The Internet recently passed an historic inflection point, with the number of broadband mobile devices surpassing the number of wired PCs and servers connected to the Internet. Mobility now profoundly affects the architecture, services and applications in both the wireless and wired domains. In this "bottom up" talk, we begin by discussing several specific mobility-related challenges and recent results in areas including mobility measurement (including privacy considerations) and modeling, and context-sensitive services. We then take a broader look at current and future challenges, and conclude by discussing several NSF investments in programs and projects in area of mobile networking.
{"title":"Research Challenges and Opportunities in a Mobility-centric World","authors":"J. Kurose","doi":"10.1145/2789168.2790089","DOIUrl":"https://doi.org/10.1145/2789168.2790089","url":null,"abstract":"The Internet recently passed an historic inflection point, with the number of broadband mobile devices surpassing the number of wired PCs and servers connected to the Internet. Mobility now profoundly affects the architecture, services and applications in both the wireless and wired domains. In this \"bottom up\" talk, we begin by discussing several specific mobility-related challenges and recent results in areas including mobility measurement (including privacy considerations) and modeling, and context-sensitive services. We then take a broader look at current and future challenges, and conclude by discussing several NSF investments in programs and projects in area of mobile networking.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128732569","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}
Konstantin Mikhaylov, J. Petäjäjärvi, Marko Mäkeläinen, Anton Paatelma, T. Hänninen
In the paper we present and demonstrate the modular prototyping platform designed for trialing the Internet of Things (IoT) applications. The new devices are constructed by stacking together the various hardware modules encapsulating power sources, processing units, wired and wireless transceivers, sensors and actuators, or sets of those. The main processing unit automatically identifies all the attached modules and adjusts own operation accordingly. The demo will showcase how the platform can be used for building up multi-radio technology enabled wireless devices which will automatically form a heterogeneous wireless sensor and actuator network (WSAN). The possible use case scenarios and the ongoing research activities around the platform will be highlighted as well.
{"title":"Demo: Modular Multi-radio Wireless Sensor Platform for IoT Trials with Plug&Play Module Connection","authors":"Konstantin Mikhaylov, J. Petäjäjärvi, Marko Mäkeläinen, Anton Paatelma, T. Hänninen","doi":"10.1145/2789168.2789176","DOIUrl":"https://doi.org/10.1145/2789168.2789176","url":null,"abstract":"In the paper we present and demonstrate the modular prototyping platform designed for trialing the Internet of Things (IoT) applications. The new devices are constructed by stacking together the various hardware modules encapsulating power sources, processing units, wired and wireless transceivers, sensors and actuators, or sets of those. The main processing unit automatically identifies all the attached modules and adjusts own operation accordingly. The demo will showcase how the platform can be used for building up multi-radio technology enabled wireless devices which will automatically form a heterogeneous wireless sensor and actuator network (WSAN). The possible use case scenarios and the ongoing research activities around the platform will be highlighted as well.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131064308","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}
Keystroke privacy is critical for ensuring the security of computer systems and the privacy of human users as what being typed could be passwords or privacy sensitive information. In this paper, we show for the first time that WiFi signals can also be exploited to recognize keystrokes. The intuition is that while typing a certain key, the hands and fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time-series of Channel State Information (CSI) values, which we call CSI-waveform for that key. In this paper, we propose a WiFi signal based keystroke recognition system called WiKey. WiKey consists of two Commercial Off-The-Shelf (COTS) WiFi devices, a sender (such as a router) and a receiver (such as a laptop). The sender continuously emits signals and the receiver continuously receives signals. When a human subject types on a keyboard, WiKey recognizes the typed keys based on how the CSI values at the WiFi signal receiver end. We implemented the WiKey system using a TP-Link TL-WR1043ND WiFi router and a Lenovo X200 laptop. WiKey achieves more than 97.5% detection rate for detecting the keystroke and 96.4% recognition accuracy for classifying single keys. In real-world experiments, WiKey can recognize keystrokes in a continuously typed sentence with an accuracy of 93.5%.
{"title":"Keystroke Recognition Using WiFi Signals","authors":"Kamran Ali, A. Liu, Wen Wang, Muhammad Shahzad","doi":"10.1145/2789168.2790109","DOIUrl":"https://doi.org/10.1145/2789168.2790109","url":null,"abstract":"Keystroke privacy is critical for ensuring the security of computer systems and the privacy of human users as what being typed could be passwords or privacy sensitive information. In this paper, we show for the first time that WiFi signals can also be exploited to recognize keystrokes. The intuition is that while typing a certain key, the hands and fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time-series of Channel State Information (CSI) values, which we call CSI-waveform for that key. In this paper, we propose a WiFi signal based keystroke recognition system called WiKey. WiKey consists of two Commercial Off-The-Shelf (COTS) WiFi devices, a sender (such as a router) and a receiver (such as a laptop). The sender continuously emits signals and the receiver continuously receives signals. When a human subject types on a keyboard, WiKey recognizes the typed keys based on how the CSI values at the WiFi signal receiver end. We implemented the WiKey system using a TP-Link TL-WR1043ND WiFi router and a Lenovo X200 laptop. WiKey achieves more than 97.5% detection rate for detecting the keystroke and 96.4% recognition accuracy for classifying single keys. In real-world experiments, WiKey can recognize keystrokes in a continuously typed sentence with an accuracy of 93.5%.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619364","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}
Xiufeng Xie, Xinyu Zhang, Swarun Kumar, Erran L. Li
Adaptive HTTP video streaming over LTE has been gaining popularity due to LTE's high capacity. Quality of adaptive streaming depends highly on the accuracy of client's estimation of end-to-end network bandwidth, which is challenging due to LTE link dynamics. In this paper, we present piStream, that allows a client to efficiently monitor the LTE basestation's PHY-layer resource allocation, and then map such information to an estimation of available bandwidth. Given the PHY-informed bandwidth estimation, piStream uses a probabilistic algorithm to balance video quality and the risk of stalling, taking into account the burstiness of LTE downlink traffic loads. We conduct a real-time implementation of piStream on a software-radio tethered to an LTE smartphone. Comparison with state-of-the-art adaptive streaming protocols demonstrates that piStream can effectively utilize the LTE bandwidth, achieving high video quality with minimal stalling rate.
{"title":"piStream: Physical Layer Informed Adaptive Video Streaming over LTE","authors":"Xiufeng Xie, Xinyu Zhang, Swarun Kumar, Erran L. Li","doi":"10.1145/2789168.2790118","DOIUrl":"https://doi.org/10.1145/2789168.2790118","url":null,"abstract":"Adaptive HTTP video streaming over LTE has been gaining popularity due to LTE's high capacity. Quality of adaptive streaming depends highly on the accuracy of client's estimation of end-to-end network bandwidth, which is challenging due to LTE link dynamics. In this paper, we present piStream, that allows a client to efficiently monitor the LTE basestation's PHY-layer resource allocation, and then map such information to an estimation of available bandwidth. Given the PHY-informed bandwidth estimation, piStream uses a probabilistic algorithm to balance video quality and the risk of stalling, taking into account the burstiness of LTE downlink traffic loads. We conduct a real-time implementation of piStream on a software-radio tethered to an LTE smartphone. Comparison with state-of-the-art adaptive streaming protocols demonstrates that piStream can effectively utilize the LTE bandwidth, achieving high video quality with minimal stalling rate.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126336290","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}
Florian Wamser, Michael Seufert, P. Casas, R. Irmer, P. Tran-Gia, R. Schatz
The performance of YouTube in cellular networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). In this paper we present YoMoApp (YouTube Performance Monitoring Application), an Android application which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, re-buffering, and video quality levels) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of cellular networks with respect to YouTube traffic, as well as to develop optimizations and QoE models for mobile HTTP adaptive streaming. We try YoMoApp through real subjective QoE lab tests showing that the tool is accurate to capture the experience of end-users watching YouTube on smartphones.
{"title":"Poster: Understanding YouTube QoE in Cellular Networks with YoMoApp: A QoE Monitoring Tool for YouTube Mobile","authors":"Florian Wamser, Michael Seufert, P. Casas, R. Irmer, P. Tran-Gia, R. Schatz","doi":"10.1145/2789168.2795176","DOIUrl":"https://doi.org/10.1145/2789168.2795176","url":null,"abstract":"The performance of YouTube in cellular networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). In this paper we present YoMoApp (YouTube Performance Monitoring Application), an Android application which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, re-buffering, and video quality levels) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of cellular networks with respect to YouTube traffic, as well as to develop optimizations and QoE models for mobile HTTP adaptive streaming. We try YoMoApp through real subjective QoE lab tests showing that the tool is accurate to capture the experience of end-users watching YouTube on smartphones.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"482 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123056945","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}
M. A. Hoque, Kasperi Saarikoski, Eemil Lagerspetz, Julien Mineraud, S. Tarkoma
Minimizing the energy consumption of mobile devices for wireless network access is important. In this article, we analyze the energy efficiency of a new set of applications which use Virtual Private Network (VPN) tunnels for secure communication. First, we discuss the energy efficiency of a number of VPN applications from a large scale deployment of 500 K devices. We next measure the energy consumption of some of these applications with different use cases. Finally, we demonstrate that a VPN tunnel can be instrumented for enhanced energy efficiency with multimedia streaming applications. Our results indicate energy savings of 40% for this class of applications.
{"title":"Poster: VPN Tunnels for Energy Efficient Multimedia Streaming","authors":"M. A. Hoque, Kasperi Saarikoski, Eemil Lagerspetz, Julien Mineraud, S. Tarkoma","doi":"10.1145/2789168.2795168","DOIUrl":"https://doi.org/10.1145/2789168.2795168","url":null,"abstract":"Minimizing the energy consumption of mobile devices for wireless network access is important. In this article, we analyze the energy efficiency of a new set of applications which use Virtual Private Network (VPN) tunnels for secure communication. First, we discuss the energy efficiency of a number of VPN applications from a large scale deployment of 500 K devices. We next measure the energy consumption of some of these applications with different use cases. Finally, we demonstrate that a VPN tunnel can be instrumented for enhanced energy efficiency with multimedia streaming applications. Our results indicate energy savings of 40% for this class of applications.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122265523","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}
Dynamic spectrum access (DSA) technique has been widely accepted as a crucial solution to mitigate the potential spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how privacy issues are managed. In current DSA proposals, the sensitive operation parameters of both federal incumbent users (IUs) and commercial secondary users (SUs) need to be shared with the dynamic spectrum access system (SAS) to realize efficient spectrum allocation. Since SAS is not necessarily operated by a trusted third party, the current proposals dissatisfy the privacy requirement of both IUs and SUs. To address the privacy issues, this paper presents a privacy-preserving SAS design, which realizes the complex spectrum allocation decision process of DSA through secure computation over ciphertext based on homomorphic encryption, thus none of the IU or SU operation parameters are exposed to SAS.
{"title":"Poster: Privacy-Preserving Server-Driven Dynamic Spectrum Access System","authors":"Yanzhi Dou, K. Zeng, Yaling Yang","doi":"10.1145/2789168.2795161","DOIUrl":"https://doi.org/10.1145/2789168.2795161","url":null,"abstract":"Dynamic spectrum access (DSA) technique has been widely accepted as a crucial solution to mitigate the potential spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how privacy issues are managed. In current DSA proposals, the sensitive operation parameters of both federal incumbent users (IUs) and commercial secondary users (SUs) need to be shared with the dynamic spectrum access system (SAS) to realize efficient spectrum allocation. Since SAS is not necessarily operated by a trusted third party, the current proposals dissatisfy the privacy requirement of both IUs and SUs. To address the privacy issues, this paper presents a privacy-preserving SAS design, which realizes the complex spectrum allocation decision process of DSA through secure computation over ciphertext based on homomorphic encryption, thus none of the IU or SU operation parameters are exposed to SAS.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"1 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123793925","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}
Dalia-Georgiana Herculea, Majed Haddad, V. Capdevielle, Chung Shue Chen
The co-existence of small cells and macro cells is a key feature of 4G and future networks. This heterogeneity, together with the increased mobility of user devices can generate a high handover frequency that could lead to unreasonably high call drop probability or poor user experience. By performing smart mobility management, the network can pro-actively adapt to the user and guarantee seamless and smooth cell transitions. In this work, we introduce an algorithm that takes as input sounding reference signal (SRS) measurements available at the base station (eNodeB in 4G systems) to estimate with a low computational requirement the mobility level of the user and with no modification at the user device/equipment (UE) side. The performance of the algorithm is showcased using realistic data and mobility traces. Results show that the classification of UE speed to three mobility classes can be achieved with accuracy of 87% for low mobility, 93% for medium mobility, and 94% for high mobility, respectively.
{"title":"Poster: Network-Based UE Mobility Estimation in Mobile Networks","authors":"Dalia-Georgiana Herculea, Majed Haddad, V. Capdevielle, Chung Shue Chen","doi":"10.1145/2789168.2795166","DOIUrl":"https://doi.org/10.1145/2789168.2795166","url":null,"abstract":"The co-existence of small cells and macro cells is a key feature of 4G and future networks. This heterogeneity, together with the increased mobility of user devices can generate a high handover frequency that could lead to unreasonably high call drop probability or poor user experience. By performing smart mobility management, the network can pro-actively adapt to the user and guarantee seamless and smooth cell transitions. In this work, we introduce an algorithm that takes as input sounding reference signal (SRS) measurements available at the base station (eNodeB in 4G systems) to estimate with a low computational requirement the mobility level of the user and with no modification at the user device/equipment (UE) side. The performance of the algorithm is showcased using realistic data and mobility traces. Results show that the classification of UE speed to three mobility classes can be achieved with accuracy of 87% for low mobility, 93% for medium mobility, and 94% for high mobility, respectively.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121580077","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}
Mobile web browsing is experienced slow because of the limited rendering capability of the mobile devices, wireless latency, and incremental rendering of the page or resource loading. The browser renders resources in between two consecutive resource downloads. However, during this period, the wireless interfaces consume energy doing nothing useful. In this work, we measure the performance of SPDY for mobile web browsing. We demonstrate that mobile devices waste energy by keeping the wireless network interface idle between consecutive resource downloads. We next show that by identifying the embedded resources in a web page and downloading those resources in parallel at the very beginning can reduce the small idle periods and thus energy consumption by 20-50%, depending on the wireless network type.
{"title":"Poster: Extremely Parallel Resource Pre-Fetching for Energy Optimized Mobile Web Browsing","authors":"M. A. Hoque, S. Tarkoma, Tuikku Anttila","doi":"10.1145/2789168.2795167","DOIUrl":"https://doi.org/10.1145/2789168.2795167","url":null,"abstract":"Mobile web browsing is experienced slow because of the limited rendering capability of the mobile devices, wireless latency, and incremental rendering of the page or resource loading. The browser renders resources in between two consecutive resource downloads. However, during this period, the wireless interfaces consume energy doing nothing useful. In this work, we measure the performance of SPDY for mobile web browsing. We demonstrate that mobile devices waste energy by keeping the wireless network interface idle between consecutive resource downloads. We next show that by identifying the embedded resources in a web page and downloading those resources in parallel at the very beginning can reduce the small idle periods and thus energy consumption by 20-50%, depending on the wireless network type.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115908384","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}
Davide Pesavento, Giulio Grassi, G. Pau, P. Bahl, S. Fdida
The need for Internet access from moving vehicles has been steadily increasing in the past few years. Solutions that rely on cellular connectivity are becoming impractical to deploy due to technical and economic reasons. Car-Fi proposes an approach that leverages existing home Wi-Fi access points configured in dual-access mode, in order to offload all data traffic from the congested and expensive cellular infrastructure to whatever Wi-Fi network is available. Thanks to an improved scanning algorithm and numerous optimizations to the connection setup, Car-Fi makes downloading large amounts of data from a moving car feasible.
{"title":"Demo: Car-Fi: Opportunistic V2I by Exploiting Dual-Access Wi-Fi Networks","authors":"Davide Pesavento, Giulio Grassi, G. Pau, P. Bahl, S. Fdida","doi":"10.1145/2789168.2789171","DOIUrl":"https://doi.org/10.1145/2789168.2789171","url":null,"abstract":"The need for Internet access from moving vehicles has been steadily increasing in the past few years. Solutions that rely on cellular connectivity are becoming impractical to deploy due to technical and economic reasons. Car-Fi proposes an approach that leverages existing home Wi-Fi access points configured in dual-access mode, in order to offload all data traffic from the congested and expensive cellular infrastructure to whatever Wi-Fi network is available. Thanks to an improved scanning algorithm and numerous optimizations to the connection setup, Car-Fi makes downloading large amounts of data from a moving car feasible.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117162526","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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