Course: Execution Environments for Distributed Computing 6th Presentation (10-15min): Intelligent Placement of Datacenters for Internet Services Source: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5961695

1. EEDC
34330
Execution Intelligent Placement of
Environments for Datacenters for Internet
Distributed Services
Computing
European Master in Distributed
Computing - EMDC
Homework number: 6
Maria Stylianou
marsty5@gmail.com

2. Outline
● Why is Intelligent Datacenter Placement so
important?
● Proposal
● Problem Setup
● Parameters
● Solving the problem
● Solution Approaches
● Evaluation + Selection of Best Approach
● Datacenter Placement Tradeoffs
● Conclusions 2

3. Why is Intelligent Datacenter
Placement so important?
Internet Services are hosted in datacenters
3

4. Why is Intelligent Datacenter
Placement so important?
Datacenter Location
Internet Services
● Response Time
● Costs
● Carbon Dioxide
Emissions
4

5. Why is Intelligent Datacenter
Placement so important?
Datacenter Location Considerations
● Proximity to
● Population centers
Internet Services ● Power Plants
● Response Time ● Source of electricity
● Costs ● Electricity, land,
● Carbon Dioxide water prices
Emissions ● Avg temperatures
5

6. Proposal
● Framework for the datacenter selection process
● Other Approaches for efficiency
● Build a tool
→ selecting datacenter locations automatically
6

7. Problem Setup
An Internet Company wants...
→ Select Locations for datacenters
→ Offer services to Population Centers
while...
→ keeping a minimized overall cost on the
datacenter network ● network latency
→ respecting constraints ●
consistency delay
● availability
7

8. Problem Setup
Important Parameters
● Cost
→ Capital & Operational
● Response Time
→ Latency & #servers
Low
● Consistency Delay
→ Latency from a neighbor
datacenter
● CO2 emissions
● Service Availability High!
→ Level of redundancy 8

9. Problem Setup
Solving the problem
● Large # of potential locations to evaluate
● Non-linear
● No fast solution
● Linear Programming Solvers not applicable
9

10. Solution Approaches
● Simple Linear Programming (LP0)
● Pre-set Linear Programming (LP1)
● Brute Force (Brute)
● Heuristic based on LP (Heuristic)
● Simulated annealing plus LP1 (SA+LP1)
● Optimized SA+LP1 (OSA+LP1)
10

11. Solution Approaches
Evaluation
● Simple Linear Programming (LP0) Cannot be
used by itself
● Pre-set Linear Programming (LP1)
● Brute Force (Brute) → Used for comparison
● Heuristic based on LP (Heuristic)
● Simulated annealing plus LP1 (SA+LP1)
● Optimized SA+LP1 (OSA+LP1)
11

12. Solution Approaches
Evaluation
● Simple Linear Programming (LP0) Cannot be
used by itself
● Pre-set Linear Programming (LP1)
● Brute Force (Brute) → Used for comparison
● Heuristic based on LP (Heuristic)
● Simulated annealing plus LP1 (SA+LP1)
Optimized SA+LP1 (OSA+LP1)
12

13. Datacenter Placement Tradeoffs
● How much does X cost?
● Lower Latency: 50ms – best compromise
>70ms → same cost ($7.8M/month)
● Higher Availability: – Tier II datacenters – best option
– Cheaper to build networks with
less redundant datacenters
● Faster Consistency: – in contrast with lower latency
– depends on # locations 13

14. Datacenter Placement Tradeoffs
● How much does X cost?
● Green Datacenter Network:
– Same latency results with an optimal-cost DC
– Less than $100K more expensive
● Chiller-less Datacenter Network:
– latency > 70ms → Cost reduction by 8%
– latency < 70ms → Not possible without chillers
14

15. Conclusions
● Intelligent Placement mandatory!
→ saves money!
● Linear Programming & Simulated Annealing
Efficient & Accurate Selection Process
15

16. EEDC
34330
Execution Intelligent Placement of
Environments for Datacenters for Internet
Distributed Services
Computing
European Master in Distributed
Computing - EMDC
Homework number: 6
Maria Stylianou
marsty5@gmail.com