Pub Date : 2017-11-01DOI: 10.23919/CNSM.2017.8256039
Andreas Baumgartner, T. Bauschert, Abdul A. Blzarour, Varun S. Reddy
5G networks are conceived to be highly flexible and programmable end-to-end connect-and-compute infrastructures. In that context, the concept of network slicing is of particular importance [1]. From a network infrastructure point of view, network slicing refers to the provisioning and assignment of physical substrate network resources to tenants. To enable an efficient resource allocation, suitable optimization models are required. In our previous contributions [2], we presented a model that takes into account traffic uncertainty by using the well known concept of Γ-robustness. We further extended this model to cope with general network slices and to consider also single substrate link and node failures [3]. In this paper, we present a novel model applying the concept of light robustness [4] [5] to address scalability issues of our previous models and to get a deeper insight into the tradeoff between the price of robustness and the realized robustness. We compare our model with a nominal and Γ-robust approach for different scenarios using network topology examples from SNDlib [6].
{"title":"Network slice embedding under traffic uncertainties — A light robust approach","authors":"Andreas Baumgartner, T. Bauschert, Abdul A. Blzarour, Varun S. Reddy","doi":"10.23919/CNSM.2017.8256039","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8256039","url":null,"abstract":"5G networks are conceived to be highly flexible and programmable end-to-end connect-and-compute infrastructures. In that context, the concept of network slicing is of particular importance [1]. From a network infrastructure point of view, network slicing refers to the provisioning and assignment of physical substrate network resources to tenants. To enable an efficient resource allocation, suitable optimization models are required. In our previous contributions [2], we presented a model that takes into account traffic uncertainty by using the well known concept of Γ-robustness. We further extended this model to cope with general network slices and to consider also single substrate link and node failures [3]. In this paper, we present a novel model applying the concept of light robustness [4] [5] to address scalability issues of our previous models and to get a deeper insight into the tradeoff between the price of robustness and the realized robustness. We compare our model with a nominal and Γ-robust approach for different scenarios using network topology examples from SNDlib [6].","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128001702","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255979
V. Räisänen
Virtualized execution environments in 5G network call for a linkage between network management and orchestration. Execution of 3GPP functionalities and management applications in the cloud also presents an opportunity to innovate outside of traditional paradigms. We describe a framework focusing on a virtual execution environment and utilizing agent composition to serve as a platform for realizations with particular goals — for example — in terms of coordination. The framework allows for focusing on the opportunities provided with cloud environment and microservices-based agent composition, and describing relevant aspects of orchestration, while avoiding aspects of orchestration which would bring unnecessary complexity to the analysis. The framework is planned to be used as a basis for research demonstrator later on for implementing 5G use cases.
{"title":"Agent composition for 5G management and orchestration","authors":"V. Räisänen","doi":"10.23919/CNSM.2017.8255979","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255979","url":null,"abstract":"Virtualized execution environments in 5G network call for a linkage between network management and orchestration. Execution of 3GPP functionalities and management applications in the cloud also presents an opportunity to innovate outside of traditional paradigms. We describe a framework focusing on a virtual execution environment and utilizing agent composition to serve as a platform for realizations with particular goals — for example — in terms of coordination. The framework allows for focusing on the opportunities provided with cloud environment and microservices-based agent composition, and describing relevant aspects of orchestration, while avoiding aspects of orchestration which would bring unnecessary complexity to the analysis. The framework is planned to be used as a basis for research demonstrator later on for implementing 5G use cases.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129039278","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8256032
Pradheba C. Rangarajan, F. Khendek, M. Toeroe
A Virtualized Network Function (VNF) is deployed as a cluster of VMs in the Network Functions Virtualization Infrastructure (NFVI). As in traditional telecom, VNFs are expected to provide the required functions at the requested level of availability. For this, one has to incorporate proper redundancy, and appropriate recovery and coordination mechanisms among the redundant entities. The Service Availability Forum (SA Forum) has standardized such mechanisms into a set of middleware services. Among them, the Availability Management Framework (AMF) has the responsibility of managing the availability of application services based on a configuration, called AMF configuration. We propose the use of AMF to manage the availability of the services provided by VNFs. For this, we map the AMF concepts to the Network Function Virtualization (NFV) domain and propose a method for the generation of AMF configurations for AMF managed VNFs. The approach generates an AMF configuration that meets the required level of availability of the requested service workload while aims at maximizing the resource utilization.
{"title":"Managing the availability of VNFs with the availability management framework","authors":"Pradheba C. Rangarajan, F. Khendek, M. Toeroe","doi":"10.23919/CNSM.2017.8256032","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8256032","url":null,"abstract":"A Virtualized Network Function (VNF) is deployed as a cluster of VMs in the Network Functions Virtualization Infrastructure (NFVI). As in traditional telecom, VNFs are expected to provide the required functions at the requested level of availability. For this, one has to incorporate proper redundancy, and appropriate recovery and coordination mechanisms among the redundant entities. The Service Availability Forum (SA Forum) has standardized such mechanisms into a set of middleware services. Among them, the Availability Management Framework (AMF) has the responsibility of managing the availability of application services based on a configuration, called AMF configuration. We propose the use of AMF to manage the availability of the services provided by VNFs. For this, we map the AMF concepts to the Network Function Virtualization (NFV) domain and propose a method for the generation of AMF configurations for AMF managed VNFs. The approach generates an AMF configuration that meets the required level of availability of the requested service workload while aims at maximizing the resource utilization.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189330","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255983
Ji Xue, Bin Nie, E. Smirni
Effective workload characterization and prediction are instrumental for efficiently and proactively managing large systems. System management primarily relies on the workload information provided by underlying system tracing mechanisms that record system-related events in log files. However, such tracing mechanisms may temporarily fail due to various reasons, yielding “holes” in data traces. This missing data phenomenon significantly impedes the effectiveness of data analysis. In this paper, we study real-world data traces collected from over 80K virtual machines (VMs) hosted on 6K physical boxes in the data centers of a service provider. We discover that the usage series of VMs co-located on the same physical box exhibit strong correlation with one another, and that most VM usage series show temporal patterns. By taking advantage of the observed spatial and temporal dependencies, we propose a data-filling method to predict the missing data in the VM usage series. Detailed evaluation using trace data in the wild shows that the proposed method is sufficiently accurate as it achieves an average of 20% absolute percentage errors. We also illustrate its usefulness via a use case.
{"title":"Fill-in the gaps: Spatial-temporal models for missing data","authors":"Ji Xue, Bin Nie, E. Smirni","doi":"10.23919/CNSM.2017.8255983","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255983","url":null,"abstract":"Effective workload characterization and prediction are instrumental for efficiently and proactively managing large systems. System management primarily relies on the workload information provided by underlying system tracing mechanisms that record system-related events in log files. However, such tracing mechanisms may temporarily fail due to various reasons, yielding “holes” in data traces. This missing data phenomenon significantly impedes the effectiveness of data analysis. In this paper, we study real-world data traces collected from over 80K virtual machines (VMs) hosted on 6K physical boxes in the data centers of a service provider. We discover that the usage series of VMs co-located on the same physical box exhibit strong correlation with one another, and that most VM usage series show temporal patterns. By taking advantage of the observed spatial and temporal dependencies, we propose a data-filling method to predict the missing data in the VM usage series. Detailed evaluation using trace data in the wild shows that the proposed method is sufficiently accurate as it achieves an average of 20% absolute percentage errors. We also illustrate its usefulness via a use case.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113312","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255971
Florian Heimgaertner, Mark T. Schmidt, David Morgenstern, M. Menth
With increasing network bandwidths, stateful firewalls are likely to become communication bottlenecks in networks. To mitigate this problem, we propose to bypass selected traffic around firewalls using software-defined networking (SDN). We discuss various approaches and elaborate the following concept. A controller samples outgoing packets at the firewall using sFlow to detect congestion. In case of congestion, flows already admitted by the firewall are identified and offloaded at an appropriate rate by installing flow-specific bypass rules on an OpenFlow-capable switch. We suggest two different algorithms to select appropriate flows and provide a proof-of-concept implementation in a network testbed using the Ryu controller framework. Experimental results illustrate the system behavior at different load levels with and without offloading. We provide an analytical system model to predict the offloading performance for other system parameters than experimentally evaluated and validate the model with our experimental results. A parameter study suggests that the offloaded traffic rate may be a multiple of the firewall's capacity if the switch supports sufficient flow rules or is able to match for TCP flags.
{"title":"A software-defined firewall bypass for congestion offloading","authors":"Florian Heimgaertner, Mark T. Schmidt, David Morgenstern, M. Menth","doi":"10.23919/CNSM.2017.8255971","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255971","url":null,"abstract":"With increasing network bandwidths, stateful firewalls are likely to become communication bottlenecks in networks. To mitigate this problem, we propose to bypass selected traffic around firewalls using software-defined networking (SDN). We discuss various approaches and elaborate the following concept. A controller samples outgoing packets at the firewall using sFlow to detect congestion. In case of congestion, flows already admitted by the firewall are identified and offloaded at an appropriate rate by installing flow-specific bypass rules on an OpenFlow-capable switch. We suggest two different algorithms to select appropriate flows and provide a proof-of-concept implementation in a network testbed using the Ryu controller framework. Experimental results illustrate the system behavior at different load levels with and without offloading. We provide an analytical system model to predict the offloading performance for other system parameters than experimentally evaluated and validate the model with our experimental results. A parameter study suggests that the offloaded traffic rate may be a multiple of the firewall's capacity if the switch supports sufficient flow rules or is able to match for TCP flags.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125209509","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255988
Gioacchino Tangari, M. Charalambides, D. Tuncer, G. Pavlou
Network operators have recently been developing multi-Gbps traffic monitoring tools that execute on commodity hardware and are part of the packet-processing pipelines realizing software dataplanes. These solutions allow sophisticated tasks to be performed on a per-packet basis, without relying on sampling or passive trace analysis, by leveraging the processing power available on servers. Although advances in packet capture have enabled intercepting packets from network cards at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive traffic monitoring approach that copes with emerging bottlenecks by timely detecting changes in the operational conditions and reconfiguring monitoring-related operations for subsets of traffic flows. Our solution performs responsive adaptations at the time scale of milliseconds and does not require a significant amount of resources. To demonstrate the capabilities of our approach we implemented it as part of a generic packet-processing pipeline and show that lossless traffic monitoring can be achieved for a wide range of conditions.
{"title":"Adaptive traffic monitoring for software dataplanes","authors":"Gioacchino Tangari, M. Charalambides, D. Tuncer, G. Pavlou","doi":"10.23919/CNSM.2017.8255988","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255988","url":null,"abstract":"Network operators have recently been developing multi-Gbps traffic monitoring tools that execute on commodity hardware and are part of the packet-processing pipelines realizing software dataplanes. These solutions allow sophisticated tasks to be performed on a per-packet basis, without relying on sampling or passive trace analysis, by leveraging the processing power available on servers. Although advances in packet capture have enabled intercepting packets from network cards at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive traffic monitoring approach that copes with emerging bottlenecks by timely detecting changes in the operational conditions and reconfiguring monitoring-related operations for subsets of traffic flows. Our solution performs responsive adaptations at the time scale of milliseconds and does not require a significant amount of resources. To demonstrate the capabilities of our approach we implemented it as part of a generic packet-processing pipeline and show that lossless traffic monitoring can be achieved for a wide range of conditions.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121548138","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8256011
Christian Koch, Benedikt Lins, Amr Rizk, R. Steinmetz, D. Hausheer
Video streaming is responsible for the largest portion of traffic in fixed and mobile networks. Yet, forecasts expect this amount to grow further. Especially for mobile devices connected to cellular networks, high QoE video streaming can be a challenge as the user data volume is metered and eventually limited. Also, the connection quality may vary severely. Prefetching videos is an approach to mitigate this issue. Here, videos that the user is likely to watch in advance are prefetched on the user's smartphone, e.g., while he is connected to WiFi. However, this approach can only be efficient if only the videos that are interesting for the respective user are prefetched. This constitutes a major estimation and prediction challenge. To this end, this paper presents three contributions: First, a user study over multiple months that draws valuable insights on the user video request behavior. Second, we propose a novel privacy-preserving prefetching framework denoted vFetch that prefetches videos based, e.g., on the user's affinity of YouTube channels. Third, a trace-based evaluation and parameter study that demonstrates vFetch's efficiency with a hit rate of ∼50% for a 50 GB cache.
{"title":"vFetch: Video prefetching using pseudo subscriptions and user channel affinity in YouTube","authors":"Christian Koch, Benedikt Lins, Amr Rizk, R. Steinmetz, D. Hausheer","doi":"10.23919/CNSM.2017.8256011","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8256011","url":null,"abstract":"Video streaming is responsible for the largest portion of traffic in fixed and mobile networks. Yet, forecasts expect this amount to grow further. Especially for mobile devices connected to cellular networks, high QoE video streaming can be a challenge as the user data volume is metered and eventually limited. Also, the connection quality may vary severely. Prefetching videos is an approach to mitigate this issue. Here, videos that the user is likely to watch in advance are prefetched on the user's smartphone, e.g., while he is connected to WiFi. However, this approach can only be efficient if only the videos that are interesting for the respective user are prefetched. This constitutes a major estimation and prediction challenge. To this end, this paper presents three contributions: First, a user study over multiple months that draws valuable insights on the user video request behavior. Second, we propose a novel privacy-preserving prefetching framework denoted vFetch that prefetches videos based, e.g., on the user's affinity of YouTube channels. Third, a trace-based evaluation and parameter study that demonstrates vFetch's efficiency with a hit rate of ∼50% for a 50 GB cache.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121117354","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255978
Elke Roth-Mandutz, Abubaker-Matovu Waswa, A. Mitschele-Thiel
Towards 5G, the challenge to achieve high reliability and low latency asks for new directions in systems so far strongly focusing on high data rates. Schemes to achieve high reliability for low latency demanding services are link diversity to ensure reliability and resource reservation to avoid scheduling delays. However, these schemes place high demands on the scarce radio resources. In this paper we propose a self-optimized approach on the network management level to minimize the capacity impact for ultra-reliable low latency communication (URLLC) services. The idea of the new URLLC Self-Organized Network (SON) is to provide optimized sets of parameters derived from the respective service requirements and the current conditions in the network. We discuss Network Management (NM) parameters regarding their impact on URLLC and present a structure, which allows a fast selection of the appropriate parameter set. One focus is on device-to-device (D2D) communication, which has a high potential to meet both, the reliability and latency requirements. An initial study on radio resource reuse indicates a promising gain in network capacity, while D2D reuses the same resources as the cellular users in the network.
{"title":"Capacity optimization for ultra-reliable low-latency communication in 5G — The SON perspective","authors":"Elke Roth-Mandutz, Abubaker-Matovu Waswa, A. Mitschele-Thiel","doi":"10.23919/CNSM.2017.8255978","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255978","url":null,"abstract":"Towards 5G, the challenge to achieve high reliability and low latency asks for new directions in systems so far strongly focusing on high data rates. Schemes to achieve high reliability for low latency demanding services are link diversity to ensure reliability and resource reservation to avoid scheduling delays. However, these schemes place high demands on the scarce radio resources. In this paper we propose a self-optimized approach on the network management level to minimize the capacity impact for ultra-reliable low latency communication (URLLC) services. The idea of the new URLLC Self-Organized Network (SON) is to provide optimized sets of parameters derived from the respective service requirements and the current conditions in the network. We discuss Network Management (NM) parameters regarding their impact on URLLC and present a structure, which allows a fast selection of the appropriate parameter set. One focus is on device-to-device (D2D) communication, which has a high potential to meet both, the reliability and latency requirements. An initial study on radio resource reuse indicates a promising gain in network capacity, while D2D reuses the same resources as the cellular users in the network.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114936812","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8255989
Fetia Bannour, Sami Souihi, A. Mellouk
The decoupling of control and data planes in Software-Defined Networking (SDN) brings benefits in terms of logically centralized control and application programming. But, the single point of management in physically centralized SDN architectures is a potential point of failure and a bottleneck that compromises network reliability and performance. Such centralized designs may also face scalability challenges especially in networks with a large number of hosts (e.g. IoT-like networks). To avoid such concerns, SDN control architectures are usually designed as physically distributed systems. This raises practical challenges about the best approach to decentralizing the control plane while maintaining the logically centralized network view. In particular, determining the number of controllers and locating them in the network is a hard task that should be addressed appropriately. This paper proposes two novel strategies that cover different aspects of the controller placement problem with respect to performance and reliability criteria. These strategies use two types of heuristics that are compared and assessed on large-scale topologies to provide operators with guidelines on how to find their optimal controller placement that meets their specific needs.
{"title":"Scalability and reliability aware SDN controller placement strategies","authors":"Fetia Bannour, Sami Souihi, A. Mellouk","doi":"10.23919/CNSM.2017.8255989","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8255989","url":null,"abstract":"The decoupling of control and data planes in Software-Defined Networking (SDN) brings benefits in terms of logically centralized control and application programming. But, the single point of management in physically centralized SDN architectures is a potential point of failure and a bottleneck that compromises network reliability and performance. Such centralized designs may also face scalability challenges especially in networks with a large number of hosts (e.g. IoT-like networks). To avoid such concerns, SDN control architectures are usually designed as physically distributed systems. This raises practical challenges about the best approach to decentralizing the control plane while maintaining the logically centralized network view. In particular, determining the number of controllers and locating them in the network is a hard task that should be addressed appropriately. This paper proposes two novel strategies that cover different aspects of the controller placement problem with respect to performance and reliability criteria. These strategies use two types of heuristics that are compared and assessed on large-scale topologies to provide operators with guidelines on how to find their optimal controller placement that meets their specific needs.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113952861","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 : 2017-11-01DOI: 10.23919/CNSM.2017.8256052
C. Morin, Géraldine Texier, Cao-Thanh Phan
Software Defined Networking (SDN) allows new approaches to provide Quality of Service (QoS). In legacy networks, strict QoS guarantees often result in bandwidth over-provisioning. Then, QoS enforcement either consumes too many resources, or is not flexible enough. We present a solution to provide QoS based on the creation of on-demand MPLS tunnels with guaranteed bandwidths across an SDN network. We introduce an SDN Traffic Engineering Management (STEM) module that interacts with the northbound applications to satisfy their requests to forward QoS-guaranteed traffic flows. STEM delegates the path selection to a Path Computation Element (PCE), and the path enforcement to an SDN controller. We rely on a stateful PCE to record the attributed resources and estimate the remaining network capacity, avoiding overloading the network with monitoring traffic. Upon STEM requests, the SDN controller enforces the QoS policy in the data plane. User flows are aggregated into MPLS tunnels and packets are labeled with a priority depending on the flow effective bandwidth. We highlight the shortfalls of several material and software OpenFlow compatible switches and detail an implementation based on a pica8 switch to overcome them. The experimental results demonstrate that this solution efficiently enforces bandwidth sharing in SDN networks.
{"title":"On demand QoS with a SDN traffic engineering management (STEM) module","authors":"C. Morin, Géraldine Texier, Cao-Thanh Phan","doi":"10.23919/CNSM.2017.8256052","DOIUrl":"https://doi.org/10.23919/CNSM.2017.8256052","url":null,"abstract":"Software Defined Networking (SDN) allows new approaches to provide Quality of Service (QoS). In legacy networks, strict QoS guarantees often result in bandwidth over-provisioning. Then, QoS enforcement either consumes too many resources, or is not flexible enough. We present a solution to provide QoS based on the creation of on-demand MPLS tunnels with guaranteed bandwidths across an SDN network. We introduce an SDN Traffic Engineering Management (STEM) module that interacts with the northbound applications to satisfy their requests to forward QoS-guaranteed traffic flows. STEM delegates the path selection to a Path Computation Element (PCE), and the path enforcement to an SDN controller. We rely on a stateful PCE to record the attributed resources and estimate the remaining network capacity, avoiding overloading the network with monitoring traffic. Upon STEM requests, the SDN controller enforces the QoS policy in the data plane. User flows are aggregated into MPLS tunnels and packets are labeled with a priority depending on the flow effective bandwidth. We highlight the shortfalls of several material and software OpenFlow compatible switches and detail an implementation based on a pica8 switch to overcome them. The experimental results demonstrate that this solution efficiently enforces bandwidth sharing in SDN networks.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114395655","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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