2021 17th International Conference on Network and Service Management (CNSM)最新文献_第3页

Artificial intelligence and big data driven IS security management solution with applications in higher education organizations 人工智能和大数据驱动的IS安全管理解决方案及其在高等教育机构的应用

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615575

Vladislavs Minkevics, Jānis Kampars

{"title":"Artificial intelligence and big data driven IS security management solution with applications in higher education organizations","authors":"Vladislavs Minkevics, Jānis Kampars","doi":"10.23919/CNSM52442.2021.9615575","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615575","url":null,"abstract":"This paper presents the architecture of a modular big-data-based information system (IS) security management system (ISMS) and elaborates one of its modules - artificial intelligence driven NetFlow data analysis (NFAI) module. The ISMS is used in production at Riga Technical University and can be adapted for use in other organizations. The proposed platform is based on mostly free and open-source tools and allows to prevent or minimize the consequences of malware's activity with little impact on the employee's privacy. The presented NFAI detection module provides detection of malware activity by extracting features from NetFlow data within a 10-minute interval and feeding it into several trained classifiers. ISMS does not rely solely on NFAI module alone, it uses an ensemble of modules and algorithms to increase the accuracy of the malware detection. The presented IS security management system can be employed in real-time environment and its NFAI detection module allows to identify an infected device as soon as it starts to communicate with the botnet (a logical collection of Internet-connected devices such as computers, smartphones or IoT devices whose security have been breached and control ceded to a third party) command and control centre to obtain new commands. The presented NFAI module has been validated in the production environment and identified infected devices which were not detected by antivirus software nor by firewall or Intrusion Detection System.","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123434031","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

Obstacle-Aware and Energy-Efficient Multi-Drone Coordination and Networking for Disaster Response 面向灾害响应的障碍物感知和节能多无人机协调与网络

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615574

Chengyi Qu, Rounak Singh, Alicia Esquivel Morel, Francesco Betti Sorbelli, P. Calyam, Sajal K. Das

{"title":"Obstacle-Aware and Energy-Efficient Multi-Drone Coordination and Networking for Disaster Response","authors":"Chengyi Qu, Rounak Singh, Alicia Esquivel Morel, Francesco Betti Sorbelli, P. Calyam, Sajal K. Das","doi":"10.23919/CNSM52442.2021.9615574","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615574","url":null,"abstract":"Unmanned aerial vehicles or drones provide new capabilities for disaster response management (DRM). In a DRM scenario, multiple heterogeneous drones collaboratively work together forming a flying ad-hoc network (FANET) instantiated by a ground control station. However, FANET air-to-air and air-to-ground links that serve critical application expectations can be impacted by: (i) environmental obstacles, and (ii) limited battery capacities. In this paper, we present a novel obstacle-aware and energy-efficient multi-drone coordination and networking scheme that features a Reinforcement Learning (RL) based location prediction algorithm coupled with a packet forwarding algorithm for drone-to-ground network establishment. We specifically present two novel drone location-based solutions (i.e., heuristic greedy, and learning-based) in our packet forwarding approach to support heterogeneous drone operation as per application requirements. These requirements involve improving connectivity (i.e., optimize packet delivery ratio and end-to-end delay) despite environmental obstacles, and improving efficiency (i.e., by lower energy use and time consumption) despite energy constraints. We evaluate our scheme by comparing it with state-of-the-art networking algorithms in a trace-based DRM FANET simulation testbed. Results show that our strategy overcomes obstacles and can achieve between 81-90% of network connectivity performance observed under no obstacle conditions. With obstacles, our scheme improves network connectivity performance by 14-38 % while also providing 23-54% of energy savings.","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124944159","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

HolistIX: a zero-touch approach for IXPs HolistIX:面向ixp的零接触方法

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615540

Christoff Visser, S. Yamamoto, Tomine Takashi, Y. Sekiya, M. Bruyère

引用次数: 1

Self Optimizing Network Slicing in 5G for Slice Isolation and High Availability 5G自优化网络切片，实现切片隔离和高可用性

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615546

Shwetha Vittal, A. Franklin

{"title":"Self Optimizing Network Slicing in 5G for Slice Isolation and High Availability","authors":"Shwetha Vittal, A. Franklin","doi":"10.23919/CNSM52442.2021.9615546","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615546","url":null,"abstract":"5G network supports end-to-end logically isolated networks in the form of network slices, catering to the needs of users of various primary network services, namely enhanced Mobile Broadband (eMBB), ultra Reliable Low Latency Communications (uRLLC), and massive Machine Type Communication (mMTC). Mobile Virtual Network Operators (MVNO)s often face challenges in achieving strong slice isolation and High Availability per slice during overload and scaling situations as the 5G network uses a shared environment for slices with multiple domains, especially considering a variety of services and devices. In this paper, we propose a novel Self Optimizing Network Slicing framework (SONS) leveraging Self Organizing Network by building it as an autonomous slice system in 5G network slicing management for efficient slice sharing and isolation. Precisely, we formulate a system model with Probabilistic Graphical Model (PGM) based Markov Network, building it as an Artificial Intelligence based learning framework. We propose Slice Belief Propagation based algorithms and Deep Learning based Long Short Term Memory (LSTM) methods to aid in serving user requests and reconfiguration of self optimizing slice. Our experiments on the proposed SONS framework shows improvement in serving higher number of users with uninterrupted connectivity by 80% in eMBB, 35% in uRLLC, and 52% in mMTC when compared to standard slice deployments, while handling the worst case of peak traffic in the control plane of 5G Core network.","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131305374","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: 7

Proactive Live Migration for Virtual Network Functions using Machine Learning 利用机器学习实现虚拟网络功能的主动实时迁移

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615564

Seyeon Jeong, N. V. Tu, Jae-Hyoung Yoo, J. W. Hong

{"title":"Proactive Live Migration for Virtual Network Functions using Machine Learning","authors":"Seyeon Jeong, N. V. Tu, Jae-Hyoung Yoo, J. W. Hong","doi":"10.23919/CNSM52442.2021.9615564","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615564","url":null,"abstract":"VM (Virtual Machine) live migration is a server virtualization technique for deploying a running VM to another server node while minimizing downtime of service the VM provides. Currently, in cloud data centers, VM live migration is widely used to apply load balancing on CPU workload and network traffic, to reduce electricity consumption, and to provide uninterrupted service during the maintenance of hardware and software updates on servers. It is critical to use VM live migration as a prevention or mitigation measure for possible failure when its indications are detected or predicted. Especially in NFV (Network Function Virtualization) environment, timely use of VNF (Virtual Network Function) live migration can maintain system availability and reduce operator's loss due to service failure. In this paper, we propose a proactive live migration method for vEPC (Virtual Evolved Packet Core) based on failure prediction. A machine learning model learns periodic monitoring data of resource usage and logs from servers and VMs/VNFs to predict future vEPC paging failure probability. We implemented the proposed method in OpenStack-based NFV environment to evaluate the real service performance gains for open source vEPC implementations.","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130647324","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

Novel HTTPS classifier driven by packet bursts, flows, and machine learning 新的HTTPS分类器由数据包爆发，流和机器学习驱动

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615561

Zdena Tropková, Karel Hynek, T. Čejka

引用次数: 5

IEEE 802.11ah (HaLow) Dongle for Simplified IoT Wireless Networking 用于简化物联网无线网络的IEEE 802.11ah (HaLow)加密狗

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615571

Min-Cheol Kim, Young-Tak Kim

引用次数: 0

A Greedy Algorithm for Minimum Cut into Bounded Sets Problem 最小分割有界集问题的贪心算法

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615583

O. Ugurlu, V. Akram, D. Eliiyi

引用次数: 0

Cost-Efficient Dynamic Service Function Chain Embedding in Edge Clouds 边缘云中具有成本效益的动态业务功能链嵌入

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615590

Weihan Chen, Zhiliang Wang, Han Zhang, Xia Yin, Xingang Shi

{"title":"Cost-Efficient Dynamic Service Function Chain Embedding in Edge Clouds","authors":"Weihan Chen, Zhiliang Wang, Han Zhang, Xia Yin, Xingang Shi","doi":"10.23919/CNSM52442.2021.9615590","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615590","url":null,"abstract":"Edge Computing (EC) provides delay protection for some delay-sensitive network services by deploying cloud infrastructure with limited resources at the edge of the network. In addition, Network Function Virtualization (NFV) implements network functions by replacing traditional dedicated hardware devices with Virtual Network Function (VNF) that can run on general servers. In NFV environment, Service Function Chaining (SFC) is regarded as a promising way to reduce the cost of configuring network services. NFV therefore allows to deploy network functions in a more flexible and cost-efficient manner, and schedule network resources according to the dynamical variation of network traffic in EC. For service providers, seeking an optimal SFC embedding scheme can improve service performance and reduce embedding cost. In this paper, we study the problem of how to dynamically embed SFC in geo-distributed edge clouds network to serve user requests with different delay requirements, and formulate this problem as a Mixed Integer Linear Programming (MILP) which aims to minimize the total embedding cost. Furthermore, a novel SFC Cost-Efficient emBedding (SFC-CEB) algorithm has been proposed to efficiently embed required SFC and optimize the embedding cost. Based on the results of trace-driven simulations, the proposed algorithm can reduce SFC embedding cost by up to 37% compared with state-of-the-art schemes (e.g., RDIP).","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128609669","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

Max-Min Fair Bandwidth Allocation in Millimeter-Wave Radio Clusters 毫米波无线电集群中最大最小公平带宽分配

2021 17th International Conference on Network and Service Management (CNSM) Pub Date : 2021-10-25 DOI: 10.23919/CNSM52442.2021.9615530

Idil Zeynep Alemdar, E. Onur

{"title":"Max-Min Fair Bandwidth Allocation in Millimeter-Wave Radio Clusters","authors":"Idil Zeynep Alemdar, E. Onur","doi":"10.23919/CNSM52442.2021.9615530","DOIUrl":"https://doi.org/10.23919/CNSM52442.2021.9615530","url":null,"abstract":"Enabling ultra high speed wireless communication, Extreme High Frequency (EHF) or Millimeter Wave (mmWave) bands will play a significant role for the 5G. Apart from speed, 5G will be very useful for handling great amounts of data simultaneously and serving bandwidth hungry applications as well. Ultra high quality and ultra fast video streaming will be one of those applications that will be made possible by 5G. While serving bandwidth hungry applications with ease will be an important development and maximizing throughput is most of the time the main goal in a network, it is also important to make sure that no other application starves. In order to prevent such a situation, fair bandwidth allocation should be considered in wireless communications. We simulated a max-min fair bandwidth allocation scenario in a mmWave radio cluster, where a radio cluster is a set of base stations connected to a main hub over 60 GHz radio links. We ran experiments with different path loss exponent values with increasing number of base stations to examine the effects of topology complexity and radio signal loss on the optimization time and on the overall network throughput while maintaining max-min fair allocation. The results showed that as the topology becomes more complex, the problem takes longer to solve. However, the overall network throughput increases. In addition, our model has achieved a decent quantitative fairness level as shown by Jain's index values, which are always more than 0.5 on a scale of 0 to 1 with respect to the topology complexity and the number users.","PeriodicalId":358223,"journal":{"name":"2021 17th International Conference on Network and Service Management (CNSM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114215788","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