AN SLA-BASED RESOURCE VIRTUALIZATION APPROACH FOR ON-DEMAND SERVICE PROVISION

Gabor Kecskemeti

MTA SZTAKI

International Workshop on Virtualization Technologies in Distributed Computing

2009

Attila Kertesz

MTA SZTAKI

Presented by: Yun Liaw

Ivona Brandic

TU Vienna

Outline

Introduction SLA-Based Resource Virtualization (SRV)

Architecture Requirements and Solutions to Realize SRV

Agreement Negotiation – Meta Negotiation Service Brokering – Meta Brokering Service Deployment and Virtualization

Case Study Related Works Conclusions and Comments

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Introduction

This paper provides an architecture for SLA-based resource virtualization that provides an solution for executing user applications in Clouds To combine SLA-based resource negotiations with

virtualized resource in terms of on-demand service provision

Most related works focus on either virtualization approaches without considering SLA management, or concentrates on SLA management neglecting the resource virtualization

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Introduction

This paper’s focus: Agreement negotiation Service brokering Deployment using virtualization technology

Contributions of this paper Presentation of a architecture for the SLA-based resource

virtualization and on-demand service provision Description of the architecture including meta-negotiation,

meta-brokering, brokering and automatic service deployment (ASD)

Demonstration of the presented approach based on a case study

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SLA-based resource Virtualization Architecture

User: a person who wants to user a service MN – Meta-Negotiator: mediates between user and meta-

broker that selecting appropriate protocols for agreements; negotiates SLA creation, handles fulfillment and violation

MB – Meta-Broker: to select a broker that is capable of deploying a service with the user needs

B – Broker: interacts with resources and ASD ASD – Automatic Service Deployment: installs the required

service on the selected resource on demand S – Service: the service that users want to deploy and

execute R – Resource: physical machines, on which virtual

machines can be deployed

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Interactions of SRV Components SLA Negotiation:

Step 1: User starts a negotiation for executing a service with certain QoS requirements (specified in a Service Description (SD) with an SLA)

Step 2: MN asks MB, if it could execute the service with the requirement

Step 3: MB matches the requirements to the properties of the available brokers and replies with an acceptance or a different offer for renegotiation

Step 4: MN replies with the answer of MB, step 1-4 may continue for renegotiation until both sides achieve an agreement

:MN:MN

Service request with QoS

requirements

Reply

:User:User

If MB could execute the service?

:MB:MB

Do_MatchAccept or other offerings

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Interactions of SRV Components Service Initiation:

Step 5: User calls the service with the SD and SLA Step 6: MN passes the SD and the possibly transformed

SLA (to the protocol that selected broker understands) Step 7: MB calls the selected Broker with SLA and a

possibly translated SD (to the language of Broker) Step 8: Broker executes the service with respect to the term

of SD and SLA

:MN:MN

Service call

Reply

:User:User

Service call

:MB:MB

Reply

BrokerBroker

Service Execution

Service call

ReplyResourceResource

Agreement Negotiation – Meta Negotiation Meta-Negotiation documents includes:

The pre-requisites to be satisfied for a negotiation Example: authentication method, terms that participants want to

negotiate on The negotiation protocols and document languages for the

specification of SLAs Conditions for the establishment of an agreement

Example: a required third-party arbitrator Meta-Negotiation documents are published into a

searchable registry through which participants can discover suitable partners for conducting negotiations

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Agreement Negotiation – Meta Negotiation Meta-Negotiation Example

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Meta-Negotiation InfrastructureMeta-Negotiation Middleware: 1.Facilitates the publishing of meta-negotiation document2.Integrates with existing service infrastructure3. Delivers information for

negotiation

Service Brokering

Meta-Broker (MB) acts as a mediator between users or higher level tools and environment-specific resource managers (i.e., brokers) To gather broker properties (availability, provided

services, etc.) To interact with MN to create agreements for service

calls To schedule service calls to lower level brokers To forward service calls to the brokers

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Meta-Broker Architecture

Translator: responsible for translating the resource specification defined by the user to the language of the appropriate resource broker

Information Collector (IC): Stores the data of the reachable brokers and the historical data of the previous submissions BPDL: Broker Property Description Language

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Service Brokering Architecture

IS Agent: A component that regularly checks the load of underlying resources of each connected broker and the ASD (to estimate the service invocation time). The data would be stored into IC

MatchMaker (MM): Lists a group of brokers that can provide the service, and rank them based on IC’s data

Interactions of the Components of Meta-Broker during Utilization

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:MB_Core:MB_Core

Service call

:MN:MN :MatchMaker:MatchMaker :InfColl:InfColl:Parser:Parser

Parse

doMatch

:Invoker:Invoker :Broker:Broker

getInfo

Service call Service call

Selected Broker

Service Deployment and Virtualization - ASD Automatic Service Deployment (ASD):

A component that can install the required service on the selected resource on demand

Built on a repository where all master copies (virtual appliance, VA) of deployable services are stored

Allows broker to check if the service is deployed and available. If not, it checks whether any of the resource can deliver the service taking into account of the deployment cost

Monitors the states of the virtual resources and deployed services, and report to the brokers

Workspace Service (WS): to offer virtualization capabilities

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Service Deployment and Virtualization - ASD

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Case Study – Maxillo Facial Surgery Simulation (MFSS) MFSS application facilitates the work of medical

practitioners and provides the pre-operative virtual planning of maxilla-facial surgery

Steps of MFSS1. Mesh generation: is used for generating meshes

necessary for the finite element method simulation2. Mesh manipulation: defines the initial and boundary

conditions for the simulation3. Finite element method (FEM): a fully parallel numeric

technique application usually running on a remote HPC cluster

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Case Study – Maxillo Facial Surgery Simulation (MFSS)

1. Transform the meta-negotiation document into XML-based document

2. The document is passed to meta-broker

3. Meta-broker receives service description (SD) and SLA

1. Matchmaking to select the broker

2. Selected broker receives SD and calls the ASD to deploy the service, or chooses an already deployed, but idle computing service

4. The job is executed and the result are returned to the workflow enactor

5. ASD decommission the service

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Related Work

SLA handling – negotiation, brokering and deployment – in web services and Grid services

Brokering that aims on supporting Grid applications with resources located in different domains

Service deployment solutions that focus on Grid applications

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Conclusions & Comments

Conclusion: An architecture of SLA-based resource virtualization

with on-demand service deployment is introduced Meta-negotiation for generic SLA management Meta-brokering for diverse broker management ASD for resource virtualization in the Cloud

Comments: An architecture-wise paper that does not touch deeper

issues, especially in service deployment section

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