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 Tian Date: April 7, 2011

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 2

Proposed Solution 3 Local QoS Monitoring Resource Management Admission Control feedback S R R R R S S Provider 1 Local QoS Monitoring Resource Management Admission Control feedback S R S Provider 2 R R Local QoS Monitoring Resource Management feedback Provider 3 Admission Control Local QoS Monitoring Resource Management Admission Control feedback 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 determine with which providers and levels of QoS Then preliminarily check the possibility of getting the SLAs Finally establish the SLAs 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

2011 New Project Summary 2011 New Project Summary High-Confidence SLA Assurance for Cloud Computing Systems and Services 4 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 A 1112 Task 1: SLA model Task 2: Integrated SLA monitoring Task 3: Optimal adaptive SLA assurance