Net-Centric Software and Systems I/UCRC

Copyright © 2011 NSF Net-Centric I/UCRC.All Rights Reserved.

High-Confidence SLA Assurance for Cloud Computing Systems and Services

Project Lead: Farokh B. Bastani, I-Ling Yen, Krishna Kavi, and Jeff TianDate: April 7, 2011

2

• Emerging cloud computing paradigm enables– On-demand access to storage, computing, software, and physical resources– Integrated capabilities of a large spectrum of networked services and

resources for realizing tasks that are far beyond current practices Need SLA to enhance cloud system usability and dependability

• Existing SLA (service level agreement) research: Siloed– SLA model: Consider agreement for each QoS aspect independently– Client perspective

• Need to establish SLAs one service at a time, lacking an end-to-end approach for the client task that require composing multiple services/resources

• Consider individual QoS aspects independently, not potential tradeoffs– Provider perspective

• Each provider operates independently, lacks a collaborative concept to globally achieve high SLA assurance while maximizing resource utilization

– No satisfactory solutions to security issues across all layers• Challenges: Develop a comprehensive SLA model and supporting

environment

Problem Description

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Proposed Solution

Local QoS Monitoring

Resource Management

Admission Control

feed

back

SR

RR

RS

S

Provider 1

Local QoS Monitoring

Resource Management

Admission Control

feed

back

SR S

Provider 2

RR

Local QoS Monitoring

Resource Management

feed

back

Provider 3

Admission Control

Local QoS Monitoring

Resource Management

Admission Control

feed

back

Provider N

Service Composer

SLA for first service

SLA for second service. . .

Fail to get agreement

Integrated SLA Monitoring- Agent based distributed monitoring and behavior integration - Rule based approach, formalize SLAs as rules, events as facts, and use reasoning to derive the violation situations - Consider fuzzy violation decision models - Across providers and resource types- Proactive SLA assurance (recovery)

- Perform end-to-end QoS analysis before SLAs May need reservations to avoid new failures - Consider QoS aspects holistically and directly determine the configuration parameters to fully control tradeoffs Improve SLA model to support holistic SLA

Improved SLA protocol:

First d

eterm

ine with

which

providers an

d levels

of QoS

Then prelim

inarily ch

eck th

e

possibilit

y of gett

ing the S

LAs

Finally es

tablish

the S

LAs

client

client

.

.

.

At each provider:- Consider strict & flexible SLAs- Develop optimal resource management and admission control schemes - Formulation: optimization problem with the objective of maximizing the gain, given task completion rewards and violation penalties and the available resources - Admit only if positive gain- Local monitoring and online reconfiguration - Ensure SLAs are satisfied if resources are sufficient; if not, adjust resource decisions

Probabilistic SLAs to collaboratively

get backup resources under failure

or extreme load

Form cloud community

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2011 New Project SummaryHigh-Confidence SLA Assurance for Cloud Computing Systems and Services

Tasks:1. Comprehensive model of cloud SLAs

considering correlations of QoS aspects and end-to-end QoS requirements

2. Integrated SLA monitoring approach across providers and resource types

3. Optimal adaptive strategies for assuring SLAs under normal and failure situations

4. Method of assessing system-level SLAs based on component-level SLAs

5. Layered collaborative approach for optimally achieving global SLA assurance by leveraging resources from multiple cloud domains

Research Goals:1. Improved SLA models and protocols to

facilitate highly dependable and practically usable cloud computing

2. Optimal supporting environment for SLA assurance considering end-to-end QoS and QoS tradeoffs and achieving local as well as global monitoring, resource management, and admission control

Benefits to Industry Partners:1. Advanced cloud technologies to meet specified

SLAs to a high degree of confidence in spite of multiple failures

2. Enable cloud computing to be used for critical applications, including health-care systems, emergency response systems, defense systems, transportation systems, etc.

Project Schedule:

A M J J A S O N D J F M A11 12

Task 1: SLA model

Task 2: Integrated SLA monitoring

Task 3: Optimal adaptive SLA assurance