2020 29th International Conference on Computer Communications and Networks (ICCCN)最新文献_第7页

Practical and White-Box Anomaly Detection through Unsupervised and Active Learning 基于无监督和主动学习的实用白盒异常检测

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209704

Yao Wang, Zhaowei Wang, Zejun Xie, Nengwen Zhao, Junjie Chen, Wenchi Zhang, Kaixin Sui, Dan Pei

{"title":"Practical and White-Box Anomaly Detection through Unsupervised and Active Learning","authors":"Yao Wang, Zhaowei Wang, Zejun Xie, Nengwen Zhao, Junjie Chen, Wenchi Zhang, Kaixin Sui, Dan Pei","doi":"10.1109/ICCCN49398.2020.9209704","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209704","url":null,"abstract":"To ensure quality of service and user experience, large Internet companies often monitor various Key Performance Indicators (KPIs) of their systems so that they can detect anomalies and identify failure in real time. However, due to a large number of various KPIs and the lack of high-quality labels, existing KPI anomaly detection approaches either perform well only on certain types of KPIs or consume excessive resources. Therefore, to realize generic and practical KPI anomaly detection in the real world, we propose a KPI anomaly detection framework named iRRCF-Active, which contains an unsupervised and white-box anomaly detector based on Robust Random Cut Forest (RRCF), and an active learning component. Specifically, we novelly propose an improved RRCF (iRRCF) algorithm to overcome the drawbacks of applying original RRCF in KPI anomaly detection. Besides, we also incorporate the idea of active learning to make our model benefit from high-quality labels given by experienced operators. We conduct extensive experiments on a large-scale public dataset and a private dataset collected from a large commercial bank. The experimental resulta demonstrate that iRRCF-Active performs better than existing traditional statistical methods, unsupervised learning methods and supervised learning methods. Besides, each component in iRRCF-Active has also been demonstrated to be effective and indispensable.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115513541","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: 15

Machine Learning Based Workload Prediction in Cloud Computing 云计算中基于机器学习的工作负荷预测

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209730

Jiechao Gao, Haoyu Wang, Haiying Shen

{"title":"Machine Learning Based Workload Prediction in Cloud Computing","authors":"Jiechao Gao, Haoyu Wang, Haiying Shen","doi":"10.1109/ICCCN49398.2020.9209730","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209730","url":null,"abstract":"As a widely used IT service, more and more companies shift their services to cloud datacenters. It is important for cloud service providers (CSPs) to provide cloud service resources with high elasticity and cost-effectiveness and then achieve good quality of service (QoS) for their clients. However, meeting QoS with cost-effective resource is a challenging problem for CSPs because the workloads of Virtual Machines (VMs) experience variation over time. It is highly necessary to provide an accurate VMs workload prediction method for resource provisioning to efficiently manage cloud resources. In this paper, we first compare the performance of representative state-of-the-art workload prediction methods. We suggest a method to conduct the prediction a certain time before the predicted time point in order to allow sufficient time for task scheduling based on predicted workload. To further improve the prediction accuracy, we introduce a clustering based workload prediction method, which first clusters all the tasks into several categories and then trains a prediction model for each category respectively. The trace-driven experiments based on Google cluster trace demonstrates that our clustering based workload prediction methods outperform other comparison methods and improve the prediction accuracy to around 90% both in CPU and memory.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"44 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115559592","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: 136

Splitter: An Efficient Scheme to Determine the Geolocation of Cloud Data Publicly 拆分器:一种公开确定云数据地理位置的有效方案

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209651

Yang Zhang, D. Jia, Shijie Jia, Limin Liu, Jingqiang Lin

{"title":"Splitter: An Efficient Scheme to Determine the Geolocation of Cloud Data Publicly","authors":"Yang Zhang, D. Jia, Shijie Jia, Limin Liu, Jingqiang Lin","doi":"10.1109/ICCCN49398.2020.9209651","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209651","url":null,"abstract":"Outsourcing data to the cloud has become a trend, and the geolocation of cloud data attracts public attention in recent years, which is relevant to data availability (e.g., disaster tolerant), data security and policies (e.g. USA Patrio Act). Unfortunately, cloud service providers are not fully trusted to the data owners. This is because the data owners lose the physical control over the cloud data, and cloud service providers have the ability and motivation to change the geolocation of cloud data between different data centers. Therefore, designing a scheme to determine the geolocation of cloud data for data owners is an urgent problem to be solved.In this paper, we propose Splitter, an efficient scheme to determine the geolocation of cloud data publicly. In Splitter, we first design a splitting method, which breaks up the challenge and proof, and only considers the response delay resulting from the general operations (i.e., addition and multiplication) to obtain the accurate response delay. Second, we combine random forest algorithm and improved triangulation method to determine the geolocation accurately. Third, we take a series of theoretical comparison and extensive experiments to evaluate our scheme. The results illustrate the efficiency and practicality of our scheme.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123842441","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

A Q-learning based Method for Energy-Efficient Computation Offloading in Mobile Edge Computing 一种基于q学习的移动边缘计算节能卸载方法

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209738

Kai Jiang, Huan Zhou, Dawei Li, Xuxun Liu, Shouzhi Xu

{"title":"A Q-learning based Method for Energy-Efficient Computation Offloading in Mobile Edge Computing","authors":"Kai Jiang, Huan Zhou, Dawei Li, Xuxun Liu, Shouzhi Xu","doi":"10.1109/ICCCN49398.2020.9209738","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209738","url":null,"abstract":"Mobile Edge Computing (MEC) has emerged as a promising computing paradigm in 5G networks, which can empower User Equipments (UEs) with computation and energy resources offered by migrating workloads from the UEs to the MEC servers. Although the issues of computation offloading and resource allocation in MEC have been studied with different optimization objectives, they mainly investigate quasi-static system environments, without considering the different resource requirements and time-varying system conditions in a dynamic system. In this paper, we exploit a multi-user MEC system, and investigate the task execution scheme for dynamic joint optimization of offloading decision and resource assignment. Our objective is to minimize the energy consumption of all UEs, with considering the delay constraint as well as the dynamic resource requirements of heterogeneous computation tasks. Accordingly, we formulate the problem as a mixed integer non-linear programming problem (MINLP), and propose a value iteration based Reinforcement Learning (RL) approach, named Q-Learning, to obtain the optimal policy of computation offloading and resource allocation. Simulation results demonstrate that the proposed approach can significantly decrease UEs’ energy consumption in different scenarios, compared with other baseline methods.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121872826","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: 12

Location Privacy-Preserving Truth Discovery in Mobile Crowd Sensing 移动人群感知中位置隐私保护的真相发现

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209742

Jingsheng Gao, Shaojing Fu, Yuchuan Luo, Tao Xie

{"title":"Location Privacy-Preserving Truth Discovery in Mobile Crowd Sensing","authors":"Jingsheng Gao, Shaojing Fu, Yuchuan Luo, Tao Xie","doi":"10.1109/ICCCN49398.2020.9209742","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209742","url":null,"abstract":"Truth discovery techniques are commonly used in mobile crowd sensing (MCS) applications to infer accurate aggregated results based on quality-aware data aggregation. However, the location information of participants may be exposed when they upload their sensitive geo-tagged sensory data to relative platforms. While there are considerable existing privacy preserving truth discovery schemes for MCS, they mainly focus on protecting the privacy of sensory data, neglecting the tagged location information which is of equal if not higher importance for the privacy of participants. In this paper, we propose a novel and efficient location privacy preserving truth discovery (LoPPTD) mechanism, which can achieve data aggregation with high accuracy, while protecting both location privacy and data privacy of users. By structuring multi-dimensional sensory data obtained at different locations and exploiting homomorphic Paillier encryption, our approach can prevent leakage of both sensory data and tagged locations effectively. Also, super-increasing sequence techniques are employed in Lo-PPTD to ensure efficiency and feasibility. Theoretical analysis and thorough experiments performed on real-world datasets demonstrate that the proposed scheme can achieve high aggregation accuracy while providing complete privacy protection for users.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116644275","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

Joint Optimization Of Routing and Flexible Ethernet Assignment In Multi-layer Multi-domain Networks 多层多域网络中路由与灵活以太网分配的联合优化

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209665

Dahina Koulougli, K. Nguyen, M. Cheriet

{"title":"Joint Optimization Of Routing and Flexible Ethernet Assignment In Multi-layer Multi-domain Networks","authors":"Dahina Koulougli, K. Nguyen, M. Cheriet","doi":"10.1109/ICCCN49398.2020.9209665","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209665","url":null,"abstract":"Optimized routing in multi-layer multi-domain (MLMD) IP-optical networks is challenging due to different technologies and policies in different domains. In this paper, we investigate the problem of using the hierarchical path computation engine (PCE) to leverage the performance of FlexE—the new flexible Ethernet technology which is used to map traffic between different layers and different domains. Our proposed PCE can be implemented in MLMD orchestration platforms to optimize network utilization while meeting delay constraints. We formulate the optimization problems of traffic routing and physical slot assignment for both FlexE-Aware and FlexE-Unaware modes with respect to QoS requirements, intra-domain information privacy and FlexE constraints. To solve the problem, we propose new algorithms that jointly optimize the routing and FlexE client assignment in polynomial time. To deal with the issue of missing intra-domain information, we use a novel implicit routing strategy to collect the intra-domain information from the child PCEs. Simulation results show the proposed solution achieves 90.1% higher efficiency than the state-of-the-art solutions.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114953890","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

Driver Identification Leveraging Single-turn Behaviors via Mobile Devices 利用移动设备的单转弯行为进行驾驶员识别

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209713

Yan Wang, Tianming Zhao, Fatemeh Tahmasbi, Jerry Q. Cheng, Yingying Chen, Jiadi Yu

{"title":"Driver Identification Leveraging Single-turn Behaviors via Mobile Devices","authors":"Yan Wang, Tianming Zhao, Fatemeh Tahmasbi, Jerry Q. Cheng, Yingying Chen, Jiadi Yu","doi":"10.1109/ICCCN49398.2020.9209713","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209713","url":null,"abstract":"Drivers’ identities are essential information that can facilitate a broad range of applications. For example, by understanding who is driving the vehicle when an accident happens, insurance companies could determine the liability and payment in a car accident claim case with high confidence. Another example, pick-up service companies could track the identities of their drivers to ensure that authorized drivers are driving esteemed clients to their destinations. While there are existing studies that can utilize video cameras and dedicated sensors to identify drivers, they either have privacy issues or require additional hardware, which is not practical enough for daily uses. In this paper, we devise a low-cost driver identification system, which can determine drivers’ identities by using sensors readily available in wearable devices. Our system captures the unique driving behaviors during pervasive but momentary driving events (i.e., turning at intersections) with motion sensors, which are widely integrated into commodity wearable devices (e.g., smartphones and activity trackers). Toward this end, we extensively analyze people’s driving behaviors and identify the critical turning events that capture people’s unique behavioral patterns for driver identification. We design a fine-grained turning segmentation method that divides sensor data into critical turning stages (i.e., before, during, and after-turn stages), which provide multiple dimensions of turning behavioral metrics facilitating driver identification. The system extracts unique turning behavior features from time and frequency domains to enable driver identification based on drivers’ turning behaviors at different types of turns. Extensive experiments are conducted with 12 drivers and various types of turns in real-road conditions. The results demonstrate that our system can identify drivers with high accuracy and low falsepositive rate based on one single turning event.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124978009","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

Providing resilience to UAV swarms following planned missions 为无人机群执行计划任务提供弹性

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209634

J. Wubben, Izan Catalán, Manel Lurbe, Francisco Fabra, F. Martinez, C. Calafate, Juan-Carlos Cano, P. Manzoni

{"title":"Providing resilience to UAV swarms following planned missions","authors":"J. Wubben, Izan Catalán, Manel Lurbe, Francisco Fabra, F. Martinez, C. Calafate, Juan-Carlos Cano, P. Manzoni","doi":"10.1109/ICCCN49398.2020.9209634","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209634","url":null,"abstract":"As we experience an unprecedented growth in the field of Unmanned Aerial Vehicles (UAVs), more and more applications keep arising due to the combination of low cost and flexibility provided by these flying devices, especially those of the multirrotor type. Within this field, solutions where several UAVs team-up to create a swarm are gaining momentum as they enable to perform more sophisticated tasks, or accelerate task execution compared to the single-UAV alternative. However, advanced solutions based on UAV swarms still lack significant advancements and validation in real environments to facilitate their adoption and deployment. In this paper we take a step ahead in this direction by proposing a solution that improves the resilience of swarm flights, focusing on handling the loss of the swarm leader, which is typically the most critical condition to be faced. Experiments using our UAV emulation tool (ArduSim) evidence the correctness of the protocol under adverse circumstances, and highlight that swarm members are able to seamlessly switch to an alternative leader when necessary, introducing a negligible delay in the process in most cases, while keeping this delay within a few seconds even in worst-case conditions.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129764489","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

Facial Micro-Expression Recognition Using Quaternion-Based Sparse Representation 基于四元数稀疏表示的面部微表情识别

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209630

Hang Yang, Qingshan Wang, Qi Wang, Peng Liu, Wei Huang

{"title":"Facial Micro-Expression Recognition Using Quaternion-Based Sparse Representation","authors":"Hang Yang, Qingshan Wang, Qi Wang, Peng Liu, Wei Huang","doi":"10.1109/ICCCN49398.2020.9209630","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209630","url":null,"abstract":"Facial micro-expressions are characterized by their extremely short duration and low intensity, can provide an important basis for judging people’s emotions, and therefore have promising potential applications in numerous fields. This paper puts forward a novel method for recognizing micro-expressions by using a quaternion-based sparse representation (QSR) model combined with the integral projection of difference energy image (IP-DEI) to extract features from color images of human faces . Using the quaternion model to jointly process color images can obtain greater feature information than gray or RGB images, and the QSR model helps reduce feature dimensions and enables greater discriminative representation. First, each micro-expression sample undergoes IP-DEI to allow the features of all samples to be displayed in the form of a quaternion matrix ${mathbf{dot Y}}$. Next we find overcomplete dictionary matrix ${mathbf{dot D}}$ and sparse coefficient matrix ${mathbf{dot X}}$ such that ${mathbf{dot Y}} = {mathbf{dot Ddot X}}$ in ideal scenarios, and consider ${mathbf{dot X}}$ to be the features contained within the micro-expression samples. Finally, we apply our method to the SMIC, CAMSE I and CAMSE II micro-expression databases while using SVM as classifier. The results of the experiment demonstrate that our method outperformed the currently most advanced methods in terms of micro-expression recognition accuracy.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129774624","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: 1

POLANCO: Enforcing Natural Language Network Policies 执行自然语言网络策略

2020 29th International Conference on Computer Communications and Networks (ICCCN) Pub Date : 2020-08-01 DOI: 10.1109/ICCCN49398.2020.9209748

P. Rivera, Zongming Fei, J. Griffioen

{"title":"POLANCO: Enforcing Natural Language Network Policies","authors":"P. Rivera, Zongming Fei, J. Griffioen","doi":"10.1109/ICCCN49398.2020.9209748","DOIUrl":"https://doi.org/10.1109/ICCCN49398.2020.9209748","url":null,"abstract":"Network policies govern the use of an institution’s networks, and are usually written in a high-level human-readable natural language. Normally these policies are enforced by low-level, technically detailed network configurations. The translation from network policies into network configurations is a tedious, manual and error-prone process. To address this issue, we propose a new intermediate language called POlicy LANguage for Campus Operations (POLANCO), which is a human-readable network policy definition language intended to approximate natural language. Because POLANCO is a high-level language, the translation from natural language policies to POLANCO is straightforward. Despite being a high-level human readable language, POLANCO can be used to express network policies in a technically precise way so that policies written in POLANCO can be automatically translated into a set of software defined networking (SDN) rules and actions that enforce the policies. Moreover, POLANCO is capable of incorporating information about the current network state, reacting to changes in the network and adjusting SDN rules to ensure network policies continue to be enforced correctly. We present policy examples found on various public university websites and show how they can be written as simplified human-readable statements using POLANCO and how they can be automatically translated into SDN rules that correctly enforce these policies.","PeriodicalId":137835,"journal":{"name":"2020 29th International Conference on Computer Communications and Networks (ICCCN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122030173","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: 1