2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)最新文献_第3页

PhD Forum: Data traffic classification using deep learning models 博士论坛:使用深度学习模型的数据流量分类

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00035

M. M. Raikar

{"title":"PhD Forum: Data traffic classification using deep learning models","authors":"M. M. Raikar","doi":"10.1109/WoWMoM51794.2021.00035","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00035","url":null,"abstract":"The growth in data traffic is exponential with the usage of network applications in mundane activities. The network operators are posed with the challenge of providing Quality of Experience (QoE) to the deluge of internet users. Network traffic classification plays a significant role in network resource management with prominent security, billing, and accounting applications. In this paper, the network data traffic classification is performed using the Deep Learning (DL) models. The previous data traffic mechanism fails when the scale in data generated is in Exabytes per day from the perspective of the internet user. The network resource management is automated by classification of the traffic without intervening by the operator. The dataset is collected from the campus network for different applications.The network traffic classification is performed using the AlexNet, ResNet, and GoogLeNet DL models. The accuracy obtained for ResNet is 95%, AlexNet is 75%, and GoogLeNet is 91%. The challenge in network traffic classification is converting the packet capture files to the data type requirements of the Convolution Neural Networks (CNN) as an image. The four different network applications are considered for traffic classification. In the next-generation network architecture, artificial intelligence will be an integral part. It reduces the human intervention in traffic characterization and analysis, which aids in meeting the QoE requirements of the users.","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121491953","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: 2

WIP: An Onion-Based Routing Protocol Strengthening Anonymity WIP:一种基于洋葱的增强匿名性的路由协议

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00041

F. Buccafurri, V. D. Angelis, Maria Francesca Idone, Cecilia Labrini

引用次数: 3

DeepMTL: Deep Learning Based Multiple Transmitter Localization DeepMTL:基于深度学习的多发射机定位

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00017

Caitao Zhan, Mohammad Ghaderibaneh, Pranjal Sahu, Himanshu Gupta

{"title":"DeepMTL: Deep Learning Based Multiple Transmitter Localization","authors":"Caitao Zhan, Mohammad Ghaderibaneh, Pranjal Sahu, Himanshu Gupta","doi":"10.1109/WoWMoM51794.2021.00017","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00017","url":null,"abstract":"In this paper, we address the problem of Multiple Transmitters Localization (MTL), i.e., to determine the locations of potential multiple transmitters in a field, based on readings from a distributed set of sensors. In contrast to the widely studied single transmitter localization problem, the MTL problem has only been studied recently in a few works. MTL problem is of great significance in many applications wherein intruders may be present. E.g., in shared spectrum systems, detection of unauthorized transmitters is imperative to efficient utilization of the shared spectrum.In this paper, we present DeepMTL, a novel deep-learning approach to address the MTL problem. In particular, we frame MTL as a sequence of two steps, each of which is a computer vision problem: image-to-image translation and object detection. The first step of image-to-image translation essentially maps an input image representing sensor readings to an image representing distribution of transmitter locations, and the second object detection step derives precise locations of transmitters from the image of transmitter distributions. For the first step, we design our learning model sen2peak, while for the second step, we customize a state-of-the-art object detection model YOLOv3-cust. We demonstrate the effectiveness of our approach via extensive large-scale simulations, and show that our approach outperforms the previous approaches significantly (by 50% or more) in accuracy performance metrics, and incurs an order of magnitude less latency compared to other prior works.","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122433740","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: 14

Feasibility of Multipath Construction in mmWave Backhaul 毫米波回程中多径建设的可行性

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00021

Yan Yan, Qiang Hu, D. Blough

{"title":"Feasibility of Multipath Construction in mmWave Backhaul","authors":"Yan Yan, Qiang Hu, D. Blough","doi":"10.1109/WoWMoM51794.2021.00021","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00021","url":null,"abstract":"This paper focuses on the problem of finding multiple paths with relay nodes to maximize throughput for ultra-high-rate millimeter wave (mmWave) backhaul networks in urban environments. Relays are selected between a pair of source and destination base stations to form multiple interference-free paths. We first formulate the problem of feasibility of multi-path construction as a constraint satisfaction problem that includes constraints on intra-path and inter-path interference and several other constraints that arise from the problem setting. Based on the derived equations, we transform the multiple paths construction problem into a Boolean satisfiability problem. This problem can then be solved through use of a satisfiability (SAT) solver, which however results in a very high running time for realistic problem sizes. To address this, we propose a heuristic algorithm that runs in a fraction of the time of the SAT solver and finds multiple interference-free paths using a modification of a maximum flow algorithm. Simulation results based on 3-D models of a section of downtown Atlanta show that the heuristic algorithm finds multiple paths in almost all the feasible cases (those where the SAT solver succeeds in finding a solution) and produces paths with higher average throughput than the SAT solver. Furthermore, the heuristic increases throughput by 50-100% in typical cases compared to a single-path solution.","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285723","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: 2

A Novel Method for Analyzing Weather Effect on Smart City Traffic 一种分析天气对智慧城市交通影响的新方法

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00061

A. Nasser, V. Simon

引用次数: 6

Multi-Agent Navigation of a Multi-Storey Parking Garage via Game Theory 基于博弈论的多层停车场多智能体导航

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00052

Elvina Gindullina, Sebastian Mortag, M. Dudin, L. Badia

引用次数: 4

Serving HTC and Critical MTC in a RAN Slice 在RAN切片中提供HTC和临界MTC

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00032

V. Mancuso, P. Castagno, M. Sereno, M. Marsan

{"title":"Serving HTC and Critical MTC in a RAN Slice","authors":"V. Mancuso, P. Castagno, M. Sereno, M. Marsan","doi":"10.1109/WoWMoM51794.2021.00032","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00032","url":null,"abstract":"We consider a slice of a radio access network where human and machine users access services with either high throughput or low latency requirements. The slice offers both eMBB and URLLC service categories to serve HTC (Human-Type Communication) and MTC (Machine-Type Communication) traffic. We propose to use eMBB for both HTC and MTC, transferring machine traffic to URLLC only when eMBB is not able to meet the low latency requirements of MTC. We show that by so doing the slice is capable of providing very good performance to about one hundred MTC users under high HTC traffic conditions. Instead, running time-critical MTC over only eMBB is not doable at all, whereas using URLLC suffices for at most a few tens of devices. Therefore, our approach improves the number of users served by the slice by one order of magnitude, without requiring extra resources or compromising performance. To study system performance we develop a novel analytical model of uplink packet transmissions, which covers both legacy eMBB-or URLLC-based MTC, as well as our compound approach. Our model allows to tune slice parameters so as to achieve the desired balance between HTC and MTC service guarantees. We validate the model against detailed simulations using as an example an autonomous driving scenario.","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115544926","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: 2

WIP: Preliminary Evaluation of Digital Twins on MEC Software Architecture WIP:数字孪生对MEC软件架构的初步评价

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00047

Marco Picone, S. Mariani, M. Mamei, F. Zambonelli, Mirko Berlier

引用次数: 5

WIP: Demand-Driven Power Allocation in Wireless Networks with Deep Q-Learning 基于深度q -学习的无线网络中需求驱动的功率分配

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00045

A. Giannopoulos, S. Spantideas, N. Capsalis, P. Gkonis, Panos Karkazis, L. Sarakis, P. Trakadas, C. Capsalis

{"title":"WIP: Demand-Driven Power Allocation in Wireless Networks with Deep Q-Learning","authors":"A. Giannopoulos, S. Spantideas, N. Capsalis, P. Gkonis, Panos Karkazis, L. Sarakis, P. Trakadas, C. Capsalis","doi":"10.1109/WoWMoM51794.2021.00045","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00045","url":null,"abstract":"Power allocation is strongly related to the coverage and capacity of wireless networks, playing a critical role in the development of 5G networks. This paper proposes a Demand-Driven Power Allocation (DDPA) algorithm aiming to fulfill the requested throughput of individual users and accommodate their needs. DDPA is based on model-free Deep Reinforcement Learning (DRL) approaches and has the ability to proactively adjust the power levels of network transmitters. The performance of the developed algorithm is evaluated for a variety of simulation parameters and variable user demands. According to the presented results, the DDPA scheme exhibits a near-optimal performance for up to 50 users in the network area (i.e. satisfaction percentage exceeds 95%), with each one requesting 1 Mbps. Moreover, performance comparison between DDPA and two typical baseline methods reveals that the former results into enhanced total allocated throughput solutions (i.e. a performance increase by a factor of approximately 9% against baseline methods).","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122172127","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: 8

WIP: An Open-Source Tool for Evaluating System-Level Performance of NB-IoT Non-Terrestrial Networks WIP:用于评估NB-IoT非地面网络系统级性能的开源工具

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) Pub Date : 2021-06-01 DOI: 10.1109/WoWMoM51794.2021.00042

A. Petrosino, Giancarlo Sciddurlo, Sergio Martiradonna, D. Striccoli, G. Piro, G. Boggia

{"title":"WIP: An Open-Source Tool for Evaluating System-Level Performance of NB-IoT Non-Terrestrial Networks","authors":"A. Petrosino, Giancarlo Sciddurlo, Sergio Martiradonna, D. Striccoli, G. Piro, G. Boggia","doi":"10.1109/WoWMoM51794.2021.00042","DOIUrl":"https://doi.org/10.1109/WoWMoM51794.2021.00042","url":null,"abstract":"Satellite Communication is expected to play a leading role in 5G & Beyond networks. Current studies, however, focus the attention on physical and link-level aspects, while ignoring to evaluate system-level performance. This paper presents a novel simulation tool, conceived as a new module for the open-source 5G-air-simulator, modeling NB-IoT satellite-based communication systems. Specifically, it implements several link-to-system abstraction models, the cell selection procedure, and a configurable satellite constellation. Furthermore, these essential features are successfully integrated within the rest of the 5G-air-simulator, thus offering the opportunity to test flexible network deployments (e.g., by varying the number and the distribution of users) under different application statistics. To demonstrate the actual effectiveness of the developed tool, this work also presents a preliminary performance assessment of an NB-IoT satellite-based communication system enabling reference monitoring scenarios.","PeriodicalId":131571,"journal":{"name":"2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129830634","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