The Experts below are selected from a list of 9717 Experts worldwide ranked by ideXlab platform
Wolfgang Kellerer - One of the best experts on this subject based on the ideXlab platform.
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sdn Hypervisors how much does topology abstraction matter
Conference on Network and Service Management, 2018Co-Authors: Nemanja Deric, Arsany Basta, Andreas Blenk, Amir Varasteh, Wolfgang KellererAbstract:SDN network Hypervisors realize the virtualization of software-defined networks. They intercept the control path between tenant controllers and their respective virtual Software-Defined Networks (SDN). Over-utilizing SDN hypervisor resources (i.e., CPU) can degrade the control plane performance of the tenants. Although many hypervisor proposals exists, a detailed performance modeling of SDN Hypervisors is missing in literature. A precise modeling of the required SDN hypervisor resources, however, is crucial for predictable and reliable operation of virtual software-defined networks. In this paper, we measure and evaluate how topology abstraction can affect the SDN hypervisor CPU utilization. We consider two topology abstraction cases: the (1) transparent and (2) big-switch abstraction. Our measurements taken from a real testbed indicate that the big-switch abstraction can reduce the SDN hypervisor CPU utilization up to $\sim 4\times $. Further, we evaluate different functions to model the SDN hypervisor CPU utilization based on our measurement results. Our evaluations show that a polynomial function provides the lowest fitting error. Motivated by our measurements, we conduct a first-step investigation of the impacts of topology abstraction on the Virtual Network Embedding (VNE) problem. Our initial simulation-based evaluations indicate that different topology abstraction procedures impact the results of the VNE problem.
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Survey on network virtualization Hypervisors for software defined networking
IEEE Communications Surveys and Tutorials, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Wolfgang KellererAbstract:Software defined networking (SDN) has emerged as a promising paradigm for making the control of communication networks flexible. SDN separates the data packet forwarding plane, i.e., the data plane, from the control plane and employs a central controller. Network virtualization allows the flexible sharing of physical networking resources by multiple users (tenants). Each tenant runs its own applications over its virtual network, i.e., its slice of the actual physical network. The virtualization of SDN networks promises to allow networks to leverage the combined benefits of SDN networking and network virtualization and has therefore attracted significant research attention in recent years. A critical component for virtualizing SDN networks is an SDN hypervisor that abstracts the underlying physical SDN network into multiple logically isolated virtual SDN networks (vSDNs), each with its own controller. We comprehensively survey Hypervisors for SDN networks in this article. We categorize the SDN Hypervisors according to their architecture into centralized and distributed Hypervisors. We furthermore sub-classify the Hypervisors according to their execution platform into Hypervisors running exclusively on general-purpose compute platforms, or on a combination of general-purpose compute platforms with general- or special-purpose network elements. We exhaustively compare the network attribute abstraction and isolation features of the existing SDN Hypervisors. As part of the future research agenda, we outline the development of a performance evaluation framework for SDN Hypervisors.
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Control Plane Latency With SDN Network Hypervisors: The Cost of Virtualization
IEEE Transactions on Network and Service Management, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Johannes Zerwas, Wolfgang KellererAbstract:Software defined networking (SDN) network Hypervisors provide the functionalities needed for virtualizing software-defined networks. Hypervisors sit logically between the multiple virtual SDN networks (vSDNs), which reside on the underlying physical SDN network infrastructure, and the corresponding tenant (vSDN) controllers. Different SDN network hypervisor architectures have mainly been explored through proof-of-concept implementations. We fundamentally advance SDN network hypervisor research by conducting a model-based analysis of SDN hypervisor architectures. Specifically, we introduce mixed integer programming formulations for four different SDN network hypervisor architectures. Our model formulations can also optimize the placement of multi-controller switches in virtualized OpenFlow-enabled SDN networks. We employ our models to quantitatively examine the optimal placement of the hypervisor instances. We compare the control plane latencies of the different SDN hypervisor architectures and quantify the cost of virtualization, i.e., the latency overhead due to virtualizing SDN networks via Hypervisors. For generalization, we quantify how the hypervisor architectures behave for different network topologies. Our model formulations and the insights drawn from our evaluations inform network operators about the trade-offs of the different hypervisor architectures and help choosing an architecture according to operator demands.
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NetSoft - hvbench: An open and scalable SDN network hypervisor benchmark
2016 IEEE NetSoft Conference and Workshops (NetSoft), 2016Co-Authors: Christian Sieber, Arsany Basta, Andreas Blenk, Wolfgang KellererAbstract:Software-defined networking (SDN) introduces a split between the forwarding plane and the control plane of modern network equipment. Furthermore, OpenFlow, as an open interface for SDN, fosters the development of logically centralized network operation systems (NOS). To allow multiple network operation systems accessing the same network, there is the concept of SDN Hypervisors. Little is known about the performance characteristics of SDN Hypervisors. Furthermore, there is a lack of scalable and realistic hypervisor benchmark tools capable of emulating dynamic load scenarios. In this paper, we present an extensible and distributed SDN hypervisor benchmarking framework based on flexible statistical request generators. The framework can be scaled out horizontally to multiple compute nodes that are centrally controlled and reconfigured at runtime. We present preliminary measurements of the CPU resource consumption of a hypervisor in a virtual environment. The results show that the performance characteristics of the hypervisor are different for dynamic load scenarios compared to static benchmarks. Furthermore, the results show that for the same overall request rate, multiple NOS increase the CPU load considerable compared to a single NOS.
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towards a dynamic sdn virtualization layer control path migration protocol
Conference on Network and Service Management, 2015Co-Authors: Arsany Basta, Andreas Blenk, Hassib Belhaj Hassine, Wolfgang KellererAbstract:Virtualization of software defined networks enables tenants to bring their own controller and manage their virtual resources with the full programmability provided by Software Defined Networking (SDN). Distributed SDN Hypervisors are proposed to provide an efficient platform for the virtualization of physical SDN networks. They address the issue of scalability that a centralized hypervisor could suffer from. As virtualization provides the possibility to change virtual SDN networks on run time, a hypervisor layer needs efficient mechanisms to dynamically adapt to the changing requirements. Existing proposals provide only a static configuration setup for their distribution of the hypervisor instances. However, in order to satisfy the dynamics of virtual SDN networks, management protocols are needed to support dynamic changes. In this paper, we propose a control path migration protocol for distributed Hypervisors. Such protocol is needed to support the dynamic adaptation of the virtualization layer. Our protocol is providing the missing procedure that allows a dynamic change of control connections between virtual SDN networks and the tenants' controllers, respectively. We provide a proof of concept implementation for our proposal. Through measurements in a real testbed setup, we show that our protocol is efficient in terms of control latency overhead and provides transparency to the controllers of the virtual SDN networks.
Andreas Blenk - One of the best experts on this subject based on the ideXlab platform.
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sdn Hypervisors how much does topology abstraction matter
Conference on Network and Service Management, 2018Co-Authors: Nemanja Deric, Arsany Basta, Andreas Blenk, Amir Varasteh, Wolfgang KellererAbstract:SDN network Hypervisors realize the virtualization of software-defined networks. They intercept the control path between tenant controllers and their respective virtual Software-Defined Networks (SDN). Over-utilizing SDN hypervisor resources (i.e., CPU) can degrade the control plane performance of the tenants. Although many hypervisor proposals exists, a detailed performance modeling of SDN Hypervisors is missing in literature. A precise modeling of the required SDN hypervisor resources, however, is crucial for predictable and reliable operation of virtual software-defined networks. In this paper, we measure and evaluate how topology abstraction can affect the SDN hypervisor CPU utilization. We consider two topology abstraction cases: the (1) transparent and (2) big-switch abstraction. Our measurements taken from a real testbed indicate that the big-switch abstraction can reduce the SDN hypervisor CPU utilization up to $\sim 4\times $. Further, we evaluate different functions to model the SDN hypervisor CPU utilization based on our measurement results. Our evaluations show that a polynomial function provides the lowest fitting error. Motivated by our measurements, we conduct a first-step investigation of the impacts of topology abstraction on the Virtual Network Embedding (VNE) problem. Our initial simulation-based evaluations indicate that different topology abstraction procedures impact the results of the VNE problem.
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Survey on network virtualization Hypervisors for software defined networking
IEEE Communications Surveys and Tutorials, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Wolfgang KellererAbstract:Software defined networking (SDN) has emerged as a promising paradigm for making the control of communication networks flexible. SDN separates the data packet forwarding plane, i.e., the data plane, from the control plane and employs a central controller. Network virtualization allows the flexible sharing of physical networking resources by multiple users (tenants). Each tenant runs its own applications over its virtual network, i.e., its slice of the actual physical network. The virtualization of SDN networks promises to allow networks to leverage the combined benefits of SDN networking and network virtualization and has therefore attracted significant research attention in recent years. A critical component for virtualizing SDN networks is an SDN hypervisor that abstracts the underlying physical SDN network into multiple logically isolated virtual SDN networks (vSDNs), each with its own controller. We comprehensively survey Hypervisors for SDN networks in this article. We categorize the SDN Hypervisors according to their architecture into centralized and distributed Hypervisors. We furthermore sub-classify the Hypervisors according to their execution platform into Hypervisors running exclusively on general-purpose compute platforms, or on a combination of general-purpose compute platforms with general- or special-purpose network elements. We exhaustively compare the network attribute abstraction and isolation features of the existing SDN Hypervisors. As part of the future research agenda, we outline the development of a performance evaluation framework for SDN Hypervisors.
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Control Plane Latency With SDN Network Hypervisors: The Cost of Virtualization
IEEE Transactions on Network and Service Management, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Johannes Zerwas, Wolfgang KellererAbstract:Software defined networking (SDN) network Hypervisors provide the functionalities needed for virtualizing software-defined networks. Hypervisors sit logically between the multiple virtual SDN networks (vSDNs), which reside on the underlying physical SDN network infrastructure, and the corresponding tenant (vSDN) controllers. Different SDN network hypervisor architectures have mainly been explored through proof-of-concept implementations. We fundamentally advance SDN network hypervisor research by conducting a model-based analysis of SDN hypervisor architectures. Specifically, we introduce mixed integer programming formulations for four different SDN network hypervisor architectures. Our model formulations can also optimize the placement of multi-controller switches in virtualized OpenFlow-enabled SDN networks. We employ our models to quantitatively examine the optimal placement of the hypervisor instances. We compare the control plane latencies of the different SDN hypervisor architectures and quantify the cost of virtualization, i.e., the latency overhead due to virtualizing SDN networks via Hypervisors. For generalization, we quantify how the hypervisor architectures behave for different network topologies. Our model formulations and the insights drawn from our evaluations inform network operators about the trade-offs of the different hypervisor architectures and help choosing an architecture according to operator demands.
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NetSoft - hvbench: An open and scalable SDN network hypervisor benchmark
2016 IEEE NetSoft Conference and Workshops (NetSoft), 2016Co-Authors: Christian Sieber, Arsany Basta, Andreas Blenk, Wolfgang KellererAbstract:Software-defined networking (SDN) introduces a split between the forwarding plane and the control plane of modern network equipment. Furthermore, OpenFlow, as an open interface for SDN, fosters the development of logically centralized network operation systems (NOS). To allow multiple network operation systems accessing the same network, there is the concept of SDN Hypervisors. Little is known about the performance characteristics of SDN Hypervisors. Furthermore, there is a lack of scalable and realistic hypervisor benchmark tools capable of emulating dynamic load scenarios. In this paper, we present an extensible and distributed SDN hypervisor benchmarking framework based on flexible statistical request generators. The framework can be scaled out horizontally to multiple compute nodes that are centrally controlled and reconfigured at runtime. We present preliminary measurements of the CPU resource consumption of a hypervisor in a virtual environment. The results show that the performance characteristics of the hypervisor are different for dynamic load scenarios compared to static benchmarks. Furthermore, the results show that for the same overall request rate, multiple NOS increase the CPU load considerable compared to a single NOS.
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towards a dynamic sdn virtualization layer control path migration protocol
Conference on Network and Service Management, 2015Co-Authors: Arsany Basta, Andreas Blenk, Hassib Belhaj Hassine, Wolfgang KellererAbstract:Virtualization of software defined networks enables tenants to bring their own controller and manage their virtual resources with the full programmability provided by Software Defined Networking (SDN). Distributed SDN Hypervisors are proposed to provide an efficient platform for the virtualization of physical SDN networks. They address the issue of scalability that a centralized hypervisor could suffer from. As virtualization provides the possibility to change virtual SDN networks on run time, a hypervisor layer needs efficient mechanisms to dynamically adapt to the changing requirements. Existing proposals provide only a static configuration setup for their distribution of the hypervisor instances. However, in order to satisfy the dynamics of virtual SDN networks, management protocols are needed to support dynamic changes. In this paper, we propose a control path migration protocol for distributed Hypervisors. Such protocol is needed to support the dynamic adaptation of the virtualization layer. Our protocol is providing the missing procedure that allows a dynamic change of control connections between virtual SDN networks and the tenants' controllers, respectively. We provide a proof of concept implementation for our proposal. Through measurements in a real testbed setup, we show that our protocol is efficient in terms of control latency overhead and provides transparency to the controllers of the virtual SDN networks.
Arsany Basta - One of the best experts on this subject based on the ideXlab platform.
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sdn Hypervisors how much does topology abstraction matter
Conference on Network and Service Management, 2018Co-Authors: Nemanja Deric, Arsany Basta, Andreas Blenk, Amir Varasteh, Wolfgang KellererAbstract:SDN network Hypervisors realize the virtualization of software-defined networks. They intercept the control path between tenant controllers and their respective virtual Software-Defined Networks (SDN). Over-utilizing SDN hypervisor resources (i.e., CPU) can degrade the control plane performance of the tenants. Although many hypervisor proposals exists, a detailed performance modeling of SDN Hypervisors is missing in literature. A precise modeling of the required SDN hypervisor resources, however, is crucial for predictable and reliable operation of virtual software-defined networks. In this paper, we measure and evaluate how topology abstraction can affect the SDN hypervisor CPU utilization. We consider two topology abstraction cases: the (1) transparent and (2) big-switch abstraction. Our measurements taken from a real testbed indicate that the big-switch abstraction can reduce the SDN hypervisor CPU utilization up to $\sim 4\times $. Further, we evaluate different functions to model the SDN hypervisor CPU utilization based on our measurement results. Our evaluations show that a polynomial function provides the lowest fitting error. Motivated by our measurements, we conduct a first-step investigation of the impacts of topology abstraction on the Virtual Network Embedding (VNE) problem. Our initial simulation-based evaluations indicate that different topology abstraction procedures impact the results of the VNE problem.
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Survey on network virtualization Hypervisors for software defined networking
IEEE Communications Surveys and Tutorials, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Wolfgang KellererAbstract:Software defined networking (SDN) has emerged as a promising paradigm for making the control of communication networks flexible. SDN separates the data packet forwarding plane, i.e., the data plane, from the control plane and employs a central controller. Network virtualization allows the flexible sharing of physical networking resources by multiple users (tenants). Each tenant runs its own applications over its virtual network, i.e., its slice of the actual physical network. The virtualization of SDN networks promises to allow networks to leverage the combined benefits of SDN networking and network virtualization and has therefore attracted significant research attention in recent years. A critical component for virtualizing SDN networks is an SDN hypervisor that abstracts the underlying physical SDN network into multiple logically isolated virtual SDN networks (vSDNs), each with its own controller. We comprehensively survey Hypervisors for SDN networks in this article. We categorize the SDN Hypervisors according to their architecture into centralized and distributed Hypervisors. We furthermore sub-classify the Hypervisors according to their execution platform into Hypervisors running exclusively on general-purpose compute platforms, or on a combination of general-purpose compute platforms with general- or special-purpose network elements. We exhaustively compare the network attribute abstraction and isolation features of the existing SDN Hypervisors. As part of the future research agenda, we outline the development of a performance evaluation framework for SDN Hypervisors.
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Control Plane Latency With SDN Network Hypervisors: The Cost of Virtualization
IEEE Transactions on Network and Service Management, 2016Co-Authors: Andreas Blenk, Arsany Basta, Martin Reisslein, Johannes Zerwas, Wolfgang KellererAbstract:Software defined networking (SDN) network Hypervisors provide the functionalities needed for virtualizing software-defined networks. Hypervisors sit logically between the multiple virtual SDN networks (vSDNs), which reside on the underlying physical SDN network infrastructure, and the corresponding tenant (vSDN) controllers. Different SDN network hypervisor architectures have mainly been explored through proof-of-concept implementations. We fundamentally advance SDN network hypervisor research by conducting a model-based analysis of SDN hypervisor architectures. Specifically, we introduce mixed integer programming formulations for four different SDN network hypervisor architectures. Our model formulations can also optimize the placement of multi-controller switches in virtualized OpenFlow-enabled SDN networks. We employ our models to quantitatively examine the optimal placement of the hypervisor instances. We compare the control plane latencies of the different SDN hypervisor architectures and quantify the cost of virtualization, i.e., the latency overhead due to virtualizing SDN networks via Hypervisors. For generalization, we quantify how the hypervisor architectures behave for different network topologies. Our model formulations and the insights drawn from our evaluations inform network operators about the trade-offs of the different hypervisor architectures and help choosing an architecture according to operator demands.
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NetSoft - hvbench: An open and scalable SDN network hypervisor benchmark
2016 IEEE NetSoft Conference and Workshops (NetSoft), 2016Co-Authors: Christian Sieber, Arsany Basta, Andreas Blenk, Wolfgang KellererAbstract:Software-defined networking (SDN) introduces a split between the forwarding plane and the control plane of modern network equipment. Furthermore, OpenFlow, as an open interface for SDN, fosters the development of logically centralized network operation systems (NOS). To allow multiple network operation systems accessing the same network, there is the concept of SDN Hypervisors. Little is known about the performance characteristics of SDN Hypervisors. Furthermore, there is a lack of scalable and realistic hypervisor benchmark tools capable of emulating dynamic load scenarios. In this paper, we present an extensible and distributed SDN hypervisor benchmarking framework based on flexible statistical request generators. The framework can be scaled out horizontally to multiple compute nodes that are centrally controlled and reconfigured at runtime. We present preliminary measurements of the CPU resource consumption of a hypervisor in a virtual environment. The results show that the performance characteristics of the hypervisor are different for dynamic load scenarios compared to static benchmarks. Furthermore, the results show that for the same overall request rate, multiple NOS increase the CPU load considerable compared to a single NOS.
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towards a dynamic sdn virtualization layer control path migration protocol
Conference on Network and Service Management, 2015Co-Authors: Arsany Basta, Andreas Blenk, Hassib Belhaj Hassine, Wolfgang KellererAbstract:Virtualization of software defined networks enables tenants to bring their own controller and manage their virtual resources with the full programmability provided by Software Defined Networking (SDN). Distributed SDN Hypervisors are proposed to provide an efficient platform for the virtualization of physical SDN networks. They address the issue of scalability that a centralized hypervisor could suffer from. As virtualization provides the possibility to change virtual SDN networks on run time, a hypervisor layer needs efficient mechanisms to dynamically adapt to the changing requirements. Existing proposals provide only a static configuration setup for their distribution of the hypervisor instances. However, in order to satisfy the dynamics of virtual SDN networks, management protocols are needed to support dynamic changes. In this paper, we propose a control path migration protocol for distributed Hypervisors. Such protocol is needed to support the dynamic adaptation of the virtualization layer. Our protocol is providing the missing procedure that allows a dynamic change of control connections between virtual SDN networks and the tenants' controllers, respectively. We provide a proof of concept implementation for our proposal. Through measurements in a real testbed setup, we show that our protocol is efficient in terms of control latency overhead and provides transparency to the controllers of the virtual SDN networks.
Aleksander Xhuvani - One of the best experts on this subject based on the ideXlab platform.
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the evaluation of transfer time cpu consumption and memory utilization in xen pv xen hvm openvz kvm fv and kvm pv Hypervisors using ftp and http approaches
Intelligent Networking and Collaborative Systems, 2011Co-Authors: Igli Tafa, Ermal Beqiri, Hakik Paci, Elinda Kajo, Aleksander XhuvaniAbstract:In this paper the authors evaluate the CPU Consumption, Memory Utilization and Transfer Time between 5 Hypervisors XEN-PV, XEN-HVM, OpenVZ, KVM-FV and KVM-PV by using FTP and HTTP approaches. All the results are compared with the Real Environment. From the experimental results, the authors have concluded that OpenVZ and XEN-PV have better performance than other Hypervisors. The worse performance is for KVM Hypervisor. In our paper we have used some scripts in order to evaluate the performance of these Hypervisors
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INCoS - The Evaluation of Transfer Time, CPU Consumption and Memory Utilization in XEN-PV, XEN-HVM, OpenVZ, KVM-FV and KVM-PV Hypervisors Using FTP and HTTP Approaches
2011 Third International Conference on Intelligent Networking and Collaborative Systems, 2011Co-Authors: Igli Tafa, Ermal Beqiri, Hakik Paci, Elinda Kajo, Aleksander XhuvaniAbstract:In this paper the authors evaluate the CPU Consumption, Memory Utilization and Transfer Time between 5 Hypervisors XEN-PV, XEN-HVM, OpenVZ, KVM-FV and KVM-PV by using FTP and HTTP approaches. All the results are compared with the Real Environment. From the experimental results, the authors have concluded that OpenVZ and XEN-PV have better performance than other Hypervisors. The worse performance is for KVM Hypervisor. In our paper we have used some scripts in order to evaluate the performance of these Hypervisors
Seela Veerabhadreswara Rao - One of the best experts on this subject based on the ideXlab platform.
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On Placement of Hypervisors and Controllers in Virtualized Software Defined Network
IEEE Transactions on Network and Service Management, 2018Co-Authors: Bala Prakasa Rao Killi, Seela Veerabhadreswara RaoAbstract:In a virtualized software defined network (VSDN), PACKET_IN messages of switches must pass through the hypervisor in order to reach the corresponding controller. Hence, the latency experienced by a network element is the sum of latency from network element to hypervisor and the latency from the hypervisor to the controller corresponding to the network element. Therefore, the locations of both the Hypervisors and controllers determine the latency of network elements in a virtualized environment. In this paper, we propose a strategy for determining the placement of controllers in a VSDN while fixing the hypervisor(s) in the physical network. We also propose an approach for jointly optimizing the placement of Hypervisors and controllers in a VSDN. The objective is to minimize the worst case latency between the network element and its corresponding controller. Furthermore, we propose a generalized model which can be used not only to optimize the worst case latency, but also to optimize other objectives such as the average latency, the maximum average latency, and the average maximum latency. The proposed problems are formulated as integer linear programs. We evaluated the performance of our proposed strategies using the AT&T network of Internet Topology Zoo and the Internet 2 OS3E topology, and compared with the hypervisor placement problem. Evaluations demonstrate that the proposed methods outperform the existing hypervisor placement approach with respect to the various performance metrics.