A topology-aware adaptive deployment framework for elastic applications

2017 IEEE International Conference on Communications Workshops (ICC Workshops)

Peuster

et al. 2017

Self Cite

In conventional large-scale networks, creation and management of network services are costly and complex tasks that often consume a lot of resources, including time and manpower. Network softwarization and network function virtualization have been introduced to tackle these problems. They replace the hardware-based network service components and network control mechanisms with software components running on general-purpose hardware, aiming at decreasing costs and complexity of implementing new services, maintaining the implemented services, and managing available resources in service provisioning platforms and underlying infrastructures. To experience the full potential of these approaches, innovative development support tools and service provisioning environments are needed. To answer these needs, we introduce the SONATA architecture, a service programming, orchestration, and management framework. We present a development toolchain for virtualized network services, fully integrated with a service platform and orchestration system. We motivate the modular and flexible architecture of our system and discuss its main components and features, such as function-and service-specific managers that allow fine-grained service management, slicing support to facilitate multi-tenancy, recursiveness for improved scalability, and full-featured DevOps support.

Section: Related Workmentioning

confidence: 99%

SONATA: Service programming and orchestration for virtualized software networks

Dräxler

2017 IEEE International Conference on Communications Workshops (ICC Workshops)

Peuster

et al. 2017

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“…Simple cloud managers like provide the basic functionality to deploy and manage single predefined virtual machines but cannot handle composed services. Other solutions, like OpenStack Heat , Terraform and Application Deployment Toolkit (ADT) , are able to deploy entire services but do not focus on network function‐specific needs. Projects directly focusing on NFV service orchestration can be divided into three categories.…”

Section: Related Workmentioning

confidence: 99%

DevOps for network function virtualisation: an architectural approach

Trans. Emerging Tel. Tech.

Dräxler

Peuster

et al. 2016

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The Service Programming and Orchestration for Virtualised Software Networks (SONATA) project targets both the flexible programmability of software networks and the optimisation of their deployments by means of integrating Development and Operations in order to accelerate industry adoption of software networks and reduce time-to-market for networked services. SONATA supports network function chaining and orchestration, making service platforms modular and easier to customise to the needs of different service providers, and introduces a specialised Development and Operations model for supporting developers.

“…Examples of such a system ranges from Geographical Load Balancing systems (??) to our own Application Deployment Toolkit [34]. They monitor traffic, decide assignments, and reconfigure the dispatching subsystem in time periods.…”

Section: System Designmentioning

confidence: 99%

Response time-optimized distributed cloud resource allocation

Keller

Proceedings of the 2014 ACM SIGCOMM Workshop on Distributed Cloud Computing

2014

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Abstract-A current trend in networking and cloud computing is to provide compute resources widely distributed exemplified by initiatives like Network Function Virtualization. This paves the way for a widespread service deployment and can improve service quality; a nearby server can reduce the user-perceived response times. But always using the nearest server is a bad decision if that server is already highly utilized. This paper investigates the optimal assignment of users to distributed resources -a convex capacitated facility location problem with integrated queuing systems. We determine the response times depending on the number of used resources. This enables service providers to balance between resource costs and the corresponding service quality. We also present a linear problem reformulation showing small optimality gaps and faster solving times; this speed-up enables a swift reaction to demand changes. Finally, we compare solutions by either considering or ignoring queuing systems and discuss the response time reduction by using the more complex model. Our investigations are backed by large-scale numerical evaluations.