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Minimizing Live VM Migration Downtime Using OpenFlow based Resiliency Mechanisms
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7734-1653
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9866-8209
Karlstad University, Faculty of Economic Sciences, Communication and IT, Centre for HumanIT. Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO)ORCID iD: 0000-0002-9446-8143
2016 (English)In: Cloud Networking (Cloudnet), 2016 5th IEEE International Conference on, IEEE, 2016Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2016.
National Category
Computer Sciences
Research subject
Computer Science; Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-47744DOI: 10.1109/CloudNet.2016.17ISI: 000391421700005OAI: oai:DiVA.org:kau-47744DiVA, id: diva2:1068984
Conference
IEEE CloudNet 2016 - 5th IEEE International Conference on Cloud Networking, Pisa, Italy, 3-5 Oct. 2016
Projects
HITS
Funder
Knowledge FoundationAvailable from: 2017-01-26 Created: 2017-01-26 Last updated: 2021-04-19Bibliographically approved
In thesis
1. Towards Seamless Live Migration in SDN-Based Data Centers
Open this publication in new window or tab >>Towards Seamless Live Migration in SDN-Based Data Centers
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Live migration of Virtual Machines (VMs) has significantly improved the flexibility of modern Data Centers (DCs). Ideally, live migration ought to be seamless which in turn raises challenges on how to minimize service disruption and avoid performance degradation. To address these challenges, a comprehensive support from the underlying network is required. However, legacy DC networks fall short to help as they take a reactive approach to live migration procedure. Moreover, the complexity and inflexibility of legacy DC networks make it difficult to deploy, manage, and improve network technologies that DC providers may need to use for migration.

In this thesis, we explore the application of Software Defined Networking (SDN) paradigm for making live VM migration more seamless. Exploiting the characteristics of SDN such as its centralized view on network states, we contribute to the body of knowledge by enhancing the quality of intra- and inter-DC live migration. Firstly, for intra-DC migration, we provide an SDN-based solution which minimizes the service disruption by employing OpenFlow-based resiliency mechanisms to prepare a DC network for migration proactively. Secondly, we improve the inter-DC live migration by accelerating the network convergence through announcing the migration in the control plane using MP-BGP protocol. Further, our proposed framework resolves the sub-optimal routing problem by conducting the gateway functionality at the SDN controller. Finally, with the ultimate goal of improving the inter-DC migration, we develop an SDN-based framework which automates the deployment, improves the management, enhances the performance, and increases the scalability of interconnections among DCs.

Abstract [en]

Live migration of Virtual Machines (VMs) has significantly improved the flexibility of modern Data Centers (DCs). Ideally, live migration ought to be seamless which requires a comprehensive support from the underlying network. However, legacy DC networks fall short to address the challenges of migration due to their inflexible and decentralized characteristics. In contrast, Software Defined Networking (SDN) is a new networking paradigm, which has the potential to improve the live migration thanks to its comprehensive view over the network, flexible structure, and its close integration with DC management infrastructures.

This thesis investigates networking challenges of short and long-haul live VM migration in SDN-based DCs. We propose solutions to make the intra- and inter-DC live migration procedures more seamless. Furthermore, our proposed SDN-based framework for inter-DC migration improves the management, enhances the performance, and increases the scalability of interconnections among DCs.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. p. 25
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:55
Keywords
Data Center, Data Center Interconnection, EVPN, SDN, VM Migration
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70166 (URN)978-91-7063-896-1 (ISBN)978-91-7063-991-3 (ISBN)
Presentation
2018-12-19, Universitetsgatan 2, Karlstad, 09:15 (English)
Opponent
Supervisors
Projects
HITS, 4707
Funder
Knowledge Foundation
Available from: 2018-11-28 Created: 2018-11-19 Last updated: 2019-11-07Bibliographically approved
2. Service Migration in Virtualized Data Centers
Open this publication in new window or tab >>Service Migration in Virtualized Data Centers
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modern virtualized Data Centers (DCs) require efficient management techniques to guarantee high quality services while reducing their economical cost. The ability to live migrate virtual instances, e.g., Virtual Machines (VMs), both inside and among DCs is a key operation for the majority of DC management tasks that brings significant flexibility into the DC infrastructure. However, live migration introduces new challenges as it ought to be fast and seamless while at the same time imposing a minimum overhead on the network. In this thesis, we study the networking problems of live service migration in modern DCs when services are deployed in virtualized environments, e.g., VMs and containers. In particular, this thesis has the following main objectives: (1) improving the live VM migration in Software-Defined Network (SDN) enabled DCs by addressing networking challenges of live VM migration, and (2) investigating the trade-off between the reconfiguration cost and optimality of the Service Function Chains (SFCs) placement after the reconfiguration has been applied when SFCs are composed of stateful Virtual Network Functions (VNFs).

To achieve the first objective, in this thesis, we use distinctive characteristics of SDN architectures such as their centralized control over the network to accelerate the network convergence time and address suboptimal routing problem. Consequently, we enhance the quality of intra- and inter-DC live migrations. Furthermore, we develop an SDN-based framework to improve the inter-DC live VM migration by automating the deployment, improving the management, enhancing the performance, and increasing the scalability of interconnections among DCs.

To accomplish the second objective, we investigate the overhead of dynamic reconfiguration of stateful VNFs. Dynamic reconfiguration of VNFs is frequently required in various circumstances, and live migration of VNFs is an integral part of this operation. By mathematically formulating the reconfiguration costs of stateful VNFs and developing a multi-objective heuristic solution, we explore the trade-off between the reconfiguration cost required to improve a given placement and the degree of optimality achieved after the reconfiguration is performed. Results show that the cost of performing the reconfiguration operations required to realize an optimal VNF placement might hamper the gain that could be achieved.

Abstract [en]

Modern virtualized Data Centers (DCs) require efficient management techniques to guarantee high quality services while reducing their economical cost. The ability to live migrate virtual instances, e.g., Virtual Machines (VMs), both inside and among DCs, is a key operation for the majority of DC management tasks that brings significant flexibility into the DC infrastructure. However, live migration introduces new challenges as it ought to be fast and seamless while at the same time imposing a minimum overhead on the network.

This thesis investigates the networking challenges of short and long-haul live VM migration in Software Defined Networking (SDN) enabled DCs. We propose solutions to make the intra- and inter-DC live VM migration more seamless. Our proposed SDN-based framework for inter-DC migration improves the management, enhances the performance, and increases the scalability of interconnections among DCs.

Moreover, by considering the overhead of VM migration over the network, servers, and quality of service the VM provides, we explore the trade-off between the costs required to change the placement of VMs and the optimality degree of the placement in the DC. Results show that the cost of improving the placement might hamper the gain that could be achieved.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2020. p. 49
Series
Karlstad University Studies, ISSN 1403-8099 ; 2020:1
Keywords
Data Center, Ethernet VPN, EVPN, Live Service Migration, Reconfiguration, SDN, Virtual Network Function, VNF
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-75921 (URN)978-91-7867-073-4 (ISBN)978-91-7867-083-3 (ISBN)
Public defence
2020-02-07, 21A342 (Eva Eriksson lecture hall), Universitetsgatan 2, 651 88, Karlstad, 10:15 (English)
Opponent
Supervisors
Funder
Knowledge Foundation
Available from: 2020-01-16 Created: 2019-12-12 Last updated: 2020-01-16Bibliographically approved
3. Traffic Management in Software-Defined Data Center Networks
Open this publication in new window or tab >>Traffic Management in Software-Defined Data Center Networks
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Traffic management in data centers is paramount to improving network and application performance, thereby improving the quality of service by reducing network congestion, packet loss, and latency. However, the deployment and configuration of traffic management techniques are challenging due to diverse data-center traffic characteristics, large data center topologies, and the interplay of different protocols at the routing, transport, and link layer. Software-Defined Networking (SDN) emerges as a new paradigm towards a centralized network configuration and traffic management by decoupling the control plane from forwarding devices. Despite its holistic view of the network, data centers are commonly interconnected by traditional networks that use standard routing protocols. It is therefore essential to achieve interoperability with legacy systems, end-to-end traffic management, and to avoid the cumbersome, time-consuming, and error-prone configuration process of data-center edge network devices.

In this thesis, we aim to improve traffic management and its configuration for software-defined data center networks. To achieve this objective, we provide novel approaches that enhance the control plane as well as leverage novel concepts of data plane programmability.

At the control plane, we first propose different mechanisms that enable the fast restoration of network connectivity after a virtual machine migration. Second, we suggest a network management automation framework that extends layer 2 connectivity to the tenants' services hosted across geo-distributed data centers. Moreover, we provide high-level policy-based mechanisms that make network configuration and traffic management simpler for data-center operators. At the data plane, we develop MP-HULA that load-balances multipath connections across least-congested paths. MP-HULA leverages advanced data plane mechanisms to rank multiple paths according to congestion metrics and uses that information for fine-grained load-balancing decisions considering transport layer information. To improve flowlet-based load-balancing decisions, we propose FlowDyn, which efficiently estimates round-trip time using programmable telemetry data. Finally, we present pCoflow, an in-network support mechanism that uses advanced programmable scheduling primitives to effectively avoid reordering for data-parallel applications even when there are flow priority changes due to global coflow scheduling updates.

Abstract [en]

Traffic management in data centers is paramount to improving network and application performance, thereby improving the quality of service by reducing network congestion, packet loss, and latency. However, the deployment and configuration of traffic management techniques are challenging due to diverse data center traffic characteristics, large data center topologies, and the interplay of different protocols at the routing, transport, and link layer. Software-Defined Networking (SDN) emerges as a new paradigm towards a centralized network configuration and traffic management by decoupling the control plane from forwarding devices.

In this thesis, we aim to improve traffic management and its configuration for software-defined data center networks by providing novel approaches that enhance the control plane as well as leveraging novel concepts of data plane programmability. At the control plane, we provide solutions such as high-level based policy framework, automation of layer 2 services, and fast restoration of network connectivity for virtual machine migration, that make network configuration and traffic management simpler for data-center operators. At the data plane, we propose approaches to improve load balancing in data centers and an in-network support mechanism to avoid reordering for data-parallel applications even when there are flow priority changes due to global coflow scheduling updates.

 

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2021. p. 69
Series
Karlstad University Studies, ISSN 1403-8099 ; 2021:15
Keywords
SDN, data center, load-balancing, traffic management, EVPN, big data, programmable data plane
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-83671 (URN)978-91-7867-210-3 (ISBN)978-91-7867-220-2 (ISBN)
Public defence
2021-06-03, Zoom, 13:00 (English)
Opponent
Supervisors
Note

Article 8 part of doctoral thesis as manuscript, now published.

Available from: 2021-05-12 Created: 2021-04-16 Last updated: 2021-09-27Bibliographically approved

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Hernandez Benet, CristianAlizadeh Noghani, KyoomarsKassler, Andreas

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