Pub Date : 2019-10-01DOI: 10.23919/cnsm46954.2019.9012694
Joel Reginald Dodoo, Weiqiang Sun, Feng Zhu, Weisheng Hu
Existing data center networks (DCNs) based on only electronic packet or all-optical switching still pose an exponential increase in power consumption and cost due to the current high demand for digital data and sustainability issues. The recent development of hybrid DCN prototypes is a promising solution offering relatively higher data throughput, low latency, reduction in cost and energy consumption. This paper explores the frontier of hybrid DCN with a special focus on energy consumption and cost. We evaluate the energy consumption per bit and the greenhouse gas (GHG) emission per year of three hybrid switching systems as compared with an optical point to point (ptp) network, results show that the hybrid switching systems will consume less energy per bit and are likely to emit less GHG annually. We present feasibility analysis on the energy consumption and cost of some hybrid DCN prototypes. Evaluation results show that Helios-like and Hybrid Optical Switching-like prototypes achieve a power usage effectiveness (PUE) value lower than 1.2, an index which represents a very efficient level of energy performance in a data center network.
{"title":"Energy Consumption of Hybrid Data Center Networks","authors":"Joel Reginald Dodoo, Weiqiang Sun, Feng Zhu, Weisheng Hu","doi":"10.23919/cnsm46954.2019.9012694","DOIUrl":"https://doi.org/10.23919/cnsm46954.2019.9012694","url":null,"abstract":"Existing data center networks (DCNs) based on only electronic packet or all-optical switching still pose an exponential increase in power consumption and cost due to the current high demand for digital data and sustainability issues. The recent development of hybrid DCN prototypes is a promising solution offering relatively higher data throughput, low latency, reduction in cost and energy consumption. This paper explores the frontier of hybrid DCN with a special focus on energy consumption and cost. We evaluate the energy consumption per bit and the greenhouse gas (GHG) emission per year of three hybrid switching systems as compared with an optical point to point (ptp) network, results show that the hybrid switching systems will consume less energy per bit and are likely to emit less GHG annually. We present feasibility analysis on the energy consumption and cost of some hybrid DCN prototypes. Evaluation results show that Helios-like and Hybrid Optical Switching-like prototypes achieve a power usage effectiveness (PUE) value lower than 1.2, an index which represents a very efficient level of energy performance in a data center network.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122726356","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012715
A. Jakaria, M. Rahman, A. Gokhale
The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller. Introducing SDN into a SCADA network helps in deploying novel grid control operations, as well as, their management. As the overall network cannot be transformed to have only SDN-enabled devices overnight because of budget constraints, a systematic deployment methodology is needed. In this work, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are specified with respect to a set of identified threat vectors. The deployment plan primarily includes the best placements of the SDN-enabled switches. The plan may include one or more links to be installed newly. We model and implement the SDNSynth framework that includes the satisfaction of several requirements and constraints involved in resilient operation of the SCADA. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study and evaluate its performance on different synthetic SCADA systems.
智能电网中的SCADA (supervisory control and data acquisition)网络需要可靠、高效地向控制器传输实时数据。将SDN引入SCADA网络有助于部署新的电网控制操作及其管理。由于预算限制，无法在一夜之间将整个网络转换为仅支持sdn的设备，因此需要一种系统的部署方法。在这项工作中，我们提出了一个名为SDNSynth的框架，它可以设计一个由传统转发设备和可编程sdn支持交换机组成的混合网络。该设计满足SCADA网络的弹性要求，这些要求是根据一组已识别的威胁向量指定的。部署计划主要包括支持sdn的交换机的最佳位置。该计划可能包括一个或多个新安装的链接。我们建模并实现了SDNSynth框架，该框架包括对SCADA弹性操作中涉及的几个要求和约束的满足。利用满足模理论(SMT)对综合模型进行编码和求解。我们在一个案例研究中演示了SDNSynth，并评估了它在不同的合成SCADA系统上的性能。
{"title":"A Formal Model for Resiliency-Aware Deployment of SDN: A SCADA-Based Case Study","authors":"A. Jakaria, M. Rahman, A. Gokhale","doi":"10.23919/CNSM46954.2019.9012715","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012715","url":null,"abstract":"The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller. Introducing SDN into a SCADA network helps in deploying novel grid control operations, as well as, their management. As the overall network cannot be transformed to have only SDN-enabled devices overnight because of budget constraints, a systematic deployment methodology is needed. In this work, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are specified with respect to a set of identified threat vectors. The deployment plan primarily includes the best placements of the SDN-enabled switches. The plan may include one or more links to be installed newly. We model and implement the SDNSynth framework that includes the satisfaction of several requirements and constraints involved in resilient operation of the SCADA. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study and evaluate its performance on different synthetic SCADA systems.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130862722","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012671
El Houssine Bourhim, H. Elbiaze, Mouhamad Dieye
In recent years, fog computing has increasingly become popular with the advent of Internet of Things (IoT) applications characterized by strict Quality of Service (QoS) requirements. To deploy applications, applications are typically decomposed into services then embedded with fog nodes. However, an overlooked aspect in container placement strategies is the heterogeneous inter-container network communication technologies and their impact on application performances in fog networks. We propose and evaluate in this paper, a near optimal genetic algorithm based container placement strategy that takes into account Remote Direct Memory Access as well host and overlay mode for inter-container communication to ensure application response time requirements.
{"title":"Inter-container Communication Aware Container Placement in Fog Computing","authors":"El Houssine Bourhim, H. Elbiaze, Mouhamad Dieye","doi":"10.23919/CNSM46954.2019.9012671","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012671","url":null,"abstract":"In recent years, fog computing has increasingly become popular with the advent of Internet of Things (IoT) applications characterized by strict Quality of Service (QoS) requirements. To deploy applications, applications are typically decomposed into services then embedded with fog nodes. However, an overlooked aspect in container placement strategies is the heterogeneous inter-container network communication technologies and their impact on application performances in fog networks. We propose and evaluate in this paper, a near optimal genetic algorithm based container placement strategy that takes into account Remote Direct Memory Access as well host and overlay mode for inter-container communication to ensure application response time requirements.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131410380","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012729
Alberto Martínez Alba, W. Kellerer
Along with many other novel features, the fifth generation of mobile networks (5G) aims at highly flexible and dynamic network management, as well as reduced cost for operators. In order to enable both features, rapid and efficient adaptation to environmental changes is needed. This requires a complete knowledge of the characteristics of the user traffic at all time scales, but state-of-the-art research clearly differentiates between large-scale and small-scale traffic behavior. In this work, we propose a traffic model that connects large-scale and smallscale phenomena. We show that the standard small-scale models may produce inaccurate results in case of network congestion. We propose a strategy to mitigate this problem and evaluate it through simulations.
{"title":"Large- and Small-Scale Modeling of User Traffic in 5G Networks","authors":"Alberto Martínez Alba, W. Kellerer","doi":"10.23919/CNSM46954.2019.9012729","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012729","url":null,"abstract":"Along with many other novel features, the fifth generation of mobile networks (5G) aims at highly flexible and dynamic network management, as well as reduced cost for operators. In order to enable both features, rapid and efficient adaptation to environmental changes is needed. This requires a complete knowledge of the characteristics of the user traffic at all time scales, but state-of-the-art research clearly differentiates between large-scale and small-scale traffic behavior. In this work, we propose a traffic model that connects large-scale and smallscale phenomena. We show that the standard small-scale models may produce inaccurate results in case of network congestion. We propose a strategy to mitigate this problem and evaluate it through simulations.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117212189","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012697
D. Borsatti, G. Davoli, W. Cerroni, F. Callegati
In this manuscript we describe an experimental work that integrates the NFV-MANO framework with segment routing to support 5G network slicing. The aim is to implement Service Function Chains spanning several cloud domains and the related interconnection transport network in a coordinated way. The manuscript shows the feasibility and the performance effectiveness of this approach, reporting numerical results from practical experiments.
{"title":"Service Function Chaining Leveraging Segment Routing for 5G Network Slicing","authors":"D. Borsatti, G. Davoli, W. Cerroni, F. Callegati","doi":"10.23919/CNSM46954.2019.9012697","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012697","url":null,"abstract":"In this manuscript we describe an experimental work that integrates the NFV-MANO framework with segment routing to support 5G network slicing. The aim is to implement Service Function Chains spanning several cloud domains and the related interconnection transport network in a coordinated way. The manuscript shows the feasibility and the performance effectiveness of this approach, reporting numerical results from practical experiments.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126433947","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012675
Sarah Wassermann, Thibaut Cuvelier, Pavol Mulinka, P. Casas
Network-traffic data commonly arrives in the form of fast data streams; online network-monitoring systems continuously analyze these kinds of streams, sequentially collecting measurements over time. Continuous and dynamic learning is an effective learning strategy when operating in these fast and dynamic environments, where concept drifts constantly occur. In this paper, we propose different approaches for stream-based machine learning, able to analyze network-traffic streams on the fly, using supervised learning techniques. We address two major challenges associated to stream-based machine learning and online network monitoring: (i) how to dynamically learn from and adapt to non-stationary data and patterns changing over time, and (ii) how to deal with the limited availability of ground truth or labeled data to continuously tune a supervised learning model. We introduce ADAM * RAL, two stream-based machine-learning approaches to tackle these challenges. ADAM implements multiple stream-based machine-learning models and relies on an adaptive memory strategy to dynamically adapt the size of the system’s learning memory to the most recent data distribution, triggering new learning steps when concept drifts are detected. RAL implements a stream-based active-learning strategy to reduce the amount of labeled data needed for streambased learning, dynamically deciding on the most informative samples to integrate into the continuous learning scheme. Using a reinforcement learning loop, RAL improves prediction performance by additionally learning from the goodness of its previous sample-selection decisions. We focus on a particularly challenging problem in network monitoring: continuously tuning detection models able to recognize network attacks over time.By continuously learning from and detecting concept drifts within real network measurements, we show that ADAM * RAL can continuously achieve high detection accuracy and limit the amount of training data needed to detect attacks over dynamic network data streams.
{"title":"ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring","authors":"Sarah Wassermann, Thibaut Cuvelier, Pavol Mulinka, P. Casas","doi":"10.23919/CNSM46954.2019.9012675","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012675","url":null,"abstract":"Network-traffic data commonly arrives in the form of fast data streams; online network-monitoring systems continuously analyze these kinds of streams, sequentially collecting measurements over time. Continuous and dynamic learning is an effective learning strategy when operating in these fast and dynamic environments, where concept drifts constantly occur. In this paper, we propose different approaches for stream-based machine learning, able to analyze network-traffic streams on the fly, using supervised learning techniques. We address two major challenges associated to stream-based machine learning and online network monitoring: (i) how to dynamically learn from and adapt to non-stationary data and patterns changing over time, and (ii) how to deal with the limited availability of ground truth or labeled data to continuously tune a supervised learning model. We introduce ADAM * RAL, two stream-based machine-learning approaches to tackle these challenges. ADAM implements multiple stream-based machine-learning models and relies on an adaptive memory strategy to dynamically adapt the size of the system’s learning memory to the most recent data distribution, triggering new learning steps when concept drifts are detected. RAL implements a stream-based active-learning strategy to reduce the amount of labeled data needed for streambased learning, dynamically deciding on the most informative samples to integrate into the continuous learning scheme. Using a reinforcement learning loop, RAL improves prediction performance by additionally learning from the goodness of its previous sample-selection decisions. We focus on a particularly challenging problem in network monitoring: continuously tuning detection models able to recognize network attacks over time.By continuously learning from and detecting concept drifts within real network measurements, we show that ADAM * RAL can continuously achieve high detection accuracy and limit the amount of training data needed to detect attacks over dynamic network data streams.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127213836","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012665
Kohei Watabe, Norinosuke Murai, Shintaro Hirakawa, K. Nakagawa
For the design of delay/loss sensitive applications (e.g., audio/video conferencing, IP telephony, or telesurgery), it is important to accurately measure metrics along an end-to-end path. To improve the accuracy of end-to-end delay measurements, in our previous work, we have proposed a parallel flow monitoring technique. In this technique, delay samples of a target flow increase by utilizing the observation results of other flows sharing the source/destination with the target flow. In this paper, we extend this delay measurement technique to loss measurements and enable it to fully utilize information of all flows including flows with different source and destination. We confirmed that the proposed method reduces the error of loss rate estimations by 57.5% on average in ns-3 simulations.
{"title":"Accurate Loss Estimation Technique Utilizing Parallel Flow Monitoring","authors":"Kohei Watabe, Norinosuke Murai, Shintaro Hirakawa, K. Nakagawa","doi":"10.23919/CNSM46954.2019.9012665","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012665","url":null,"abstract":"For the design of delay/loss sensitive applications (e.g., audio/video conferencing, IP telephony, or telesurgery), it is important to accurately measure metrics along an end-to-end path. To improve the accuracy of end-to-end delay measurements, in our previous work, we have proposed a parallel flow monitoring technique. In this technique, delay samples of a target flow increase by utilizing the observation results of other flows sharing the source/destination with the target flow. In this paper, we extend this delay measurement technique to loss measurements and enable it to fully utilize information of all flows including flows with different source and destination. We confirmed that the proposed method reduces the error of loss rate estimations by 57.5% on average in ns-3 simulations.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131183998","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012680
Amjad Badar, D. Lou, U. Graf, Christian Barth, Christian Stich
In the past years, the Industry 4.0, also known as the Fourth Industrial Revolution, has emerged by the advancement of manufacturing technologies with the Internet of Things (IoT) to enable interconnected manufacturing machines and systems with higher productivity. One of the interesting scenarios in the context of I4.0 is to provide control from the edge, which will improve the efficiency and flexibility of the system at a reduced cost. The industrial automation, especially the process automation (PA) aims for a converged network for data communication. Traditionally internet protocol (IP) is being used for standard IT communication to connect machines to the enterprise network, but not used as much for field network due to lack of determinism. Recent, research has been focused on the design and development of deterministic IP communication, and some preliminary results have been standardized in the IETF Deterministic Network (DetNet) group. In this paper, we investigate on extending the deterministic IP communication to operational technology (OT) domain to support real time industrial Ethernet (RTE) communications. We have integrated IEC-61131-3 based soft PLC (Programmable Logic Controller) runtime system into an Edge computing gateway. The RTE frames are wrapped up with custom UDP/IP header by a proxy and delivered to the deterministic routers. The routers forward packets with a bounded delay of less than 30us per hop. We validate our approach using an experimental test setup, a virtualized PLC (vPLC) inside the edge device remotely controlling the PA application (bioreactor) by passing through proxies and deterministic routers in a heterogeneous network.
{"title":"Intelligent Edge Control with Deterministic-IP based Industrial Communication in Process Automation","authors":"Amjad Badar, D. Lou, U. Graf, Christian Barth, Christian Stich","doi":"10.23919/CNSM46954.2019.9012680","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012680","url":null,"abstract":"In the past years, the Industry 4.0, also known as the Fourth Industrial Revolution, has emerged by the advancement of manufacturing technologies with the Internet of Things (IoT) to enable interconnected manufacturing machines and systems with higher productivity. One of the interesting scenarios in the context of I4.0 is to provide control from the edge, which will improve the efficiency and flexibility of the system at a reduced cost. The industrial automation, especially the process automation (PA) aims for a converged network for data communication. Traditionally internet protocol (IP) is being used for standard IT communication to connect machines to the enterprise network, but not used as much for field network due to lack of determinism. Recent, research has been focused on the design and development of deterministic IP communication, and some preliminary results have been standardized in the IETF Deterministic Network (DetNet) group. In this paper, we investigate on extending the deterministic IP communication to operational technology (OT) domain to support real time industrial Ethernet (RTE) communications. We have integrated IEC-61131-3 based soft PLC (Programmable Logic Controller) runtime system into an Edge computing gateway. The RTE frames are wrapped up with custom UDP/IP header by a proxy and delivered to the deterministic routers. The routers forward packets with a bounded delay of less than 30us per hop. We validate our approach using an experimental test setup, a virtualized PLC (vPLC) inside the edge device remotely controlling the PA application (bioreactor) by passing through proxies and deterministic routers in a heterogeneous network.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134551710","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012725
Chunghan Lee, Kentaro Ebisawa, H. Kuwata, M. Kohno, S. Matsushima
The GPRS Tunneling Protocol User Plane (GTP-U) has long been deployed for GSM, UMTS and 4G LTE. Now for 5G, IPv6 Segment Routing (SRv6) has been proposed as an alternative user plane protocol to GTP-U in both 3GPP and IETF. SRv6 based on source routing has many advantages: stateless traffic steering, network programming and so on. Despite the advantages, it is hard to expect to replace GTP-U by SRv6 all at once, even in a 5G deployment because of a lot of dependencies between 3GPP nodes. Therefore, stateless translation and coexistence with GTP-U have been proposed in IETF. However there are no suitable measurement platform and performance evaluation results between GTP-U and SRv6. In particular, it is hard to measure latency on commercial traffic generators when a receiving packet type is different from a sending packet type. In this paper, we focus on the performance evaluation between GTP-U and SRv6 stateless translation. We designed an SRv6 measurement platform using a programmable switch, and measured GTP-U and SRv6 functions with pre-defined scenarios on a local environment. Well-known performance metrics, such as throughput and packets per second (PPS), are measured by the traffic generator while the latency at the functions was measured using telemetry on our SRv6 platform. In our evaluation, we cannot find the abrupt performance drop of well-known metrics at SRv6 stateless translation. Moreover, the latency of SRv6 stateless translation is similar to GTP-U and their performance degradation is negligible. Through the evaluation results, it is obvious that the SRv6 stateless translation is acceptable to the 5G user plane.
{"title":"Performance Evaluation of GTP-U and SRv6 Stateless Translation","authors":"Chunghan Lee, Kentaro Ebisawa, H. Kuwata, M. Kohno, S. Matsushima","doi":"10.23919/CNSM46954.2019.9012725","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012725","url":null,"abstract":"The GPRS Tunneling Protocol User Plane (GTP-U) has long been deployed for GSM, UMTS and 4G LTE. Now for 5G, IPv6 Segment Routing (SRv6) has been proposed as an alternative user plane protocol to GTP-U in both 3GPP and IETF. SRv6 based on source routing has many advantages: stateless traffic steering, network programming and so on. Despite the advantages, it is hard to expect to replace GTP-U by SRv6 all at once, even in a 5G deployment because of a lot of dependencies between 3GPP nodes. Therefore, stateless translation and coexistence with GTP-U have been proposed in IETF. However there are no suitable measurement platform and performance evaluation results between GTP-U and SRv6. In particular, it is hard to measure latency on commercial traffic generators when a receiving packet type is different from a sending packet type. In this paper, we focus on the performance evaluation between GTP-U and SRv6 stateless translation. We designed an SRv6 measurement platform using a programmable switch, and measured GTP-U and SRv6 functions with pre-defined scenarios on a local environment. Well-known performance metrics, such as throughput and packets per second (PPS), are measured by the traffic generator while the latency at the functions was measured using telemetry on our SRv6 platform. In our evaluation, we cannot find the abrupt performance drop of well-known metrics at SRv6 stateless translation. Moreover, the latency of SRv6 stateless translation is similar to GTP-U and their performance degradation is negligible. Through the evaluation results, it is obvious that the SRv6 stateless translation is acceptable to the 5G user plane.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132557239","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012661
Alessandro Gaballo, Matteo Flocco, Flavio Esposito, G. Marchetto
With edge computing, it is possible to offload computationally intensive tasks to closer and more powerful servers, passing through an edge network. This practice aims to reduce both response time and energy consumption of data-intensive applications, crucial constraints in mobile and IoT devices. In challenged networked scenarios, such as those deployed by first responders after a natural or human-made disaster, it is particularly challenging to achieve high levels of throughput due to scarce network conditions.In this paper, we present an algorithm for traffic management that takes advantage of a deep learning model to implement the forwarding mechanism during task offloading in these challenging scenarios. In particular, our work explores if and when it is worth using deep learning on a switch to route traffic generated by microservices and offloading requests. Our approach differs from classical ones in the design: we do not train centralized routing decisions. Instead, we let each router learn how to adapt to a lossy path without coordination, by merely using signals from standard performance-unaware protocols such as OSPF. Our results, obtained with a prototype and with simulations are encouraging, and uncover a few surprising results.
{"title":"Steering Traffic via Recurrent Neural Networks in Challenged Edge Scenarios","authors":"Alessandro Gaballo, Matteo Flocco, Flavio Esposito, G. Marchetto","doi":"10.23919/CNSM46954.2019.9012661","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012661","url":null,"abstract":"With edge computing, it is possible to offload computationally intensive tasks to closer and more powerful servers, passing through an edge network. This practice aims to reduce both response time and energy consumption of data-intensive applications, crucial constraints in mobile and IoT devices. In challenged networked scenarios, such as those deployed by first responders after a natural or human-made disaster, it is particularly challenging to achieve high levels of throughput due to scarce network conditions.In this paper, we present an algorithm for traffic management that takes advantage of a deep learning model to implement the forwarding mechanism during task offloading in these challenging scenarios. In particular, our work explores if and when it is worth using deep learning on a switch to route traffic generated by microservices and offloading requests. Our approach differs from classical ones in the design: we do not train centralized routing decisions. Instead, we let each router learn how to adapt to a lossy path without coordination, by merely using signals from standard performance-unaware protocols such as OSPF. Our results, obtained with a prototype and with simulations are encouraging, and uncover a few surprising results.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"124 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120872368","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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