lambda scheduling algorithm for file transfers on high-speed optical circuits hojun lee polytechnic...
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Lambda scheduling algorithm for file transfers
on high-speed optical circuits
Hojun LeePolytechnic Univ.
Hua Li and Edwin ChongColorado State Univ.
Malathi VeeraraghavanUniv. of Virginia
Contact: [email protected]
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Outline Background & Problem statement Varying-Bandwidth List Scheduling (V
BLS) Conclusions and future work
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Background
Many optical network testbeds being created for eScience applications Canarie’s Ca*net 4 - Canada Translight – USA SURFnet – Netherlands UKLight – UK
Target applications: Terabyte/petabyte file transfers Remote visualization, computational
steering
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Background These optical networks are circuit-switched Circuit-switched network operation:
Establish a circuit reserve capacity at each switch on end-to-end path
Dedicated resources implies “rate guarantee” Sounds great – but what’s the catch?
Cost, if network resources are not SHARED on some basis Answer: implement dynamic provisioning of circuits
User holds a “lambda” for some short duration and releases for others to use
How “dynamic?” The greater the sharing, the lower the costs Our proposed approach (NSF project called CHEETAH):
Hold “lambdas” only for the duration of file transfers
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Background: Old theory says circuits unsuitable for file transfers
PS: Packet switch CS: Circuit switch
Fixed bandwidth scheme
Capacity C
PS
1
.
.N
2
3
Each transfer gets C/N capacity
1
23
NThe lone remaining transfer enjoys
full capacity C
Capacity C
CS
1
.
.N
2
3
Each transfer is allocated C/N capacity
1
23
N
The lone remaining transfer continueswith capacity allocation C/N
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Our answer to this handicap
Instead of scheduling a “fixed capacity” for the duration of a file transfer -
To take advantage of bandwidth that becomes available subsequent to the start of the transfer -
Schedule varying capacities for different time ranges within the duration of a transfer
Provide sender this schedule at the start of the transfer (i.e., during circuit provisioning) – it adjusts sending rate
Announce schedule to all the circuit switches on the path for an automated reconfiguration of circuits at time range boundaries
How do we predict the time ranges in which more capacity will be available after the transfer starts at the time of circuit setup?
Require users to specify file sizes Scheduler keeps track of allocations already made to
ongoing transfers
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Problem statement
Hence our problem is not how to schedule lambdas for fixed durations, but -
Rather it is how to schedule lambdas for file transfers
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Scheduling requests Specify
File size Maximum rate
File transfers, unlike real-time audio/video, can be allocated “any” capacity; higher the rate, smaller the transfer delay
End host processing, network interface card and disk limitations place an upper bound on the rate allocated for the file transfer
Requested start time Allows users to specify a delayed start time Immediate-request vs. book-ahead calls (pricing)
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VBLS: A Lambda-Scheduling Algorithm for File Transfers
End host applications request lambdas for file transfers by specifying a three-tuple
: file size : a maximum bandwidth limit for the request : the desired start time for the transfer
The scheduler assigns a Time-Range-Capacity (TRC) vector for each transfer
: the start of the kth time range : the end of the kth time range : the capacity allocated for the transfer in the kth time ra
nge.
),,( max reqTRF
F
maxR
reqT
},...,2,1),,,{( kCEB kkkkB
kE
kC
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VBLS: an exampleAssume the available capacity of a 4-channel link is as shown below
F: 5GBRmax: 2 channelsTreq: 50
Per-channel rate: 10GbpsTime unit: 100ms
In 10 time units can transfer 1.25GB
TRC allocated: (50, 60, 1)(60, 70, 2)(70, 75, 2)
Availablecapacity
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VBLS algorithm Identify change points (P1, P2, ..., Pn), in available
capacity function, (t) Find interval [Pi, P(i+1)] in which Treq lies Four cases are possible while allocating resources in
that interval: Remaining file can be fully transferred and (i) Rmax Remaining file can be fully transferred and (i) > Rmax Remaining file cannot be fully transferred and (i) Rmax Remaining file cannot be fully transferred and (i) > Rmax
In each case, we set parameters of a time range: Beginning of time range End of time range Capacity allocated in that time range
In last two cases, decrease remaining file size variable and continue to next interval between change points
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Analysis and simulation
Traffic model: Call arrival process = file transfer
arrival process: Poisson with rate File size F: bounded Pareto distribution
pxk
pk
xkxfX
,
1
)(1
k: lower bound on file size; p: upper bound on file size; : shape parameter: 1.1
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Validation of simulation program with analysis
Simple case: All calls specify same maximum rate,
which is set equal to link capacity C M/G/1 model with ‘G’ being bounded
Pareto Analytical result available
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Result for validation case
File latency: mean waiting time – from Treq until first bit is transmitted
System load
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
System load
File
late
ncy
(sec
)
Analytical model (EQ(2))Simulation
CFE ][
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Sensitivity analysis: Effect of maximum rate
All calls request same Rmax of 1, 5, 10, 100 channels on a link of capacity C=100 channels Mean latency smallest in the 1-
channel case Mean file transfer delay (which is
latency + service time) is smallest in 100-channel case
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Sensitivity analysis: Effect of file size lower bound (k) and upper bound (p)
All calls request same Rmax of 1, 5, 10 channels on a link of capacity C=100 channels Case 1: k=500MB; p = 10GB Case 2: k= 10GB; p = 100GB
File latency is more in Case 2 because variance is higher in Case 2 (shape of bounded Pareto distribution)
Increasing upper bound p, increases variance and hence file latency increases
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Simulation comparison of VBLS against FBLS (Fixed-Bandwidth LS) and PS
Normalized delay (D)
i
iF
i
idiF
D
Calls choose 1, 5 or 10 channels with probability 0.3, 0.3 and 0.4
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Alternate view: throughput
File throughput (y-axis): long-term average of file size divided by transfer delay
System load (x-axis)
1 channel 5 channels 10 channels
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Observation VBLS
Achieves close to idealized PS (infinite buffer) performance
Finite-buffer PS networks need something like TCP – reduces idealized PS throughput levels
Compare with current TCP enhancements under design
which are implementing run-time discovery of available bandwidth to ideally adjust sending rates to match available bandwidth
goal: avoid packet losses and consequent rate drops
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Practical considerations
Extending VBLS scheme to multiple links Clock synchronization & Propagation delay
Staggered schedule Accounting for retransmissions Available capacity function
Cannot be continuous, has to be discrete Wasted resources because of discretization
Cost of achieving PS-like performance Circuit switches now more complex Need electronics to do timer-based reconfigurations
of circuits
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Extensions
Add a second class of requests: Holding time Minimum rate Maximum rate Requested start time
Useful for remote visualization and other interactive applications
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Conclusions and future work
VBLS overcomes a well-known drawback of using circuits for file transfers
fixed-bandwidth allocation fails to take advantage of bandwidth that becomes available subsequent to the start of a transfer
Simulations showed that VBLS can improve performance over fixed-bandwidth schemes significantly for file transfers
Cost: implementation complexity Future work: to include a second class of user requests for lambd
as, targeted at interactive applications such as remote visualization and simulation steering