2020 16th International Conference on Mobility, Sensing and Networking (MSN)最新文献

{"title":"A Study on MQTT Node Selection","authors":"F. Chen, Yujia Huo, Kun Liu, Wenying Tang, Jian-ming Zhu, Zhiyuan Sui","doi":"10.1109/MSN50589.2020.00101","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00101","url":null,"abstract":"The Internet of Things (IOT) is an Internet-based network that covers everything. Message Queuing Telemetry Transport (MQTT) is one of the commonly used communication protocols for any platform in the Internet of Things. Whether it is from the perspective of overall security or device compatibility and resource consumption, the MQTT protocol has certain advantages and is the most competitive communication protocol in the current Internet of Things. However, the user password login form adopted by the MQTT protocol has a certain degree of security problems. IOTA is an encrypted currency, and the Tangle network it uses is a new distributed structure. Based on this situation, this article innovatively combines the Tangle network with the MQTT protocol, and proposes a new communication option for MQTT nodes. When a new node enters the network, start from the Broker with the help of a “walker”, by judging the connection and survival of the node, using the Markov Chain Monte Carlo (MCMC) random walk algorithm to complete the node selection, and finally realize MQTT Communication between nodes. This article puts forward the design idea of this scheme, and realizes the scheme through simulation experiment.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130610795","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 Privacy-preserving and Collusion-resisting Top-k Query Processing in WSNs","authors":"Jianguo Zhou, Hua Dai, Jie Zhu, Rongqi Qi, Geng Yang, Jian Xu","doi":"10.1109/MSN50589.2020.00113","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00113","url":null,"abstract":"In the wireless sensor networks, it is a challenging issue to protect the data privacy from curious users while providing top-k query services. In this paper, a novel privacy-preserving and collusion-resisting top-k query processing interactive protocol is proposed for WSNs. To the best of our knowledge, it is the first work providing the privacy preservation and collusion resistance simultaneously in top-k query processing in WSNs. Data encryption with different private keys, the bloom filter and HMAC are adopted to achieve data privacy preservation even there are a few sensors colluding with the adversaries. During the interactive procedures of the query processing, two rounds of secure interactions between the sink and sensors are performed to obtain the query results. The protocol analysis indicates that the protocol can preserve data privacy even a few sensors collude with the adversaries, while the experiment result shows that the proposed protocol has good performance on network communication cost.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131104553","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":"Federated Deep Payload Classification for Industrial Internet with Cloud-Edge Architecture","authors":"Peng Zhou","doi":"10.1109/MSN50589.2020.00048","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00048","url":null,"abstract":"Payload classification is a kind of powerful deep packet inspection model built on the raw payloads of network traffic, and hence can remove the need of any configuration assumptions for network management and intrusion detection. While in the emerging industrial Internet, a majority of local industry owners are not willing to share their private payloads that possibly contain sensitive information and thus cause the classification model not always well trained due to the lack of sufficient training samples. In this paper, we address this privacy concern and propose a federated learning model for industrial payload classification. In particular, we consider a cloud-edge architecture for the industrial Internet topology, and assemble federated learning process by cloud-edge collaboration: each data owner has his own edge server for learning a local classification model and the industrial cloud takes the responsibility for aggregating local models to a federated one. We adopt a gradient-based deep convolutional neural network model as our local classifier and use the method of weighted gradient averaging for model aggregation. By this way, the data owners can avoid to disclose their private payload for model training, but instead share their local model’s gradients to keep the federated model able to learn local samples indirectly. At the end, we have conducted a large set of experiments with real-world industrial Internet traffic datasets, and have successfully confirmed the effectiveness of the proposed federated model for payload classification with privacy-preserved.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133159380","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":"Jointly Video Bitrate Adaptation and Multicast Resource Allocation in Mobile Edge Networks","authors":"Simin Li, Xiaobin Tan, Shunyi Wang, Jian Yang, Quan Zheng","doi":"10.1109/MSN50589.2020.00051","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00051","url":null,"abstract":"Current schemes for Dynamic Adaptive Streaming over HTTP (DASH) are mainly client-driven. Thus, in the scenario of multiple users watching the same video, repeated subscription and data transmission results in an under-utilization of network bandwidth resources. Additionally, competition for limited network resources of individual users may motivate selfish behaviors, which leads to unfairness and sub-optimal utility of video services. In this paper, Multimedia Broadcast Multicast Service (MBMS) in mobile edge networks for multi-bitrate video sessions is applied to overcome these limitations. We formulate a non-linear integer programming (NLIP) model, which jointly optimize bitrate adaptation and resource allocation for multiple users. This model takes video quality, playback interruptions, and quality oscillations as linear constraints to maximize multicast users’ Quality of Experience (QoE). Due to NP-Hardness of this problem, we propose a heuristic greedy algorithm, which can work out the optimal or near-optimal solution with low time complexity. The evaluation results demonstrate that our method can achieve Pareto Optimality of the system utility, and maximize users’ QoE while ensuring fairness.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115285258","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":"5G B5G 2020 Workshop","authors":"","doi":"10.1109/msn50589.2020.00009","DOIUrl":"https://doi.org/10.1109/msn50589.2020.00009","url":null,"abstract":"","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"157 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120942239","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":"Optimizing functional split of baseband processing on TWDM-PON based fronthaul network","authors":"G. Hasegawa, M. Murata, Y. Nakahira, M. Kashima, S. Ata","doi":"10.1109/MSN50589.2020.00061","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00061","url":null,"abstract":"One of the major shortcomings of Centralized Radio Access Networks (C-RAN) is that the large capacity is required for fronthaul network between Remote Radio Heads (RRHs) and central office with baseband unit (BBU) pool. Possible solutions are to introduce lower-cost networking technology for fronthaul network, such as Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON), and to introduce functional split, that moves some baseband processing functions to cell site to decrease the utilization of the fronthaul network. In this paper, we construct the mathematical model for selecting function split options of baseband processing to minimize the power consumption of TWDM-PON based fronthaul network. In detail, we formulate the optimization problem for minimizing the total power consumption of fronthaul network in terms of the capacity of TWDM-PON, the number of RRHs in each cell site, server resources, latency constraints, the amount of traffic from each RRH, physical/virtual server power consumption characteristics. Numerical examples are shown for confirming the correctness of the proposed model and for presenting the effect of resource enhancement methods on the capacity and energy efficiency of the system.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123410588","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":"Training Machine Learning Models Through Preserved Decentralization","authors":"G. A. Kusi, Qi Xia, Christian Nii Aflah Cobblah, Jianbin Gao, Hu Xia","doi":"10.1109/MSN50589.2020.00080","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00080","url":null,"abstract":"In the era of big data, fast and effective machine learning algorithms are urgently required for large-scale data analysis. Data is usually created from several parts and stored in a geographically distributed manner, which has stimulated research in the field of distributed machine learning. The traditional master-level distributed learning algorithm involves the use of a trusted central server and focuses on the online privacy model. On the contrary, the specific linear learning model and security issues are not well understood in this column. We built a decentralized advanced-Proof-of-Work (aPoW) algorithm specifically for learning a general predictive model over the blockchain. In aPoW, we establish the data privacy of the differential privacy based schemes to protect each party and propose a secure domain against potential Byzantine attacks at a reduced rate. We explored a technical module in newsprint to consider a universal learning model (linear or non-linear) to provide a secure, confidential decentralized machine learning system called deepLearning Chain. Finally, we introduce deepLearning Chain on blockchain through comprehensive experiments, demonstrate its performance and effectiveness.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126356797","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":"Efficient Distributed Training in Heterogeneous Mobile Networks with Active Sampling","authors":"Yunhui Guo, Xiaofan Yu, Kamalika Chaudhuri, T. Simunic","doi":"10.1109/MSN50589.2020.00041","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00041","url":null,"abstract":"Mobile edge computing is an emerging research topic which aims at pushing the computation from the cloud to the edge devices. Most of the current machine learning (ML) algorithms, such as federated learning, are designed for homogeneous mobile networks, that is, all the devices collect the same type of data. In this paper, we address distributed training of ML algorithms in heterogeneous mobile networks where the features, rather than the samples, are distributed across multiple heterogeneous mobile devices. Training ML models in heterogeneous mobile networks incurs a large communication cost due to the necessity to deliver the local data to a central server. Inspired by active learning, which is traditionally used to reduce the labeling cost for training ML models, we propose an active sampling method to reduce the communication cost of learning in heterogeneous mobile networks. Instead of sending all the local data, the proposed active sampling method identifies and sends only informative data from each device to the central server. Extensive experiments on four real datasets, both with numerical simulation and on a networked mobile system, show that the proposed method can reduce the communication cost by up to 53% and energy consumption by up to 67% without accuracy degradation compared with the conventional approaches.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"11 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127464700","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 Priority Task Scheduling Algorithm based on Residual Energy in EH-WSNs","authors":"Wuyungerile Li, Hao Gao, Yingcong Liu, Bing Jia, Baoqi Huang","doi":"10.1109/MSN50589.2020.00023","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00023","url":null,"abstract":"Energy Harvesting Wireless Sensor Networks (EHWSNs) have been widely studied in recent years. In solar charged EH-WSNs, the Sun illumination changes with the changes of environment, in consequence the collected energy of the sensor node is unstable, especially in rainy day, windy day or the angle of the solar panel changes. Therefore, the reasonable assignment of energy in EH-WSNs becomes critical important. In This paper, based on the solar energy charateristics, we propose a priority task scheduling algorithm that suitable for EH-WSNs, that is, the transmission method and order of collected data are determined according to task priority and the remaining energy of the node. The simulation results show that the priority task scheduling algorithm guarantees the fairness of node energy distribution, the timeliness of sending urgent tasks and the high processing rate of common tasks when the energy provided by the environment is small.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114434117","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":"COPSS-lite: A Lightweight ICN based Pub/Sub System for IoT Environments","authors":"S. S. Adhatarao, Haitao Wang, M. Arumaithurai, Xiaoming Fu","doi":"10.1109/MSN50589.2020.00034","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00034","url":null,"abstract":"Content Centric Networking (CCN) and Named Data Networking (NDN) are popular ICN proposals that are widely accepted in the ICN community; however, they do not provide an efficient pub/sub mechanism. Hence, a content oriented pub/sub system named COPSS was developed to enhance the CCN/NDN protocols with efficient pub/sub capabilities. Internet houses powerful devices like routers and servers that can operate with the full-fledged implementation of such ICN protocols. However, Internet of Things (IoT) has become a growing topic of interest in recent years with billions of resource constrained devices expected to connect to the Internet in the near future. The current design to support IoT relies mainly on IP which has limited address space and hence cannot accommodate the increasing number of devices. Even though, IPv6 provides a large address space, IoT devices operate with constrained resources and hence, IPv6 protocol and its headers will induce additional overhead for their operation. Interestingly, we observed that IoTs are information centric in nature and therefore, ICN could be the more suitable candidate to support IoT environments. Although NDN and COPSS are designed for the Internet, their current full fledged implementations cannot be used by the resource constrained IoT devices. Therefore, CCN-lite was designed to provide a light weight, inter-operable version of the CCNx protocol to support the IoT devices. However, we show that communication in the IoT networks resemble pub/sub communication paradigm. However, CCN-lite like its ancestors (CCN/NDN) lacks the support for an efficient pub/sub mechanism while COPSS cannot be directly applied to the constrained IoT networks. Therefore, in this work, we develop COPSS-lite, an efficient and light weight implementation of pub/sub along with multi-hop routing to support the IoT networks. Essentially, COPSS-lite enhances CCN-lite with pub/sub capability with minimal overhead and further enables multi-hop connections by incorporating the famous RPL protocol for low power and lossy networks. Through evaluation using the real world sensor devices from the IoT Lab, we demonstrate the benefits of COPSS-lite in comparison with stand alone CCN-lite. Our results show that COPSS-lite is compact, operates on all platforms that support CCN-lite and significantly improves the performance of constrained devices in the IoT environments.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126454854","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}