charging.ppt

Charging Models for Data Centers

Charging Models for Data Centers

Bhuvan UrgaonkarThe Penn State University

Bhuvan UrgaonkarThe Penn State University

Data CentersData Centers• Clusters of compute and storage

servers connected by high-speed nets• Resources made available to

applications• Charge the applications for these

resources• Applications might have clients that they

charge

• Clusters of compute and storage servers connected by high-speed nets

• Resources made available to applications

• Charge the applications for these resources• Applications might have clients that they

charge

Charging in a Data Center


• Between data center & application provider• Lease out fixed # servers (over-provision)• Fixed monthly rate (e.g., yahoo Web hosting)• Performance-based charging (mostly research prototypes)• Usage-based (e.g., Sun Grid)

• Between application provider & clients• Fixed monthly rate (possibly with multiple classes)• Transaction granularity (roughly same as usage-based)

• Between data center & application provider• Lease out fixed # servers (over-provision)• Fixed monthly rate (e.g., yahoo Web hosting)• Performance-based charging (mostly research prototypes)• Usage-based (e.g., Sun Grid)

• Between application provider & clients• Fixed monthly rate (possibly with multiple classes)• Transaction granularity (roughly same as usage-based)

Classification of Charging Models

Classification of Charging Models

• Flat-rate• Usage-based• Flat-rate + Usage-based• Performance-based• Bidding-based

• Flat-rate• Usage-based• Flat-rate + Usage-based• Performance-based• Bidding-based

Flat-rate ChargingFlat-rate Charging• Local phone service, cable connection• (+) Billing can not get easier• (-) Consumer: Why should I pay even

when I was on vacation?• (-) Provider: Could I have improved my

revenue by charging based on usage?

• Local phone service, cable connection• (+) Billing can not get easier• (-) Consumer: Why should I pay even

when I was on vacation?• (-) Provider: Could I have improved my

revenue by charging based on usage?

Usage-based ChargingUsage-based Charging• Electricity• Actually rate fluctuates!• Service interrupted deliberately sometimes

• Long-distance phone• Sun Grid: $1/CPU-hour• There should be a way for the consumer

to verify its usage• E.g., Electricity meters at our homes

• Electricity• Actually rate fluctuates!• Service interrupted deliberately sometimes

• Long-distance phone• Sun Grid: $1/CPU-hour• There should be a way for the consumer

to verify its usage• E.g., Electricity meters at our homes

Flat-rate + Usage-basedFlat-rate + Usage-based

• Cell phones• 400 day-time minutes for free• Usage-based beyond that

• Cell phones• 400 day-time minutes for free• Usage-based beyond that

Performance-based ChargingPerformance-based Charging

• Service providers like AT&T, Sprint guarantee average delays in the backbone

• For data centers• Difficult for the data center to translate given

performance into resources• Workloads vary, applications are complex

• Desirable by application provider• Caveat: How do I know what response time my

clients are experiencing?

• Service providers like AT&T, Sprint guarantee average delays in the backbone

• For data centers• Difficult for the data center to translate given

performance into resources• Workloads vary, applications are complex

• Desirable by application provider• Caveat: How do I know what response time my

clients are experiencing?

Bidding-based ChargingBidding-based Charging

• eBay• Clients bid till a pre-decided time• Highest bidder gets to buy• Winning bidder can not back down• Open-bid: You see what others are

doing• Closed-bid: You don’t see what others

are doing

• eBay• Clients bid till a pre-decided time• Highest bidder gets to buy• Winning bidder can not back down• Open-bid: You see what others are

doing• Closed-bid: You don’t see what others

are doing

Bidding-based ChargingBidding-based Charging• (+) Provider: This seems to maximize

revenue• (-) Provider: Has to provide bidding

mechanism• Scalability may be a problem

• (-) Consumer: I have no guarantees; some rich guy can always shoot me down!

• (-) Consumer: Outcome known only at the end of the bid• Have to wait till then to make any decisions

• (+) Provider: This seems to maximize revenue

• (-) Provider: Has to provide bidding mechanism• Scalability may be a problem

• (-) Consumer: I have no guarantees; some rich guy can always shoot me down!

• (-) Consumer: Outcome known only at the end of the bid• Have to wait till then to make any decisions

Possible Factors Governing the Choice of Charging ModelPossible Factors Governing

the Choice of Charging Model• Ease of monitoring and accounting• Abundance of resource• Competition for the resource

• Ease of verifying/proving resource usage• Dependencies between various

resources being bought (bidding)• Different levels of desirability of the

resource among the consumers

• Ease of monitoring and accounting• Abundance of resource• Competition for the resource

• Ease of verifying/proving resource usage• Dependencies between various

resources being bought (bidding)• Different levels of desirability of the

resource among the consumers

Interlude: Differentiated Service

Interlude: Differentiated Service

• When does it make sense to have multiple classes?

• What decides the priority scheme/scheduling discipline?

• When does it make sense to have multiple classes?

• What decides the priority scheme/scheduling discipline?

Two Aspects of the Charging ProblemTwo Aspects of the Charging Problem

• Charging Model• Economics Problem

• Accounting and Verification Mechanism• Systems Problem









Charging in a Data Center• Which model is suitable?

• Apps are interested in performance metrics• Data center would prefer usage-based charging• What about bidding for resources?

• What does the choice of model depend on?• Abundance, competition, peace of mind?• Got to be revenue maximization, right?

• How to charge for the usage of multiple resources?• CPU, disk, network, …

• Which model is suitable? • Apps are interested in performance metrics• Data center would prefer usage-based charging• What about bidding for resources?

• What does the choice of model depend on?• Abundance, competition, peace of mind?• Got to be revenue maximization, right?

• How to charge for the usage of multiple resources?• CPU, disk, network, …






Two Aspects of theCharging ProblemTwo Aspects of theCharging Problem





Two Systems Requirements for Enabling Charging

Two Systems Requirements for Enabling Charging

• Accounting• Resource provider should be able to

monitor and account resource usage• Verification• Resource consumer should be able to

verify its own resource usage• Ability to dispute provider’s claims

• Accounting• Resource provider should be able to

monitor and account resource usage• Verification• Resource consumer should be able to

verify its own resource usage• Ability to dispute provider’s claims

AccountingAccounting

• Well studied by OS and networks communities• Resource containers from Rice

University

• Mostly an engineering exercise• Does the problem become any harder

in a virtualized hosting environment?

• Well studied by OS and networks communities• Resource containers from Rice

University

• Mostly an engineering exercise• Does the problem become any harder

in a virtualized hosting environment?

VerificationVerification• Remember: App doesn’t trust the data

center• Auditing: Instead of verifying resource usage

at all times, the consumer does it sometimes• The provider should not be able to predict or

detect an audit• Audit at random

• Provider and consumer should agree to the auditing process• Involve a third party that both trust• The data center also doesn’t trust the application!

• Failing an audit is a violation of SLA

• Remember: App doesn’t trust the data center

• Auditing: Instead of verifying resource usage at all times, the consumer does it sometimes• The provider should not be able to predict or

detect an audit• Audit at random

• Provider and consumer should agree to the auditing process• Involve a third party that both trust• The data center also doesn’t trust the application!

• Failing an audit is a violation of SLA

Auditing in a Data Center:

Exhaustive Profiling


Exhaustive Profiling• The auditor uses extensive profiling

to identify resource usage to performance mapping for all possible workloads

• (+) The data center can not figure out it is being audited

• (-) Such profiling might be prohibitively expensive

• The auditor uses extensive profiling to identify resource usage to performance mapping for all possible workloads

• (+) The data center can not figure out it is being audited

• (-) Such profiling might be prohibitively expensive


Selective Profiling


Selective Profiling• The auditor sends well-profiled probes and

observes their performance• (+) No need for extensive/exhaustive profiling• (-) Data center might identify probes• Camouflage needed

• (-) Not trivial to construct probes whose performance is independent of the rest of the workload

• The auditor sends well-profiled probes and observes their performance

• (+) No need for extensive/exhaustive profiling• (-) Data center might identify probes• Camouflage needed

• (-) Not trivial to construct probes whose performance is independent of the rest of the workload

Auditing in a Data Center:Self-Monitoring

Applications

Auditing in a Data Center:Self-Monitoring

Applications• Assume it is possible to modify

the application• Can the application monitor its

own resource usage?• Can not trust the underlying

OS/VMM

• Assume it is possible to modify the application

• Can the application monitor its own resource usage?• Can not trust the underlying

OS/VMM

Self-Monitoring Application

Self-Monitoring Application

• Idea: We add a special auditing code (AC) to the application• … for (i=0; i < 1000000; i++); …• At a randomly chose time t1, the application

sends a message to the auditor• The application jumps to AC and starts

executing it• The auditor ACKs the message• The application receives the ACK at time t2

and determines t2-t1, compares it with expected time to reach the current value of i

• Idea: We add a special auditing code (AC) to the application• … for (i=0; i < 1000000; i++); …• At a randomly chose time t1, the application

sends a message to the auditor• The application jumps to AC and starts

executing it• The auditor ACKs the message• The application receives the ACK at time t2

and determines t2-t1, compares it with expected time to reach the current value of i

Problems with Self-Monitoring Applications


• The execution time of AC depends on what other apps are doing• Not a problem: data center expected to

guarantee lower bounds

• Unpredictable delays in the Internet• Send multiple probes and take average• The auditor could record probe reception times

and try to adjust for network delays

• The execution time of AC depends on what other apps are doing• Not a problem: data center expected to

guarantee lower bounds

• Unpredictable delays in the Internet• Send multiple probes and take average• The auditor could record probe reception times

and try to adjust for network delays



• How to ensure data center can not identify a msg to auditor or the execution of AC?• Msg to auditor and ACK should look like normal

requests and responses• Giveaway: Data center observes that the application

has become CPU-intensive suddenly• Not a problem if the app becomes CPU-intensive when

serving its normal workload• Need to ensure that the CPU usage during the execution

of AC is indistinguishable from that when serving normal workload• E.g., Running a while loop that lasts 30 min would be a bad

idea

• How to ensure data center can not identify a msg to auditor or the execution of AC?• Msg to auditor and ACK should look like normal

requests and responses• Giveaway: Data center observes that the application

has become CPU-intensive suddenly• Not a problem if the app becomes CPU-intensive when

serving its normal workload• Need to ensure that the CPU usage during the execution

of AC is indistinguishable from that when serving normal workload• E.g., Running a while loop that lasts 30 min would be a bad

idea

Design Issues: Self-Monitoring Applications

Design Issues: Self-Monitoring Applications

• What is the right observation period? How many observations should be made?

• What about other resources?• Network bandwidth perhaps similar to CPU• Memory and disk bandwidth much harder!

• What is the right observation period? How many observations should be made?

• What about other resources?• Network bandwidth perhaps similar to CPU• Memory and disk bandwidth much harder!

SummarySummary• Charging in data centers seems like

an important problem to address• We can break-down the charging

problem into• Charging model: Economics problem• Accounting and verification: Systems

problems

• Many interesting open issues!

• Charging in data centers seems like an important problem to address

• We can break-down the charging problem into• Charging model: Economics problem• Accounting and verification: Systems

problems

• Many interesting open issues!

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charging.ppt