Post on 12-Jan-2016
transcript
LIDS
MIT
Outline
• Motivation
• Simulation Study
• Scheduled OFS
• Experimental Results
• Discussion
LIDS
MIT
Optical Flow Switching Motivation
IP router IP router IP router
WDM WDM WDM
IP router IP router IP router
WDM WDM WDM
IP router IP router IP router
WDM WDM WDM
Without flow switching
Router initiated flows
End-end flows
• OFS reduces the amount of electronic processing by switching long sessions at the WDM layer
– Lower costs, reduced delays, increased switch capacity– Provide specific QoS for advanced services
LIDS
MIT
OFS Motivation (cont)
Flow Size1KB 1MB 100MB10MB
Nu
mb
er
of F
low
s
To
t al B
y te s
Flow Size1MB 100MB10MB1KB
Optical DomainElect. Domain Optical DomainElect. Domain
-Internet displays a “heavy-tail” distribution of connections-More efficient optics => more transactions in optical domain (red line moves left)
LIDS
MIT
Optical Flow Switching Study
• Short-duration optical connections – Access area– Wide area
• Network architecture issues– Connection setup– Route/wavelength assignment– Goal: efficient use of network resources I.e. high throughput
• Previous work: “probabilistic” approaches– Difficulty: high-arrival rate leads to high blocking probability– Problem: lack of timely network state information
• Our proposed solution: Use of timing information in network– Schedule connections– Gather timely network state information
• This demonstration– Demonstrate flow switching– Demonstrate viability of timing and scheduling connections– Investigate key sources of overhead– High efficiency
LIDS
MIT
Connection Setup Investigation
• Key issue:– How to learn optical resource availability?– Distribution problem– “Wavelength continuity” problem makes it worse
• Previous work– Addresses issues one at a time– Assumes perfect network state information– Will these results be useful for ONRAMP, WAN implementation?
• This work– Assesses effects of distributed network state information– Models some current proposals
MP-lambda-S ASON
LIDS
MIT
Methodology
• Design distributed approaches – Combined routing, wavelength assignment– Connection setup
• Baseline flow switching architecture– Requested flows from user to user– Durations on order of seconds– All-optical
• Simulate approaches on WAN topology– End-to-end latency (“time of flight” only)– Approaches: Ideal, Tell-and-Go, Reverse Reservation
• Assess performance versus idealized approach– Blocking probability
LIDS
MIT
Ideal Approach Illustration
A C B
D
-Changers-Changers-Changers
-Changers
A C B
DBidirectionalMulti-fiber Link
Network Infrastructure
“Tell”cntl packet
LLR Routing, Connection Setup
Optical Flow
Assume: Flow Requested from A->B
LIDS
MIT
Tell-and-Go Approach Illustration
A C B
D
Link-stateUpdates Available : 1,2,3Available : 1,2
Available : 2,3 Available : 2,3,4
Link-State Protocol
A C B
D
Optical Flow
Connection Setup
“Tell” Packet - Single wavelength
Assume: Flow Requested from A->B
LIDS
MIT
Reverse Reservation Approach Illustration
A C B
D
Information Packets
A C B
D
Route Discovery
Route Chosen by B
ReservationPacket
Assume: Flow Requested from A->B
Route, Wavelength Reservation
LIDS
MIT
Simulation Description
• Results shown as Blocking Probability vs. Traffic Intensity– Uniform, Poisson flow traffic per node
• Fixed WAN topology
• Parameters:– F = Number of fibers/link– L = Number of channels/link– K = Number of routes considered for routing decisions– U = Update interval (seconds) = Average service rate for flows (flows/second) = Average arrival rate of flows (flows/second) = Traffic intensity. Equal to /
not utilization factor
LIDS
MIT
Simulation Topology
LIDS
MIT
Latency-free Control Network Results (1sec flows)
RR: F=1, L=16, K=10 TG: F=1, L=16, K=10
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LIDS
MIT
Control Network With Latency Results (1sec flows)
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TG, RR: U=0.1, F=1, L=16, K=10
LIDS
MIT
Interesting Phenomenon
• Why is TG performance better than RR?– 1 sec flows and large rho => small inter-arrival times
Smaller than round trip time
– Thus, with high probability, successive flows will see same state (at least locally)
– Increases chance of collision Effect of distribution (latency)
• Why is Rand better than FF?– This is exactly opposite of analytical papers’ claim– Combination of reasons
Nodes have imperfect information FF makes them compete for same wavelengths (false advertisement)
– Not seen in analysis because distribution was ignored
LIDS
MIT
Scheduled OFS in ONRAMP
• Inaccurate information hurts performance– In this case: Simple speed of light– Biggest problem: Core network resources wasted
• Our proposal: Use of timing information to schedule flows– Deliver network information on time to make decisions– Exchange flow-based information– Maximize utilization of core network– Possible small delay for user
• Issues– Can timing be implemented cheaply, scaled?– Can schedules be implemented?– Must make use of current/future optical devices– Low cost
• ONRAMP OFS– Demonstration of scheduled OFS in access-area network– One example of an implementation
LIDS
MIT
Fixed Xponder
Tunable Xponder
Access Node #2
OXC
Router
GE GE
IPFLOW
IP
Control
Xmitter (X)
Fixed Xponder
Tunable Xponder
Access Node #1
Router
OXC
GE GE
IP FLOW
IP
Control
Intermediate Node
OXCOXC
RouterRouter
•
Receiver (R )
Fixed Xponder
Tunable Xponder
Access Node #2
OXC
GE GE
IPFLOW
IP
Control
)
Fixed Xponder
Tunable Xponder
Access Node #1
Router
OXC
GE GE
IP FLOW
IP
Control
Intermediate Node
OXCOXC
RouterRouter
X- R-
OXC Sched OXC Sched
OXC Sched
Scheduling in ONRAMP
LIDS
MIT
• Uses timeslotting and schedules for lightpaths
• X => i busy on output of node i at corresponding slot
OXC Schedule
Slot 1 …..Slot 2 Slot 3
X X
X
X
ONRAMP Connection Setup
LIDS
MIT
-Overheads includes all timing uncertainty
-Efficiency of any scheduled algorithm related to timing uncertainty, and switching/electronic overheads
-Rough efficiency = Flow duration / Flow duration + Overhead
Slot 1
Overhead - Dependent on timing uncertainty
TIMEScheduling OH
Cannot go in next timeslot
Scheduling OH
Can go in next timeslot
Slot 3Slot 2
Algorithm Timeline
LIDS
MIT
Utilizing Link Capacity
• Sending GigE over transparent optical channel– Clock rate 1.244 Ghz– Rate 8/10 coding results in raw bit rate of 995.2 Mb/s
• Payload capacity for UDP– Send MTU-sized packets
9000 bytes Avoid fragmentation
– Headers Ethernet (26 bytes) + IP (20 bytes) + UDP (8 bytes) = 54 bytes Result: 8946 bytes of payload/packet
– Link payload limit 989.2288 Mb/s
• Rate-limited UDP– Input: desired rate– Timed sends of UDP packets achieve desired rates– Demonstrates transparency of OFS channel
LIDS
MIT
Experimental Setup
• OFS implemented in lab
• One second timeslots– Timing overhead negligible
• Routing/wavelength selection– All available wavelengths (currently 14)– Both directions around ring
• Gigabit Ethernet link layer– Flows achieve theoretical maximum link rate ~989 Mb/s
• Rate limited UDP– Unidirectional flows– No packet loss (100s of flows)– Variable rate– Demonstrates transparent use of optical connection
LIDS
MIT
OFS Performance
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LIDS
MIT
Current Performance Limitations
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LIDS
MIT
• Current overhead is 0.10 seconds– Efficiency for one-second flows is therefore 90%– Analysis of overhead reveals possible overhead of Gigabit Ethernet
frame sync Still under investigation
– Switching overhead and timing uncertainty negligible– I.e. scheduling viable, efficient
Current Performance Limitations(cont.)F
low
Req
uest
time
Beg
in S
lot
Scheduling
Command
GBE Sync?
Receiver Laser
Switching
Algorithm Overhead Timeline
Flow begins…………
10ms 150ms100ms