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GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers

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Apr 16, 2010 GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers Dzmitry Kliazovich ERCIM Fellow University of Luxembourg – PowerPoint PPT presentation

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Title: GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers


1
GreenCloud A Packet-level Simulator of
Energy-aware Cloud Computing Data Centers
Apr 16, 2010
  • Dzmitry Kliazovich
  • ERCIM Fellow
  • University of Luxembourg

2
Outline
  • Data center architectures
  • Two-tier, three-tier, and three-tier high-speed
  • Structure of data center simulator
  • Energy efficiency, simulator components
  • Case study data center simulations

3
Why energy is important?
  • Increased computing demand
  • Data centers are rapidly growing
  • Consume 10 to 100 times more energy per square
    foot than a typical office building
  • Energy cost dynamics
  • Energy accounts for 10 of data center
    operational expenses (OPEX) and can rise to 50
    in the next few years
  • Accompanying cooling system costs 2-5 million
    per year

4
Distribution of data center energy consumption
5
Data center architectures
  • Two-tier data center architecture
  • Access and Core layers
  • 1 GE and 10 GE links
  • Full mesh core network
  • Load balancing using ICMP

6
Data center architectures
  • Three-tier data center architecture
  • Access, Aggregation, and Core layers
  • Scales to over 10,000 servers
  • 8-way ECMP load balancing

7
Data center architectures
  • Three-tier High-Speed data center architecture
  • Increased core network bandwidth
  • 2-way ECMP load balancing
  • 100 GE standard (IEEE 802.3ba) still in works
    since Nov 2007

8
Data center simulator
  • Greencloud is an extension of NS-2 network
    simulator for energy-aware cloud computing
    simulations
  • Provides packet-level simulation dynamics
  • Focused on workload distribution strategies and
    energy consumption models of simulator components
    (servers, switches, links, etc.)

9
Data center simulator
10
Simulator components
  • Servers
  • Responsible for task execution
  • Single-core nodes
  • Preset processing limit in MIPS or FLOPS
  • Supported power management modes
  • DVFS Dynamic Voltage/Frequency Scaling
  • DNS Dynamic Shutdown
  • Both DNS if server is idle, DVFS otherwise

11
Simulator components
  • Servers Energy Model

memory modules, disks, I/O resources
CPU
Idle server consumes about 66 of the peak load
for all CPU frequencies
12
Simulator components
  • Switches
  • Most common Top-of-Rack (ToR) switches typically
    operate at Layer-2 interconnecting gigabit links
    in the access network
  • Aggregation and core networks host Layer-3
    switches operating at 10 GE (or 100 GE)
  • Links
  • Transceivers power consumption depends on the
    quality of signal transmission in cables and is
    proportional to their cost
  • 1 GE links 0.4W is consumed for 100 meter
    transmissions over twisted pair
  • 10 GE links 1W is consumed for 300 meter
    transmission over optical fiber
  • Supported power management modes
  • DVFS, DNS, or both

13
Simulator components
  • Switches Energy Model

Chassis 36
Linecards 53
Port transceivers 11
14
Simulator components
  • Workloads
  • Model cloud user applications (social networking,
    instant messaging, content distribution, etc.)
  • Workload properties
  • Computational MIPS, duration
  • Communicational workload size, its internal and
    external transfers
  • Generation
  • Trace-driven
  • Using random distribution (Exp, Pareto, etc.)

15
Simulation Setup
  • Data center architectures
  • Two-tier (2T), three-tier (3T), and three-tier
    high-speed (3Ths)
  • Simulation parameters
  • Average data center load is 30
  • 1536 computing servers
  • 1, 10, and 100 GE links with 10 ns delay
  • 4500 bytes workloads (3 Ethernet packets)
  • 60 minutes of simulation time

16
Simulation Setup
  • Energy-aware green scheduler

Under-loaded servers, DVFS can be applied
Servers at the peak load
Idle servers, DNS can be applied
17
Evaluation results
  • Distribution of energy consumption in data center

18
Evaluation results
  • Comparison of energy-efficiency schemes

19
Conclusions
  • Energy consumption is becoming a concern in cloud
    computing data centers
  • Developed a packet-level simulator for
    energy-aware data centers
  • Obtained results compare the performance of
    dynamic voltage/frequency scaling (DVFS) and
    dynamic server/network shutdown (DNS) schemes
  • Future work will focus on adding storage area
    network as well as on the development of novel
    workload consolidation and traffic aggregation
    techniques

20
Thank you!
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