Pub Date : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165480
Sotirios Brotsis, N. Kolokotronis, Konstantinos Limniotis, S. Shiaeles
The blockchain has found numerous applications in many areas with the expectation to significantly enhance their security. The Internet of things (IoT) constitutes a prominent application domain of blockchain, with a number of architectures having been proposed for improving not only security but also properties like transparency and auditability. However, many blockchain solutions suffer from inherent constraints associated with the consensus protocol used. These constraints are mostly inherited by the permissionless setting, e.g. computational power in proof-of-work, and become serious obstacles in a resource-constrained IoT environment. Moreover, consensus protocols with low throughput or high latency are not suitable for IoT networks where massive volumes of data are generated. Thus, in this paper we focus on permissioned blockchain platforms and investigate the consensus protocols used, aiming at evaluating their performance and fault tolerance as the main selection criteria for (in principle highly insecure) IoT ecosystem. The results of the paper provide new insights on the essential differences of various consensus protocols and their capacity to meet IoT needs.
{"title":"On the Security of Permissioned Blockchain Solutions for IoT Applications","authors":"Sotirios Brotsis, N. Kolokotronis, Konstantinos Limniotis, S. Shiaeles","doi":"10.1109/NetSoft48620.2020.9165480","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165480","url":null,"abstract":"The blockchain has found numerous applications in many areas with the expectation to significantly enhance their security. The Internet of things (IoT) constitutes a prominent application domain of blockchain, with a number of architectures having been proposed for improving not only security but also properties like transparency and auditability. However, many blockchain solutions suffer from inherent constraints associated with the consensus protocol used. These constraints are mostly inherited by the permissionless setting, e.g. computational power in proof-of-work, and become serious obstacles in a resource-constrained IoT environment. Moreover, consensus protocols with low throughput or high latency are not suitable for IoT networks where massive volumes of data are generated. Thus, in this paper we focus on permissioned blockchain platforms and investigate the consensus protocols used, aiming at evaluating their performance and fault tolerance as the main selection criteria for (in principle highly insecure) IoT ecosystem. The results of the paper provide new insights on the essential differences of various consensus protocols and their capacity to meet IoT needs.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"105 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120827126","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165381
G. Bendiab, S. Shiaeles, Abdulrahman Alruban, N. Kolokotronis
With the increase of IoT devices and technologies coming into service, Malware has risen as a challenging threat with increased infection rates and levels of sophistication. Without strong security mechanisms, a huge amount of sensitive data are exposed to vulnerabilities, and therefore, easily abused by cybercriminals to perform several illegal activities. Thus, advanced network security mechanisms that are able of performing a real-time traffic analysis and mitigation of malicious traffic are required. To address this challenge, we are proposing a novel IoT malware traffic analysis approach using deep learning and visual representation for faster detection and classification of new malware (zero-day malware). The detection of malicious network traffic in the proposed approach works at the package level, reducing significantly the time of detection with promising results due to the deep learning technologies used. To evaluate our proposed method performance, a dataset is constructed which consists of 1000 pcap files of normal and malware traffic that are collected from different network traffic sources. The experimental results of Residual Neural Network (ResNet50) are very promising, providing a 94.50% accuracy rate for detection of malware traffic.
{"title":"IoT Malware Network Traffic Classification using Visual Representation and Deep Learning","authors":"G. Bendiab, S. Shiaeles, Abdulrahman Alruban, N. Kolokotronis","doi":"10.1109/NetSoft48620.2020.9165381","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165381","url":null,"abstract":"With the increase of IoT devices and technologies coming into service, Malware has risen as a challenging threat with increased infection rates and levels of sophistication. Without strong security mechanisms, a huge amount of sensitive data are exposed to vulnerabilities, and therefore, easily abused by cybercriminals to perform several illegal activities. Thus, advanced network security mechanisms that are able of performing a real-time traffic analysis and mitigation of malicious traffic are required. To address this challenge, we are proposing a novel IoT malware traffic analysis approach using deep learning and visual representation for faster detection and classification of new malware (zero-day malware). The detection of malicious network traffic in the proposed approach works at the package level, reducing significantly the time of detection with promising results due to the deep learning technologies used. To evaluate our proposed method performance, a dataset is constructed which consists of 1000 pcap files of normal and malware traffic that are collected from different network traffic sources. The experimental results of Residual Neural Network (ResNet50) are very promising, providing a 94.50% accuracy rate for detection of malware traffic.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123410937","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165306
Yukito Ueno, Ryo Nakamura, Yohei Kuga, H. Esaki
Longest prefix matching (LPM) is a fundamental process in IP routing used not only in traditional hardware routers but also in modern software middleboxes such as the applications of Network Function Virtualization. However, the performance of recent LPM methods in software routers is insufficient for high-speed packet processing such as two or more 100 Gbps throughput. To improve the performance of LPM, we propose Spider, a new LPM method that achieves a fully parallelized LPM procedure using single instruction, multiple data (SIMD) instructions in a CPU. The evaluation shows that the proposed method has 1.8-1.9 times faster LPM performance compared with the state-of-the-art methods in this study area. We describe the Spider's lookup procedure fully parallelized by SIMD instructions and the design of the routing table efficiently processed by the procedure. We also report the following three evaluations: (1) The effect of parallelization by SIMD instructions on the performance of Spider; (2) the scalability of Spider with the number of CPU cores; and (3) the performance comparison with the previous methods in terms of randomly generated and real-trace traffic patterns.
{"title":"Spider: Parallelizing Longest Prefix Matching with Optimization for SIMD Instructions","authors":"Yukito Ueno, Ryo Nakamura, Yohei Kuga, H. Esaki","doi":"10.1109/NetSoft48620.2020.9165306","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165306","url":null,"abstract":"Longest prefix matching (LPM) is a fundamental process in IP routing used not only in traditional hardware routers but also in modern software middleboxes such as the applications of Network Function Virtualization. However, the performance of recent LPM methods in software routers is insufficient for high-speed packet processing such as two or more 100 Gbps throughput. To improve the performance of LPM, we propose Spider, a new LPM method that achieves a fully parallelized LPM procedure using single instruction, multiple data (SIMD) instructions in a CPU. The evaluation shows that the proposed method has 1.8-1.9 times faster LPM performance compared with the state-of-the-art methods in this study area. We describe the Spider's lookup procedure fully parallelized by SIMD instructions and the design of the routing table efficiently processed by the procedure. We also report the following three evaluations: (1) The effect of parallelization by SIMD instructions on the performance of Spider; (2) the scalability of Spider with the number of CPU cores; and (3) the performance comparison with the previous methods in terms of randomly generated and real-trace traffic patterns.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125436817","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165424
Hasan Tooba, Adnan Akhunzada, Thanassis Giannetsos, Jahanzaib Malik
The Internet of Things (IoT) is rapidly evolving, while introducing several new challenges regarding security, resilience and operational assurance. In the face of an increasing attack landscape, it is necessary to cater for the provision of efficient mechanisms to collectively detect sophisticated malware resulting in undesirable (run-time) device and network modifications. This is not an easy task considering the dynamic and heterogeneous nature of IoT environments; i.e., different operating systems, varied connected networks and a wide gamut of underlying protocols and devices. Malicious IoT nodes or gateways can potentially lead to the compromise of the whole IoT network infrastructure. On the other hand, the SDN control plane has the capability to be orchestrated towards providing enhanced security services to all layers of the IoT networking stack. In this paper, we propose an SDN-enabled control plane based orchestration that leverages emerging Long Short-Term Memory (LSTM) classification models; a Deep Learning (DL) based architecture to combat malicious IoT nodes. It is a first step towards a new line of security mechanisms that enables the provision of scalable AI-based intrusion detection focusing on the operational assurance of only those specific, critical infrastructure components,thus, allowing for a much more efficient security solution. The proposed mechanism has been evaluated with current state of the art datasets (i.e., N_BaIoT 2018) using standard performance evaluation metrics. Our preliminary results show an outstanding detection accuracy (i.e., 99.9%) which significantly outperforms state-of-the-art approaches. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security does not hinder the deployment of intelligent IoT-based computing systems.
{"title":"Orchestrating SDN Control Plane towards Enhanced IoT Security","authors":"Hasan Tooba, Adnan Akhunzada, Thanassis Giannetsos, Jahanzaib Malik","doi":"10.1109/NetSoft48620.2020.9165424","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165424","url":null,"abstract":"The Internet of Things (IoT) is rapidly evolving, while introducing several new challenges regarding security, resilience and operational assurance. In the face of an increasing attack landscape, it is necessary to cater for the provision of efficient mechanisms to collectively detect sophisticated malware resulting in undesirable (run-time) device and network modifications. This is not an easy task considering the dynamic and heterogeneous nature of IoT environments; i.e., different operating systems, varied connected networks and a wide gamut of underlying protocols and devices. Malicious IoT nodes or gateways can potentially lead to the compromise of the whole IoT network infrastructure. On the other hand, the SDN control plane has the capability to be orchestrated towards providing enhanced security services to all layers of the IoT networking stack. In this paper, we propose an SDN-enabled control plane based orchestration that leverages emerging Long Short-Term Memory (LSTM) classification models; a Deep Learning (DL) based architecture to combat malicious IoT nodes. It is a first step towards a new line of security mechanisms that enables the provision of scalable AI-based intrusion detection focusing on the operational assurance of only those specific, critical infrastructure components,thus, allowing for a much more efficient security solution. The proposed mechanism has been evaluated with current state of the art datasets (i.e., N_BaIoT 2018) using standard performance evaluation metrics. Our preliminary results show an outstanding detection accuracy (i.e., 99.9%) which significantly outperforms state-of-the-art approaches. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security does not hinder the deployment of intelligent IoT-based computing systems.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"467 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114891905","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 : 2020-06-01DOI: 10.1109/netsoft48620.2020.9165343
Shiku Hirai, Takuya Tojo, S. Seto, S. Yasukawa
Cloud-native Network Functions (CNFs), which are an advanced form of Virtualized Network Functions (VNFs), are expected to optimize network slicing and make the development and deployment cycle of network services faster than VNFs by using a container-based microservices architecture. However, to satisfy the requirements for high reliability and performance assurance unique to network services, additional functions specific to the Kubernetes-based CNF platform are required. In this demonstration, we propose an automated CNF provisioning engine that optimizes the hardware resources of CNFs in multi-cloud environments on the basis of performance prediction and demonstrate its effectiveness by implementing it on Kubernetes as a core function of the future CNF platform.
{"title":"Automated Provisioning of Cloud-Native Network Functions in Multi-Cloud Environments","authors":"Shiku Hirai, Takuya Tojo, S. Seto, S. Yasukawa","doi":"10.1109/netsoft48620.2020.9165343","DOIUrl":"https://doi.org/10.1109/netsoft48620.2020.9165343","url":null,"abstract":"Cloud-native Network Functions (CNFs), which are an advanced form of Virtualized Network Functions (VNFs), are expected to optimize network slicing and make the development and deployment cycle of network services faster than VNFs by using a container-based microservices architecture. However, to satisfy the requirements for high reliability and performance assurance unique to network services, additional functions specific to the Kubernetes-based CNF platform are required. In this demonstration, we propose an automated CNF provisioning engine that optimizes the hardware resources of CNFs in multi-cloud environments on the basis of performance prediction and demonstrate its effectiveness by implementing it on Kubernetes as a core function of the future CNF platform.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128523380","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165431
P. Veitch, John J. Browne, Jonas Krogell
A key requirement for 5G networks supporting a range of network slices with distinct service characteristics, is to provide continuous monitoring and assurance of slice key performance indicators (KPIs). This paper describes a novel integrated framework using complementary methods of monitoring performance assurance. End-to-end active monitoring using a vendor-specific capability, is complemented by an open-source solution to passively collect and visualize platform telemetry. Via a proof-of-concept testbed, it is demonstrated that combining the reporting and visualization of performance KPIs applicable to different parts of the network infrastructure, provides a very powerful and holistic insights framework for 5G slicing assurance.
{"title":"An Integrated Instrumentation and Insights Framework for Holistic 5G Slice Assurance","authors":"P. Veitch, John J. Browne, Jonas Krogell","doi":"10.1109/NetSoft48620.2020.9165431","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165431","url":null,"abstract":"A key requirement for 5G networks supporting a range of network slices with distinct service characteristics, is to provide continuous monitoring and assurance of slice key performance indicators (KPIs). This paper describes a novel integrated framework using complementary methods of monitoring performance assurance. End-to-end active monitoring using a vendor-specific capability, is complemented by an open-source solution to passively collect and visualize platform telemetry. Via a proof-of-concept testbed, it is demonstrated that combining the reporting and visualization of performance KPIs applicable to different parts of the network infrastructure, provides a very powerful and holistic insights framework for 5G slicing assurance.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115380384","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165508
Asma Chiha, M. V. D. Wee, K. Briggs, D. Colle
The ever-increasing customer demand for emerging applications and services poses new technological as well as business challenges for the new 5G networks. To meet user’ expectations, satellite communication can complement terrestrial deployments, in some specific use cases. Though, integrating satellite and 5G needs close collaboration between different network operators, that have different backgrounds, which poses business and technical challenges. This paper aims to assess, from a business-model perspective, the role of a radio-resource broker in the satellite-5G network integration case. The paper concludes that efficiency gains can be result from using a broker, if specific technical challenges are overcome and if it is managed by a regulatory body. The broker analysis showed that three different business models of the broker can be realized, depending on which level the satellite operator could allow the broker to manage its network resources.
{"title":"Techno-economic evaluation of a brokerage role in the context of integrated satellite-5G networks","authors":"Asma Chiha, M. V. D. Wee, K. Briggs, D. Colle","doi":"10.1109/NetSoft48620.2020.9165508","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165508","url":null,"abstract":"The ever-increasing customer demand for emerging applications and services poses new technological as well as business challenges for the new 5G networks. To meet user’ expectations, satellite communication can complement terrestrial deployments, in some specific use cases. Though, integrating satellite and 5G needs close collaboration between different network operators, that have different backgrounds, which poses business and technical challenges. This paper aims to assess, from a business-model perspective, the role of a radio-resource broker in the satellite-5G network integration case. The paper concludes that efficiency gains can be result from using a broker, if specific technical challenges are overcome and if it is managed by a regulatory body. The broker analysis showed that three different business models of the broker can be realized, depending on which level the satellite operator could allow the broker to manage its network resources.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114383160","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165339
Susanna Schwarzmann, T. Zinner
HTTP Adaptive Streaming (HAS) is the de-facto standard for video delivery over the Internet. Splitting the video clip into small segments and providing multiple quality levels per segment allows the client to dynamically adapt the quality to current network conditions. The performance of HAS, and as a consequence the user Quality of Experience (QoE), is influenced by a multitude of parameters. This includes adjustable settings like quality switching thresholds, the initial buffer level, or the maximum buffer, as well as video characteristics like segment duration or the variation of segment sizes along the video. Recently, a couple of analytical models for video streaming have been proposed, allowing to compare these input parameters and derive their impact on QoE-relevant metrics for HAS-based video delivery. The outcome of these models are typically asymptotic probabilities, distribution functions, or centralized and standardized moments. For instance, these models do not yield any temporal information in terms of stalling events or requested video quality. This contradicts to QoE prediction models like P.1203, which compute the QoE based on the chronological sequence of a specific video playback. So far, it is unclear how and to which extent the generalized results of analytical models can be utilized to derive sequence-based QoE values or the QoE distribution for a set of sequences for similar input parameters with stochastic variations. To address this problem, we compare testbed measurements with the output of a GI/GI/1 model with pq-policy and buffer-based quality switching capability to conclude to which extent the results still allow to approximate the video QoE.
{"title":"Linking QoE and Performance Models for DASH-based Video Streaming","authors":"Susanna Schwarzmann, T. Zinner","doi":"10.1109/NetSoft48620.2020.9165339","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165339","url":null,"abstract":"HTTP Adaptive Streaming (HAS) is the de-facto standard for video delivery over the Internet. Splitting the video clip into small segments and providing multiple quality levels per segment allows the client to dynamically adapt the quality to current network conditions. The performance of HAS, and as a consequence the user Quality of Experience (QoE), is influenced by a multitude of parameters. This includes adjustable settings like quality switching thresholds, the initial buffer level, or the maximum buffer, as well as video characteristics like segment duration or the variation of segment sizes along the video. Recently, a couple of analytical models for video streaming have been proposed, allowing to compare these input parameters and derive their impact on QoE-relevant metrics for HAS-based video delivery. The outcome of these models are typically asymptotic probabilities, distribution functions, or centralized and standardized moments. For instance, these models do not yield any temporal information in terms of stalling events or requested video quality. This contradicts to QoE prediction models like P.1203, which compute the QoE based on the chronological sequence of a specific video playback. So far, it is unclear how and to which extent the generalized results of analytical models can be utilized to derive sequence-based QoE values or the QoE distribution for a set of sequences for similar input parameters with stochastic variations. To address this problem, we compare testbed measurements with the output of a GI/GI/1 model with pq-policy and buffer-based quality switching capability to conclude to which extent the results still allow to approximate the video QoE.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114644215","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165364
Masahiro Sasabe, Takanori Hara
Network functions virtualization (NFV) is a new paradigm to achieve flexible and agile network services by decoupling network functions from proprietary hardware and running them on generic hardware as virtual network functions (VNFs). In the NFV network, a certain network service can be modeled as a sequence of VNFs, called a service chain. Given a connection request (origin node, destination node, and service chain requirement, which is a sequence of functions), the service chaining problem aims to find an appropriate service path, which starts from the origin and ends with the destination while executing the VNFs at the intermediate nodes in the required order. Some existing work noticed that the service chaining problem was similar to the shortest path tour problem (SPTP). To the best of our knowledge, this is the first work that exactly formulates the service chaining problem as an SPTP-based integer linear program (ILP). Through numerical results, we show the SPTP-based ILP can support 1.30-1.77 times larger scale systems than the existing ILP.
{"title":"Shortest Path Tour Problem Based Integer Linear Programming for Service Chaining in NFV Networks","authors":"Masahiro Sasabe, Takanori Hara","doi":"10.1109/NetSoft48620.2020.9165364","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165364","url":null,"abstract":"Network functions virtualization (NFV) is a new paradigm to achieve flexible and agile network services by decoupling network functions from proprietary hardware and running them on generic hardware as virtual network functions (VNFs). In the NFV network, a certain network service can be modeled as a sequence of VNFs, called a service chain. Given a connection request (origin node, destination node, and service chain requirement, which is a sequence of functions), the service chaining problem aims to find an appropriate service path, which starts from the origin and ends with the destination while executing the VNFs at the intermediate nodes in the required order. Some existing work noticed that the service chaining problem was similar to the shortest path tour problem (SPTP). To the best of our knowledge, this is the first work that exactly formulates the service chaining problem as an SPTP-based integer linear program (ILP). Through numerical results, we show the SPTP-based ILP can support 1.30-1.77 times larger scale systems than the existing ILP.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114916026","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 : 2020-06-01DOI: 10.1109/NetSoft48620.2020.9165501
C. Dominicini, D. Mafioletti, A. Locateli, R. Villaça, M. Martinello, M. Ribeiro, A. Gorodnik
Source routing (SR) is a prominent alternative to table-based routing for reducing the number of network states. However, traditional SR approaches, based on Port Switching, still maintain a state in the packet by using a header rewrite operation. The residue number system (RNS) is a promising way of executing fully stateless SR, in which forwarding decisions at core nodes rely on a simple modulo operation over a route label. Nevertheless, such operation over integer arithmetic is not natively supported by commodity network hardware. Thus, we propose a novel RNS-based SR scheme, named PolKA, that explores binary polynomial arithmetic using Galois field (GF) of order 2. We evaluate PolKA in comparison to Port Switching by implementing emulated and hardware prototypes using P4 architecture. Results show that PolKA can achieve equivalent performance, while providing advanced routing features, such as fast failure reaction and agile path migration.
{"title":"PolKA: Polynomial Key-based Architecture for Source Routing in Network Fabrics","authors":"C. Dominicini, D. Mafioletti, A. Locateli, R. Villaça, M. Martinello, M. Ribeiro, A. Gorodnik","doi":"10.1109/NetSoft48620.2020.9165501","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165501","url":null,"abstract":"Source routing (SR) is a prominent alternative to table-based routing for reducing the number of network states. However, traditional SR approaches, based on Port Switching, still maintain a state in the packet by using a header rewrite operation. The residue number system (RNS) is a promising way of executing fully stateless SR, in which forwarding decisions at core nodes rely on a simple modulo operation over a route label. Nevertheless, such operation over integer arithmetic is not natively supported by commodity network hardware. Thus, we propose a novel RNS-based SR scheme, named PolKA, that explores binary polynomial arithmetic using Galois field (GF) of order 2. We evaluate PolKA in comparison to Port Switching by implementing emulated and hardware prototypes using P4 architecture. Results show that PolKA can achieve equivalent performance, while providing advanced routing features, such as fast failure reaction and agile path migration.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130850909","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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