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Incentivising Resource Sharingin Federated Clouds
Eduardo Falcã[email protected]
Francisco BrasileiroAndrey Brito
José Luis Vivas
2
Challenge
●Promotion of cooperation among selfish individuals in a decentralized context;
●Incentive mechanisms to prevent collaborative peers from defecting from the federation;
●Peers need to take efficient decisions●“To whom should I donate?”●“How much should I donate?”
3
Baseline – Network of Favors
●Network of Favors (NoF)●each peer keeps a local record of the past
interactions with other peers.Peer Provided
FavorsConsumed Favors
Credit
D 300 150 150B 100 55 45E 30 5 25C 15 30 0F 0 200 0
A{
4
Problem Statement
●Whenever there is contention of resources, the collaborative actors are prioritized;
●NoF works fine in these scenarios.
Peer Provided Favors
Consumed Favors
Credit
D 300 150 150B 100 55 45E 30 5 25C 15 30 0F 0 200 0
A{requests
+10
+10+10
+10
+10
free: +20
5
Problem Statement
●When there isn’t contention of resources, some free riders are able to consume the exceeding resources.
●These resources won’t be reciprocated in the future.Peer Provided
FavorsConsumed Favors
Credit
D 300 150 150B 100 55 45E 30 5 25C 15 30 0F 0 200 0
A{requests
0
+10
free: +20
0
00
6
Solution
• Satisfaction-Driven NoF (SD-NoF)– Context: P2P opportunistic desktop
grids;– Low cost for maintenance and
hosting;– Provides all exceeding
resources to maximize the satisfaction of the peers.
• Fairness-Driven NoF (FD-NoF)– Context: P2P federation of
private cloud providers;– High cost due to purchase,
maintenance, energy, hosting, etc;
– Regulates the amount of provided resources in order to guarantee good levels of fairness
probability of being answered level of reciprocity
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Simulation Model
● : number of peers;● : % free riders;● The simulation poceeds in steps;● Collaborators and free riders have the same total
resource capacity (), and the same amount of demand (); ● SD-NoF provides ;● FD-NoF provides
● : probability of consuming;● Colaborators [consuming state, provider state];● Free riders [consuming state], critical case,
factors
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Scenarios
●Designed to assess the different scenarios of contention of resources between collaborators ():
low resource contention
moderate resource contention
high resource contention
requested
provided
factors
Constant n=100; f=75%; steps=10000; C=1Variable and
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SD-NoF
Proposal: FD-NoFcollaborators should be equipped with a control mechanism that enables them to regulate the amount of resources donated
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Peer Provided Favors
Consumed Favors
Credit
D 300 150 150B 100 55 45E 30 5 25C 15 30 0F 0 200 0
Peer Provided Favors
Consumed Favors
Credit Current Fairness
Previous Fairness
D 300 150 150 2 ...B 100 55 45 1.81 ...E 30 5 25 6 ...C 15 30 0 0.5 ...F 0 200 0 0 ...
FD-NoF
●NoF + Feedback Control Loop FD-NoF
A{
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FD-NoF
∆=𝟓% ∙𝑪
A
E
D
C
B
Max(C)
80%
100%
65%
50%
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FD-NoF: satisfaction
Resource contention=0.5Average deterioration: 4%
13
FD-NoF: fairness
Resource contention=0.5Average improvement: 44%
Is it worth sacrificing 4% of satisfaction to increase 44% of
fairness?
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Concluding Remarks
●FD-NoF shows good evidences that achieves its goal:
●Low resource contention● Satisfaction -4%●Fairness +44%
●Moderate and high resource contention: similar results to SD-NoF.
15
Future Work
●Improve the Feedback Control Loop;●Validation of the results in a realistic scenario;
●Fogbow middleware●http://www.fogbowcloud.org/
●EUBrazilCC project: federation of private cloud providers
●http://eubrazilcloudconnect.eu/
