Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175399
Trond Vatten
The deployment of 5G networks has brought significant advancements in mobile communication, enabling novel applications and services with diverse requirements. Network slicing, a crucial technology for realizing 5G’s full potential, allows operators to create multiple, logically separate networks on a shared physical infrastructure. However, ensuring the resilience and survivability of network slices during network failures is a crucial challenge that needs to be addressed, particularly for critical infrastructure services. This paper presents an ongoing research project investigating the survivability of network-sliced 5G systems during network failures, focusing on the ClusPR framework for service chaining and resource allocation.The study aims to: 1) develop a framework for assessing the survivability of network-sliced 5G systems during and after failures; 2) explore factors influencing the resilience of various slicing approaches in challenging events; and 3) apply findings to design resilient 5G networks and develop strategies for handling undesired events. As the project advances, the expected results will provide valuable insights and heuristics into proactive and reactive strategies for maintaining the continuous operation of critical services in 5G networks during network outages.
{"title":"Investigating 5G Network Slicing Resilience through Survivability Modeling","authors":"Trond Vatten","doi":"10.1109/NetSoft57336.2023.10175399","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175399","url":null,"abstract":"The deployment of 5G networks has brought significant advancements in mobile communication, enabling novel applications and services with diverse requirements. Network slicing, a crucial technology for realizing 5G’s full potential, allows operators to create multiple, logically separate networks on a shared physical infrastructure. However, ensuring the resilience and survivability of network slices during network failures is a crucial challenge that needs to be addressed, particularly for critical infrastructure services. This paper presents an ongoing research project investigating the survivability of network-sliced 5G systems during network failures, focusing on the ClusPR framework for service chaining and resource allocation.The study aims to: 1) develop a framework for assessing the survivability of network-sliced 5G systems during and after failures; 2) explore factors influencing the resilience of various slicing approaches in challenging events; and 3) apply findings to design resilient 5G networks and develop strategies for handling undesired events. As the project advances, the expected results will provide valuable insights and heuristics into proactive and reactive strategies for maintaining the continuous operation of critical services in 5G networks during network outages.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130830092","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175436
Wafik Zahwa, Abdelkader Lahmadi, M. Rusinowitch, Mondher Ayadi
Automatically deploying distributed Access Control Lists (ACLs) in a software-defined network can ensure their internal services and hosts connectivity, security and reliability. ACLs are often deployed in a switch using Ternary ContentAddressable Memory (TCAM). Since TCAM memory is often too limited to store a large ACL, one has to split the lists and distribute the parts on several switches in such a way that every packet travelling from a source to a destination undergoes the required match-action rules. In this paper, we develop and compare three algorithms based on graph theory and Reinforcement Learning (RL) techniques to automatically distribute ACLs across networks switches, while minimizing their TCAM memory occupancy. We compare the three algorithms on several network topologies to evaluate their efficiency in terms of memory occupancy.
{"title":"Automated Placement of In-Network ACL Rules","authors":"Wafik Zahwa, Abdelkader Lahmadi, M. Rusinowitch, Mondher Ayadi","doi":"10.1109/NetSoft57336.2023.10175436","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175436","url":null,"abstract":"Automatically deploying distributed Access Control Lists (ACLs) in a software-defined network can ensure their internal services and hosts connectivity, security and reliability. ACLs are often deployed in a switch using Ternary ContentAddressable Memory (TCAM). Since TCAM memory is often too limited to store a large ACL, one has to split the lists and distribute the parts on several switches in such a way that every packet travelling from a source to a destination undergoes the required match-action rules. In this paper, we develop and compare three algorithms based on graph theory and Reinforcement Learning (RL) techniques to automatically distribute ACLs across networks switches, while minimizing their TCAM memory occupancy. We compare the three algorithms on several network topologies to evaluate their efficiency in terms of memory occupancy.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131015152","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175438
Mohamed-Anis Mekki, B. Brik, A. Ksentini, C. Verikoukis
Fine-granular management of cloud-native computing resources is one of the key features sought by cloud and edge operators. It consists in giving the exact amount of computing resources needed by a microservice to avoid resource over-provisioning, which is, by default, the adopted solution to prevent service degradation. Fine-granular resource management guarantees better computing resource usage, which is critical to reducing energy consumption and resource wastage (vital in edge computing). In this paper, we propose a novel Zero-touch management (ZSM) framework featuring a fine-granular computing resource scaler in a cloud-native environment. The proposed scaler algorithm uses Artificial Intelligence (AI)/Machine Learning (ML) models to predict microservice performances; if a service degradation is detected, then a root-cause analysis is conducted using eXplainable AI (XAI). Based on the XAI output, the proposed framework scales only the needed (exact amount) resources (i.e., CPU or memory) to overcome the service degradation. The proposed framework and resource scheduler have been implemented on top of a cloud-native platform based on the well-known Kubernetes tool. The obtained results clearly indicate that the proposed scheduler with lesser resources achieves the same service quality as the default scheduler of Kubernetes.
{"title":"XAI-Enabled Fine Granular Vertical Resources Autoscaler","authors":"Mohamed-Anis Mekki, B. Brik, A. Ksentini, C. Verikoukis","doi":"10.1109/NetSoft57336.2023.10175438","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175438","url":null,"abstract":"Fine-granular management of cloud-native computing resources is one of the key features sought by cloud and edge operators. It consists in giving the exact amount of computing resources needed by a microservice to avoid resource over-provisioning, which is, by default, the adopted solution to prevent service degradation. Fine-granular resource management guarantees better computing resource usage, which is critical to reducing energy consumption and resource wastage (vital in edge computing). In this paper, we propose a novel Zero-touch management (ZSM) framework featuring a fine-granular computing resource scaler in a cloud-native environment. The proposed scaler algorithm uses Artificial Intelligence (AI)/Machine Learning (ML) models to predict microservice performances; if a service degradation is detected, then a root-cause analysis is conducted using eXplainable AI (XAI). Based on the XAI output, the proposed framework scales only the needed (exact amount) resources (i.e., CPU or memory) to overcome the service degradation. The proposed framework and resource scheduler have been implemented on top of a cloud-native platform based on the well-known Kubernetes tool. The obtained results clearly indicate that the proposed scheduler with lesser resources achieves the same service quality as the default scheduler of Kubernetes.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122973732","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175457
Movsun Kuy, L. Schumacher, Sokchenda Sreng
Network Function Virtualization (NFV) is a hot topic in computer networking and aims to replace proprietary, hardware-based networking services with virtualized, cloud-based network functions. However, the current implementation of NFV Management and Orchestration (MANO) often relies on either expensive or high-overhead cloud resources, such as AWS and OpenStack, as the NFV infrastructure (NFVI), which may limit research and deployment in edge computing scenarios. To address this issue, our work proposes a cost-effective solution to set up an NFVI suitable for both testbed research and production edge deployment. We suggest using a cluster of Raspberry Pi (RPi) powered by Canonical Metal-as-a-Service (MAAS) as a bare-metal cloud infrastructure to establish an NFVI for Virtual Network Functions (VNF) deployment from Open-Source MANO (OSM).
网络功能虚拟化(Network Function Virtualization, NFV)是计算机网络领域的一个热门话题，旨在用虚拟化的、基于云的网络功能取代专有的、基于硬件的网络服务。然而，目前NFV管理和编排(MANO)的实现通常依赖于昂贵或高开销的云资源，如AWS和OpenStack，作为NFV基础设施(NFVI)，这可能会限制边缘计算场景的研究和部署。为了解决这个问题，我们的工作提出了一个经济有效的解决方案来建立一个NFVI，适用于测试平台研究和生产边缘部署。我们建议使用由Canonical Metal-as-a-Service (MAAS)提供支持的树莓派(RPi)集群作为裸机云基础设施，从开源MANO (OSM)建立虚拟网络功能(VNF)部署的NFVI。
{"title":"Experimental demonstration of NFV deployment with RPi and MAAS","authors":"Movsun Kuy, L. Schumacher, Sokchenda Sreng","doi":"10.1109/NetSoft57336.2023.10175457","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175457","url":null,"abstract":"Network Function Virtualization (NFV) is a hot topic in computer networking and aims to replace proprietary, hardware-based networking services with virtualized, cloud-based network functions. However, the current implementation of NFV Management and Orchestration (MANO) often relies on either expensive or high-overhead cloud resources, such as AWS and OpenStack, as the NFV infrastructure (NFVI), which may limit research and deployment in edge computing scenarios. To address this issue, our work proposes a cost-effective solution to set up an NFVI suitable for both testbed research and production edge deployment. We suggest using a cluster of Raspberry Pi (RPi) powered by Canonical Metal-as-a-Service (MAAS) as a bare-metal cloud infrastructure to establish an NFVI for Virtual Network Functions (VNF) deployment from Open-Source MANO (OSM).","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128612508","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175419
Daniele Bringhenti, R. Sisto, Fulvio Valenza
In the latest years, multi-domain Kubernetes architectures composed of multiple clusters have been getting more frequent, so as to provide higher workload isolation, resource availability flexibility and scalability for application deployment. However, manually configuring their security may lead to inconsistencies among policies defined in different clusters, or it may require knowledge that the administrator of each domain cannot have. Therefore, this paper proposes an automatic approach for the automatic generation of the network security policies to be deployed in each cluster of a multi-domain Kubernetes deployment. The objectives of this approach are to reduce of configuration errors that human administrators commonly make, and to create transparent cross-cluster communications. This approach has been implemented as a framework named Multi-Cluster Orchestrator, which has been validated in realistic use cases to assess its benefits to Kubernetes orchestration.
{"title":"Security automation for multi-cluster orchestration in Kubernetes","authors":"Daniele Bringhenti, R. Sisto, Fulvio Valenza","doi":"10.1109/NetSoft57336.2023.10175419","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175419","url":null,"abstract":"In the latest years, multi-domain Kubernetes architectures composed of multiple clusters have been getting more frequent, so as to provide higher workload isolation, resource availability flexibility and scalability for application deployment. However, manually configuring their security may lead to inconsistencies among policies defined in different clusters, or it may require knowledge that the administrator of each domain cannot have. Therefore, this paper proposes an automatic approach for the automatic generation of the network security policies to be deployed in each cluster of a multi-domain Kubernetes deployment. The objectives of this approach are to reduce of configuration errors that human administrators commonly make, and to create transparent cross-cluster communications. This approach has been implemented as a framework named Multi-Cluster Orchestrator, which has been validated in realistic use cases to assess its benefits to Kubernetes orchestration.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121798386","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175437
J. Vieira, A. L. E. Battisti, E. Macedo, Paulo F. Pires, D. Muchaluat-Saade, Flávia Coimbra Delicato, A. Oliveira
The combination of both Network Function Virtualization (NFV) and Edge Computing facilitates the Quality of Service (QoS) fulfillment of latency-stringent applications by taking advantage of the proximity of the devices at the edge and the user, and provides the necessary flexibility to enable agile, cost-effective, and on-demand service delivery models for 5G environments. However, to achieve those benefits, VNFs must be deployed so that system resource utilization is optimized and service QoS is maintained. In this context, the selection of the most suitable edge nodes to deploy VNFs is a challenging research issue because multiple — and often conflicting — objectives must be considered by the VNF placement algorithm. The challenges become greater when considering the high dynamism of the edge environment. The availability of edge nodes and users’ locations vary over time, making original allocation decisions ineffective. In this paper, we propose DSP, a Dynamic Smart VNF Placement algorithm that considers the dynamic nature of a 5G edge environment. Our proposal focuses on optimizing resource utilization with an online placement approach to handle continuously arriving service requests. Furthermore, we also account for user mobility providing an approach that reduces the performance impact caused by users’ movement. Additionally, a two-level resource-sharing mechanism is provided, minimizing the cost for the infrastructure provider with low impact on QoS.
{"title":"Dynamic and Mobility-Aware VNF Placement in 5G-Edge Computing Environments","authors":"J. Vieira, A. L. E. Battisti, E. Macedo, Paulo F. Pires, D. Muchaluat-Saade, Flávia Coimbra Delicato, A. Oliveira","doi":"10.1109/NetSoft57336.2023.10175437","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175437","url":null,"abstract":"The combination of both Network Function Virtualization (NFV) and Edge Computing facilitates the Quality of Service (QoS) fulfillment of latency-stringent applications by taking advantage of the proximity of the devices at the edge and the user, and provides the necessary flexibility to enable agile, cost-effective, and on-demand service delivery models for 5G environments. However, to achieve those benefits, VNFs must be deployed so that system resource utilization is optimized and service QoS is maintained. In this context, the selection of the most suitable edge nodes to deploy VNFs is a challenging research issue because multiple — and often conflicting — objectives must be considered by the VNF placement algorithm. The challenges become greater when considering the high dynamism of the edge environment. The availability of edge nodes and users’ locations vary over time, making original allocation decisions ineffective. In this paper, we propose DSP, a Dynamic Smart VNF Placement algorithm that considers the dynamic nature of a 5G edge environment. Our proposal focuses on optimizing resource utilization with an online placement approach to handle continuously arriving service requests. Furthermore, we also account for user mobility providing an approach that reduces the performance impact caused by users’ movement. Additionally, a two-level resource-sharing mechanism is provided, minimizing the cost for the infrastructure provider with low impact on QoS.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130684663","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175400
R. Caldelli, P. Castoldi, M. Gharbaoui, B. Martini, M. Matarazzo, F. Sciarrone
Intent-based Networking (IBN) has emerged as an innovative approach to automate the provisioning of network services while abstracting the details of the underlying infrastructure and simplifying the interaction between the users and the network. In this paper, we present an intent-based framework that allows for the deployment of SDN-based and QoS-aware network slices. The main objective of the work is to describe the role of artificial intelligence techniques such as Natural Language Processing (NLP) and user profiling in helping non-expert users easily interact with the IBN system and express their desired operational goals. Such innovative solutions offer a customized support to the users to improve their Quality of Experience (QoE) while increasing the automation in the network configuration process.
{"title":"On helping users in writing network slice intents through NLP and User Profiling","authors":"R. Caldelli, P. Castoldi, M. Gharbaoui, B. Martini, M. Matarazzo, F. Sciarrone","doi":"10.1109/NetSoft57336.2023.10175400","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175400","url":null,"abstract":"Intent-based Networking (IBN) has emerged as an innovative approach to automate the provisioning of network services while abstracting the details of the underlying infrastructure and simplifying the interaction between the users and the network. In this paper, we present an intent-based framework that allows for the deployment of SDN-based and QoS-aware network slices. The main objective of the work is to describe the role of artificial intelligence techniques such as Natural Language Processing (NLP) and user profiling in helping non-expert users easily interact with the IBN system and express their desired operational goals. Such innovative solutions offer a customized support to the users to improve their Quality of Experience (QoE) while increasing the automation in the network configuration process.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129897061","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}
Pub Date : 2023-06-19DOI: 10.1109/NetSoft57336.2023.10175491
C. Cesila, R. P. Pinto, K. S. Mayer, A. F. Escallón-Portilla, D. Mello, D. Arantes, C. E. Rothenberg
This work presents Chat-IBN-RASA, a conversational AI chatbot based on the open-source RASA framework, acting as an Intent Translator component for Intent-Based Networking (IBN) architectures. The IBN-driven RASA chatbot allows users to interact with the network management system using high-level language communication without the need for in-depth technical knowledge of the network. The chatbot is trained using Natural Language Understanding (NLU) models, a defined domain, stories, and custom actions for API communication and database queries. We present the prototype implementation in a use case of survivability intents in packet-optical networks. The custom actions featured include communication with the network database, path computation, and the recommended path for intent deployment, considering availability, protection type, data rate, and link distances.
{"title":"Chat-IBN-RASA: Building an Intent Translator for Packet-Optical Networks based on RASA","authors":"C. Cesila, R. P. Pinto, K. S. Mayer, A. F. Escallón-Portilla, D. Mello, D. Arantes, C. E. Rothenberg","doi":"10.1109/NetSoft57336.2023.10175491","DOIUrl":"https://doi.org/10.1109/NetSoft57336.2023.10175491","url":null,"abstract":"This work presents Chat-IBN-RASA, a conversational AI chatbot based on the open-source RASA framework, acting as an Intent Translator component for Intent-Based Networking (IBN) architectures. The IBN-driven RASA chatbot allows users to interact with the network management system using high-level language communication without the need for in-depth technical knowledge of the network. The chatbot is trained using Natural Language Understanding (NLU) models, a defined domain, stories, and custom actions for API communication and database queries. We present the prototype implementation in a use case of survivability intents in packet-optical networks. The custom actions featured include communication with the network database, path computation, and the recommended path for intent deployment, considering availability, protection type, data rate, and link distances.","PeriodicalId":223208,"journal":{"name":"2023 IEEE 9th International Conference on Network Softwarization (NetSoft)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132487219","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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