Use cases for policy-based resource management in VNF-FG
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This document describes two use cases for policy-based resource
management in VNF-FG. These two use cases are not covered by two
documents [irtf-nfvrg-resource-management] and [irtf-nfvrg-policy-
based-resource-management]. These two use cases considers service plan
policies in VNF-FG placement and affinity policies in Network
forwarding path update.Keywords:
Resource Management
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"This paper introduces a system for resource management using the concepts of 'process,' 'facility,' and 'event.' Except for the processor no attempt has been made to give serious suggestions for the policy to be followed for resource allocation. However, a basic framework is provided in which a system analyst can express solutions to resource management problems.
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Resource Management System
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Large enterprises operate two or more data centers for scaling and fault tolerance. Each data center maintains a certain degree of autonomy while sharing resources with other data centers. In this paper we describe how policy-based resource management can be used in existing commercial products such that each data center can control when, what, and how to share resources with other data centers.
Data center
Resource Management
Shared resource
Data Sharing
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In this paper we present a complete analysis of dynamic resource allocation in policy-enabled networks. This analysis is carried out throughout both practical and analytical evaluations. Firstly, we present the details of our dynamic resource allocation architecture based on the policy-based management framework. Then, we evaluate, through extensive experimentations on a developed test-bed, the scalability of such architecture in a real environment. Finally, we develop an analytical model for the proposed architecture. This analytical evaluation allows us to confirm our practical analysis and to identify the weakness of such architectures
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To meet the adaptive requirement of the workflow enactment system, this paper presented the architecture of resource dynamic assignment management modules.The workflow resource management method used in HP Company was modified and extended. The priority policy and situation policy were added to the resource management policies that consist of the requirement policy, qualification policy, substitution policy. It facilitates the resource dynamic assignment. Using the policies matching and rewriting, the request can be translated into an SQL sentence. It simplifies HP's method. Along with examples the detailed method of resource dynamic assignment based on the policies matching and rewriting was explained.
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This document specifies problem definition and use cases of NFV
resource management in service chaining for path optimization, traffic
optimization, failover, load balancing, etc. It further describes
design considerations and relevant framework for the resource
management capability that dynamically creates and updates network
forwarding paths (NFPs) considering resource constraints of NFV
infrastructure.
Chaining
Failover
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In this paper, we propose an economic and management framework for autonomic resource allocation in federations. In the proposed approach resource allocation is based on a long-run cost-based pricing scheme. A significant consideration of the proposed approach is that resource sharing among federated domains exhibits substantial externalities or spillovers since decisions on resource levels made by a single domain affect all other network domains and their users. Then, we propose an integrated management framework based on economic-enhanced agents for implementing the proposed economic model.
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Externality
Shared resource
Economic model
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Software upgrades, reconfiguration, and deployment of new services happen so frequently in the carrier-grade VNF-based networks that operators need automated orchestration and change management systems. The current approaches deal independently with each service and concentrate mainly on resource allocation or optimization of the change execution processes. We propose a new Joint Resource Allocation and Scheduling (JRAS) approach, where the orchestrator manages changes, addressing the diverse requirements and dependencies of all services together. These features result in significant gain achieved by JRAS compared to other approaches, as shown by the performed numerical analysis.
Orchestration
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In previous years, many studies have been conducted on grid computing, in which users and resource providers organize various virtual organizations (VOs) to share resources and services. A VO organizes other sub-VOs for the purpose of achieving the VO goal, which forms the hierarchical VO environment. In this paper, we model and formalize the resource allocation problem in hierarchical VOs. Resource providers and VOs agree upon the VO resource sharing policy, such as resource sharing amount and resource usage cost for VOs. We provide the resource allocation scheme of a VO resource broker to minimize the total cost in order to meet a user's job deadline. In addition, we deal with several cost adjustment methods in resource providers to utilize their resources efficiently in hierarchical VOs
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Large data centers usually host many different services on a shared computing infrastructure, for which on-demand resource management is necessary to maximize providers' revenues by meeting service quality targets at least operational cost. This paper presents a novel architecture of autonomic resource management framework based on virtualized service-oriented computing (SOC) environment. A non-linear continuous optimization problem is defined for adaptive resource allocation and a model-based approach is adopted to solve this problem. Different from traditional approaches, the analytic model we established provides probabilistic performance guarantees and considers non-steady-state behavior assisted by admission control. Results of prototype experiments demonstrate that the performance of multiple services has been greatly improved by taking advantage of fine-grained resource sharing, while incurring much lower resource usage cost. Also, differentiated service qualities could be provided to different client classes through our dynamic resource allocation scheme.
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Shared resource
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