 2018 关于MSN 2018

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/msn.2018.00005

引用次数: 0

Clustering-based Communication Backbone for Large Scale UAV Networks 基于聚类的大规模无人机网络通信骨干网

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00007

Hai-hu Yu, Hejiao Huang, X. Jia

引用次数: 6

Complex Behavior Recognition Based on Convolutional Neural Network: A Survey 基于卷积神经网络的复杂行为识别研究进展

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00024

Jianxin Feng, Junmei Liu, Chengsheng Pan

引用次数: 2

Path Planning for Sensor Data Collection by Using UAVs 利用无人机采集传感器数据的路径规划

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00033

Baichuan Kong, Hejiao Huang, X. Jia

引用次数: 3

Deep Identity Confusion for Automatic Sleep Staging Based on Single-Channel EEG 基于单通道脑电图的深度身份混淆自动睡眠分期

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.000-6

Yu Liu, Ruiting Fan, Yucong Liu

引用次数: 4

Real-Time Trajectory Data Publishing Method with Differential Privacy 差分隐私的实时轨迹数据发布方法

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00029

Fengyun Li, Jinhua Yang, Lifang Xue, Dawei Sun

引用次数: 2

A Blockchain-Based Scheme for Secure Data Provenance in Wireless Sensor Networks 基于区块链的无线传感器网络安全数据溯源方案

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00009

Yu Zeng, Xing Zhang, Rizwan Akhtar, Changda Wang

{"title":"A Blockchain-Based Scheme for Secure Data Provenance in Wireless Sensor Networks","authors":"Yu Zeng, Xing Zhang, Rizwan Akhtar, Changda Wang","doi":"10.1109/MSN.2018.00009","DOIUrl":"https://doi.org/10.1109/MSN.2018.00009","url":null,"abstract":"In wireless sensor networks (WSNs), provenance is vital for assessing data's trustworthiness, detecting the misbehaviors conducted by adversaries or troubleshooting communication failures. The provenance can be encoded through fingerprinting the node IDs along a packet path where the packets are generated, forwarded and/or aggregated. Because WSNs are resource-tightened networks, most of the known provenance schemes applied in WSNs address the issues on how to reduce the provenance size with various compression techniques only. However, reducing the provenance size at a sensor node also costs too much energy. In addition, such schemes did not take the secure and persistant provenance storage for consideration in a long term. To fill the gap, we propose a blockchainbased data provenance scheme (BCP) of compression free, where the provenances are stored distributively on the nodes along the packet path and the BS can retrieve the provenance on demand through a query process. An edge computing based monitor network consisting of high performance nodes (H-nodes) is deployed above or nearby the WSNs, which keeps the WSN's provenance data in a blockchain-based database. The security and authenticity of the provenances are then protected. What's more, the WSN is released from consuming much energy in handling provenance data, which is more superior to all the previous schemes. Both the simulation and experiment results show that our scheme BCP is more energy efficient and secure than those of the known distributed data provenances.","PeriodicalId":264541,"journal":{"name":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115109292","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}

引用次数: 9

Ensemble Deep Learning Method for Short-Term Load Forecasting 短期负荷预测的集成深度学习方法

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00021

Haibo Guo, Lingling Tang, Yuexing Peng

{"title":"Ensemble Deep Learning Method for Short-Term Load Forecasting","authors":"Haibo Guo, Lingling Tang, Yuexing Peng","doi":"10.1109/MSN.2018.00021","DOIUrl":"https://doi.org/10.1109/MSN.2018.00021","url":null,"abstract":"Short-term load forecasting (STLF) is the basis for the economic operation of the power system, and accurate STLF can optimize the power company's generation scheduling and improve the economics and safety of power grid operation. Classical regression-based models are mainly developed for stationary time series, while power load is typical nonstationary one. Shallow neural network model usually cannot capture complicated non-linear pattern efficiently, while power load features complicated varying patterns due to the numerous factors such as region, climate, economics, industry. Deep neural network, especially recurrent neural network (RNN) methods, like long short-term memory (LSTM), can model complicated pattern efficiently with the state-of-the-art erformance, but the training of the deep network becomes much harder with the increase of input sequence length. Since the power load holds large span of periodicity from daily through yearly, LSTM cannot fully exploit the inner correlation of power load. In this paper, ensemble deep learning method is proposed to exploit both non-linear pattern by LSTM and large-span period by similar day method. The proposed method integrates several LSTM networks, and each network is fed with different input time sequences which are selected regarding the similarity of load pattern. Experiment results show the effectiveness of the proposed method when comparing with exiting methods.","PeriodicalId":264541,"journal":{"name":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123662626","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}

引用次数: 4

Multi-Dimension Context-Based Service Recommendation Algorithm in VANET 基于上下文的VANET多维服务推荐算法

2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2018-12-01 DOI: 10.1109/MSN.2018.00010

Yanliu Zheng, Juan Luo, Haibo Luo

{"title":"Multi-Dimension Context-Based Service Recommendation Algorithm in VANET","authors":"Yanliu Zheng, Juan Luo, Haibo Luo","doi":"10.1109/MSN.2018.00010","DOIUrl":"https://doi.org/10.1109/MSN.2018.00010","url":null,"abstract":"Aiming at the information overload and driving safety problems existing in VANET, this paper proposes a multidimension context-based service recommendation algorithm in VANET based on the recommended middleware architecture of VANET service. The middleware architecture not only shields the heterogeneity of the underlying devices, but also quickly captures the vehicle's rich real-time contextual information. The algorithm belongs to the content-based recommendation category. Firstly, the service station is filtered according to the context information, and the optional service station is selected. Secondly, the user preference model is calculated according to the user history service record. Then, the similarity between the service provided by the service station and the user preference model is calculated. Finally, the recommendation coefficient is calculated and sorted according to the recommendation coefficient, and the service that meets the personalized requirement is recommended for the user. In this paper, the Yelp real data set is used to simulate the algorithm. The simulation results show that the recommended results of the algorithm are more in line with the user's individual needs, and the accuracy of the recommendation results is improved, and the bypass probability caused by the service is reduced.","PeriodicalId":264541,"journal":{"name":"2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126538472","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}

引用次数: 0