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Lecture 9: More Cloud Applications. Xiaowei Yang (Duke University). News: Buffalo as Data Center Mecca. $1.9 billion, at least 200 employees Low-cost electric power, tax incentives, plenty of shovel-ready sites, cool climate. Review. Cloud Computing Elasticity Pay-as-you-go Challenges

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lecture 9 more cloud applications

Lecture 9: More Cloud Applications

Xiaowei Yang (Duke University)

news buffalo as data center mecca
News: Buffalo as Data Center Mecca
  • $1.9 billion, at least 200 employees
  • Low-cost electric power, tax incentives, plenty of shovel-ready sites, cool climate
  • Cloud Computing
    • Elasticity
    • Pay-as-you-go
  • Challenges
    • Security: co-residence, inference
    • Performance
      • Coarse-grained sharing
      • Lack of virtualized interface for specialized hardware
  • Cloud Applications
    • Execution augmentation for mobile devices
    • Energy saving for mobile
    • Energy saving for desktops
    • Disaster recovery
the case for energy oriented partial desktop migration

The Case for Energy-Oriented Partial Desktop Migration

NiltonBila†, Eyal de Lara†, MattiHiltunen, Kaustubh Joshi,

H. Andr´esLagar-Cavillaand M. Satyanarayanan

  • Offices and homes have many PCs
  • But, they areoften left running idle
    • PCs idle on average 12 hours a day
      • “Skilled in the art of being idle” by Nedevschi et al. in NSDI 2009
    • 60% of desktops remain powered overnight
      • “After-hours power status of office equipment in the USA” by Webber, in Energy 2006
why is it important
Why is it important?
  • Dell Optiplex 745 Desktop
  • Peak power: 280W
  • Idle power: 102.1W
  • Sleep power: 1.2W
  • If we put one to sleep when it is idle, the saving is (102.1-1.2)W.
why do we leave desktops on
Why do we leave desktops on?
  • Applications with always on semantics
    • Skype, IM, email, personal media sharing
  • Interspersed activities with idle periods
    • Lunch break
    • Chatting with colleagues
related work
Related work
  • Full VM migration
    • LiteGreen, USENIX 2010 best paper
    • Encapsulate user session in VM
    • When idle, migrate VM to consolidation server and power down PC
    • When busy, migrate back to user’s PC





partial vm migration
Partial VM migration
  • Idle VM only access partial memory and disk state (working set)
  • Migrate only the working set to a server
    • Potentially a cloud server
    • Cloud provider can further aggregate
  • Small migration footprint
  • Client
    • Fast migration
    • Low energy cost
  • Network
    • Reduce bandwidth demand
  •   Server
    • More VMs per server
feasibility study
Feasibility Study
  • Can its desktop save energy by sleeping when an VM runs on the cloud?
  • Does the entire domain save energy by migrating idle sessions by sleeping?
  • Prototyped simple on-demand migration approach with SnowFlock
    • Prepared a VM image, and run the VM
    • After five minutes, used SnowFlock to clone the VM
    • Monitor memory and disk page migration to cloneVM
  • Dell Optiplex 745 Desktop
    • 4GB RAM, 2.66GHz Intel C2D
    • Peak power: 280W
    • Idle power: 102.1W
    • Sleep power: 1.2W
  • VM Image:
    • Debian Linux 5
    • 1GB RAM
    • 12 GB disk
memory request pattern
Memory Request Pattern
  • Spatial locality
    • Pre-fetching
page request interval
Page Request Interval
  • 98% of request arrive in close succession
memory footprint
Memory footprint
  • A cloud node with 4GB of RAM can run ~30 VMs
annual energy savings
Annual Energy Savings
  • No partial migration
open issues
Open issues
  • Can it save cost?
    • Network
    • Cloud Rental
  • Frequent power cycling reduces hw life expectancy and limits power savings
    • Reduce number of sleep cycles and increase sleep duration
    • Predict page access patterns and prefetch
    • Leverage content addressable memory
  • Fast reintegration
    • Big Q: Can it be fast enough so that a user does not suffer a long delay?
  • Policies
    • When to migrate/re-integrate?
    • When does the desktop go to sleep?
    • On re-integration, should state be maintained in the cloud? For how long?
disaster recovery as a cloud service economic benefits deployment challenges

Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges

Timothy Wood and Emmanuel Cecchet, University of Massachusetts Amherst; K.K. Ramakrishnan, AT&T Labs—Research; PrashantShenoy, University of Massachusetts Amherst; Jacobus van derMerwe, AT&T Labs—Research; ArunVenkataramani, University of Massachusetts Amherst

datacenter disasters
Datacenter Disasters
  • Disasters cause expensive application downtime
  • Truck crash shuts down Amazon EC2 site center (May 2010)
  • Lightning strikes EC2 data (May 2009)
  • Comcast Down: Hunter shoots cable (2008)
  • Squirrels bring down NASDAQ exchange (1987 and 1994)
dr fits in the cloud
DR Fits in the Cloud
  • Customer: pay-as-you-go and elasticity
    • Normal is cheap (fewer resources for backup than normal operations)
    • Rapidly scale up resources after disaster is detected
  • Provider: high degree of multiplexing
    • Customers will not fail at once
    • Can offer extra services like disaster detection
what is disaster recovery
What is disaster recovery
  • Use DR services to prevent lengthy service disruptions
  • Data backups + failover mechanism
    • Periodically replicate state
    • Switch to backup site after disaster
dr metrics
DR Metrics
  • Recovery Point Objective (RPO): the most recent backup time prior to any failure
  • Recovery Time Objective (RTO): how long it can take for an application to come back online after a failure occurs
    • Time to detect failure
    • Provision servers
    • Initialize applications
    • Configure networks to connect


    • Have a minimal impact on the performance of each application being protected under failure-free operation
    • How can DR impact performance?
  • Consistency
    • The application can be restored to a consistent state
  • Geographic separation
    • Challenge: increasing network latency
dr mechanisms
DR Mechanisms
  • Hot Backup Site
    • Provides a set of mirrored stand-by servers that are always available
    • Minimal RTO and RPO
    • Use synchronous replication to prevent any data loss
warm backup site
Warm backup Site
  • Cheaply synchronize state during normal operations
  • Obtain resources on demand after failure
  • Short delay to resource provision and applications
cost analysis study
Cost analysis study
  • Compare DR in Colocation center to Cloud
  • Colocation
    • pays for servers and space at all times
  • Cloud DR
    • Pays for resources as they are used
case study 1
Case Study 1
  • RUBiS: an ebay-like multi-tier web application
    • Three front ends
    • One database server
    • Only database state is replicated
cost analysis
Cost analysis
  • 99% Uptime cost (3 days of disaster per year)
case 2 data warehouse
Case 2: Data Warehouse
  • Post-disaster expensive due to high powered VM instance
  • Overall cheaper because 99% Uptime
rpo vs cost tradeoff
RPO vs Cost Tradeoff
  • Flexible
  • Colo has a fixed cost regardless of RPO requirements
cost analysis summary
Cost Analysis Summary
  • Cloud DR’s benefits depend on
    • Type of resources to run application
    • Variation between normal and post-disaster costs
    • RPO and RTO requirements
    • Uptime
  • Cloud is better if post-disaster cost much higher than normal mode
provider challenges
Provider Challenges
  • How to maximize revenue?
    • Makes money from storage in normal case
    • But must pay for servers and keep them available for DR
    • Possible solutions
      • Spot instances (EC2 uses them)
      • Higher prices for higher priority resources
  • Correlated failures
    • Large disasters may affect many
    • Possible solutions
      • Decide provision using a risk model
      • Spread out customers
mechanisms needed for cloud dr
Mechanisms Needed for Cloud DR
  • Network reconfiguration
    • Application must be brought up online after moved to a backup site
    • May require setting up a private business network
  • Security and Isolation
  • VM migration and cloning
    • Restore an application after a disaster is handled
    • Cloud provider does not support VM migration in and out cloud yet
  • Cloud based disaster recovery
    • Can reduce cost
      • Up to 85% from a case study
    • Flexible tradeoff between cost and RPO
  • Next lecture
    • Another cloud application for group collaboration
  • Monday is in fall break
  • Next Wednesday
    • Midterm
    • http://www.cs.duke.edu/courses/fall10/cps296.2/syllabus.html