Execution

Environments for

Distributed

Computing

Intelligent Placement of

Datacenter for Internet

Services

EEDC

34

33

0

Master in Computer Architecture,

Networks and Systems - CANS

Homework number: 6

by Arinto Murdopo – arinto@gmail.com

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Problem Statement

Data Center

where? dónde? di mana? oú? waar?

dove? どこですか? πού? 在哪里？어디?

Response time, availability, cost, environmental concerns

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Proposed Solution

Framework

Solve optimization Problem

Produce tool to compare efficiency and accuracy

Characterization

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Framework

Minimize Cost

Efficiently select data center locations

Response Time Consistency Availability

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Solve Optimization Problem

Problem formulation

Approaches: • Simple Linear Programming (LP0) • Pre-set Linear Programming (LP1) • Brute force (Brute) • Heuristic-based on LP (Heuristic) • Simulated Annealing plus LP1 (SA+LP1) • Optimzed SA + LP1 (OSA + LP1)

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Placement Tool

Available Inputs:

MaxS

1/ratioServerUser

MAXLAT

MAXDELAY

MINAVAIL

area of interest

Granularity

existing data center

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Placement Tool

Location-dependent data:

Network backbones: latency data from backbone ISP

Power plants, transmission lines, and CO2 emissions: obtained from DOE

Electricity, land, water and temperature: obtained from DOE as well

Missing data are obtained from neighboring location

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Placement Tool

Datacenter characteristics:

Cooling : CRACs and Water Chillers for cooling

Connection: It costs $500k/mile of transmission line, and $480k/mile of fiber. Amortization of 12 years

Building: Its costs depends of the maximum power

Land: 6 K square feet per Megawatt

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Placement Tool

Datacenter characteristics:

Water: 24K gallons of water per MW per day

Server: Each server costs $2000 (4 years amortization), each interconnect switch costs $20K (4 years amortization)

Staff: $0.05 per Watt per month. $100K per year salary for 1K servers

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Characterization

Characterize 7 locations in US

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Characterization

Evaluate each location with Placement Tools Parameters

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Characterization

Evaluate each location with Placement Tools Parameters

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Broadening The Scope

Distribution of cost assuming 500 potential locations

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Sample Output

Specifications: 1. 60 K servers 2. Latency <= 60 ms 3. Consistency Delay <= 85 ms 4. Minimum Availability = 5 nines

Results Three locations : 1. Seattle(A, 1789 servers) 2. St. Louis (B, 22712 servers) 3. Oklahoma city(C, 5501 servers)

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Evaluation of Chosen Approach

Based on this specification:

1. 60 K servers

2. Latency <= 60 ms

3. Consistency Delay <= 85 ms

4. Minimum Availability = 5 nines

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Overall cost table (in million)

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Evaluation of Chosen Approach

Running Times of Solution Approaches

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Evaluation of Chosen Approach

Solution Quality

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Evaluation of Chosen Approach

Recommended approach:

OSA + LP1, since it provides best tradeoff between running time and search quality

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Exploring Placement Tradeoff

Latency

Latency of 50 ms strikes the best compromise between latency and cost

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Exploring Placement Tradeoff

Availability

It is usually cheaper to build networks out of less redundant datacenters Tier II data centers are the best option

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Exploring Placement Tradeoff

Consistency Delay

Low latency and low consistency are conflicting goals

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Exploring Placement Tradeoff

Green datacenters

Green network is less than $100k more expensive per month than the cost-optimal network when the maximum latency can be relatively high (> 70ms)

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Exploring Placement Tradeoff

Chiller-less data center

Avoiding chillers reduces costs by 8% for max latencies >= 70ms

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Conclusions

• Proposed and implemented optimization framework for automatic data center placement for Internet Services

• Characterized US regions • Evaluated solutions based on the framework

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Questions and answers