1. Resource Allocation in Heterogeneous Computing Systems
By Chris Klumph and Kody Willman Advisor: Professor H.J. Siegel

2. Resource allocation in a MMOG
in a massive multiplayer online game (MMOG) multiple users are simultaneously connected at any given time
a heterogeneous system includes
varying computer capabilities
varying communication times
need to implement resource allocation heuristics for this heterogeneous system

3. Part of our problem … … all players connected directly to a MS vs.
Mn-1 Mn
Main Server …
all players connected directly to a MS
vs.
players are connected to a MS directly or through SS M1
SS2 M3 M4 M5
SS6
Mn-1 Mn
Main Server …

4. Goal of Project and Terminology
given 200 players are directly connected to MS
need to create different heuristics
distribute the 200 players between MS and SS
So RTmax time is as low as possible
RTmax
the maximum communication time between computers and MS
heuristic
way to allocate resources
chromosome
mapping of a possible solution of players and SS

5. For this problem Chris has worked on Genitor heuristic
Kody has worked on
Min-Min heuristic

6. Genitor Overview Genitor_matching_scheduling {
initial_population_generation;
ranking;
while(stopping criteria not met)
selection;
crossover;
mutation; }
output best solution found;
selection – selects 2 random parents in the hope of duplicating better chromosomes
crossover – picks 2 random points within chromosomes, and swaps data points in between points
mutation –randomly mutate elements within chromosomes
ranking – determines which chromosome represents the best solution found, inserts into ranked list
stopping criteria – 10,000 iterations with no change in best solution or 10 minutes

7. Chromosome Example Users 1 & 3 connected to SS which is user 26 2
Users 1 & 3 connected to SS which is user 2
Users 4 & 5 connected directly to MS
Users 7, 8 connected to SS which is user 6 4 1 8 5 7 3
Player # 1 2 3 4 5 6 7 8 SS M

8. Initial Population and Ranking
Player # 1 2 3 4 5 6 7 8 M SS 9 10
initial population generation
M – connected to main server(MS) as a player
SS– player is a secondary server
1-8 – player is connected to that SS
randomly generates 200 chromosomes
ranking (R#)
create ranked list based on each chromosome’s RTmax
Each mapping is created durring the initial population phase.
Stopping criteria is 300,000 iterations.

9. Selection and Crossover
two parents
roulette wheel selection
crossover - two point R#
Player # 1 2 3 4 5 6 7 8 M SS 9 10
Point 1
Point 2 R# 1 2 3 4 5 6 7 8 M SS
Choose the parents randomly using Roulette Selection
swap the 3 through 6 portion R# 1 2 3 4 5 6 7 8 M SS

10. Crossover Fixing fixing – line not always valid
Player # 1 2 3 4 5 6 7 8 M SS 9 10
check that all players match up to valid SS or MS R# 1 2 3 4 5 6 7 8 M SS
randomly assign the players to the known SS or to MS
If it was a SS, find all that were connected to it and randomly reassign to another SS (individually)
If you are now connected to a SS that isn’t a -1 (ie invalid) then randomly assign yourself to another valid SS. R# 1 2 3 4 5 6 7 8 M SS

11. Mutation randomly swap numbers 0.1% chance
Player # 1 2 3 4 5 6 7 8 M SS 9 10 11 12
randomly swap numbers
0.1% chance R#
Player # 1 2 3 4 5 6 7 8 M SS 9 10 R# 1 2 3 4 5 6 7 8 M SS
6->7
rank each chromosome, then sort into mapping R# 1 2 3 4 5 6 7 8 9 M SS

12. Repeat and Final Output
Player # 1 2 3 4 5 6 7 8 M SS 9 10 11 12 R#
Player # 1 2 3 4 5 6 7 8 M SS 9 10
drop two lowest-ranking chromosomes
repeat until 10,000 iteration of no change in best solution or 10 minutes
output best solution
at location Rank 1
done

13. Min-Min Overview have 200 players or tasks
run a greedy Min-Min (used as base comparison)
run Phase1
run Phase2
compare completion times
output best solution
considering all unmapped tasks
while(there are unmapped tasks) {
find task with single overall minimum computation plus connection time;
assign task to corresponding machine;
update machines and computation and connection times; }

14. Min-Min Introduction no players connected to MS, only SS1 2 3 4 5 6 7 8 9 10
Type UP
no players connected to MS, only SS
3 types of players
UP – unmapped player
SS – secondary servers
M – mapped to MS
1-10 – player mapped to that SS
find player with minimum connection plus computation time
connect player
update connection and computation times
repeat for all unmapped players P# 1 2 3 4 5 6 7 8 9 10
Type M SS

15. Greedy Min-Min Base start with all users unmapped
randomly pick k users (between 1-10) to be initial SS
finish the mapping with a modified Min-Min heuristic
not able to create more SS than k randomly generated P# 1 2 3 4 5 6 7 8 9 10
Type UP P# 1 2 3 4 5 6 7 8 9 10
Type UP SS P# 1 2 3 4 5 6 7 8 9 10
Type SS M

16. Phase 1 implementation find the user with the largest RTmax
if user is SS or M
no other players connected
remap as player connected to SS with a better RTmax
if user is connect to SS
remap as player to different SS with better connection time or
remap as SS with better connection time
repeat for 1000 iterations or no update P# 1 2 3 4 5 6 7 8 9 10
Type SS M P# 1 2 3 4 5 6 7 8 9 10
Type SS M

17. Phase 2 set up start with the end mapping from Phase 1
find the set of all the SS
from the set of SS find the SS with the largest α
α is highest computation plus highest communication
p is the number of players connected to that SS
µ is the computational constant for that SS
Comm(SS, MS) is the communication time from SS to the MS
α = (p)² x µ + 2 x Comm(SS, MS) P# 1 2 3 4 5 6 7 8 9 10
Type SS M

18. Phase 2 implementation
try swapping all mapped players into the set of SS in the α SS location
remap with the modified Min-Min
if mapped player gives a better round trip time
make that mapped player a SS
repeat 1000 iterations or no improvement
output best solution P# 1 2 3 4 5 6 7 8 9 10
Type SS M P# 1 2 3 4 5 6 7 8 9 10
Type SS M

19. Future Work
continue to modify current heuristics to get better results
could possibly implement other types of heuristics
consider making it a dynamic application where players can join, play, and then leave
budget
have not needed to buy equipment or programs
still have full budgeted amount of $100
sponsors
no sponsors currently
Questions?