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1
Design and Analysis of Overlay
Networks
EL 933, Class11
Yong Liu
11/29/2005
2
Outline
! Paper 1: "Application Level Relay for High-bandwidth
Data Transport”,
Yong Liu, Yu Gu, Honggang Zhang, Weibo Gong and
Don Towsley, the First Workshop on Networks for
Grid Applications (GridNets) , October 2004
! Paper 2: "On the Interaction Between Overlay
Routing and Traffic Engineering'',
Yong Liu, Honggang Zhang, Weibo Gong and Don
Towsley, In Proc. of IEEE/INFOCOM 2005
! Re-Cap of All Lectures
3
Elements in Computer Networks
! Performance metrics" throughput
" delay
" reliability
! End Hosts, Routers, Links
! Network Control" routing
o OSPF, MPLS, BGP
" congestion control
o TCP
A
B
4
Application-level Overlay Networks
! routing overlay: RON, Detour
! content distribution: Akamai
! multicast overlay: Overcast
! computing grids
! p2p file sharing
! appl.-level view of network
! appl.-level control
" routes
" services
A D
B C
underlay
overlay
G=(V,E)
A D
B C
5
Yet Another Layer of Control?
! Network control
" network-wide performance
" trade off between performance and
• complexity, reliability, manageability, policies
" imperfect practice: network wide and individuals
! Application-level control
" do it on my own
" on top of existing network control
" improved performance for individuals
• throughput, delay, resilience, services.
" selfish behavior v.s. common good
6
Application Level Relay for High-
bandwidth Data Transport
Yong Liu, Yu Gu, Honggang Zhang,
Weibo Gong and Don Towsley
7
Application-level TCP Relay
A B
R R
R R
R
8
Related Work! “Implementation and Performance Evaluation of
Indirect TCP”, Bakre et al. IEEE Trans. Comput., 46
(3), 1997
! “Split TCP for Mobile Ad Hoc Networks”, Kopparty et
al, Symposium on Ad-Hoc Wireless Networks, 2002
! “ROMA: Reliable Overlay Multicast with Loosely
Coupled TCP Connections”, Kwon et al, INFOCOM04
! “Scalability of Reliable Group Communication Using
Overlays”, Baccelli et al, INFOCOM04
9
TCP Pipeline along End-end Path
!TCP performs poorly
for long-haul data
transfers
" low bandwidth
" inefficient packet
retransmission
" long feedback delay
" multiple congested links
0 1 2 n3R R R R
TCP1 TCP2 TCP3 TCPn
!TCP Pipeline: chain of
sequential TCP
connections
" higher bandwidth
" local recovery of
lost packets
" shorter feedback delay
" isolate congested links10
TCP Pipeline Setup
! Pipeline throughput
" homogeneous case: times faster than end-end TCP
" general case: throttled by slowest segment
! Relay nodes incur processing & memory overhead
! Problem: How many relays needed and where?
" find optimal pipeline organization with m (<=n) relays
" given link statistics (delay, loss) solve dynamic programming
problem bottom-up
0 1 2 n3
11
Evaluation: TCP Pipeline! Dynamic Programming
" optimal TCP Pipeline with m relay nodes, (0<=m<=5)
Number of Relays
Thro
ughpu
t (k
bps
)
0 1 2 63 4 540 80 120 40 40 40
12
Pipelining + Striping
! Striping: employ parallel TCP connections to broaden pipelinebottle-neck
! Striping overhead:
" connection setup/packet reassembly/competition among conn.s
! Optimally organize TCP connections sequentially and in parallel
" how many relays and how many TCP connections on each hop?
" dynamic programming problem
0 1 2 n3
13
Setting up Relays Deviating Underlay Path
! Relay path: path in overlay
graph; one TCP connection
per overlay link.
! Path width: minimum TCP
throughput on overlay links
! View TCP throughput as overlay
link weight, find widest path in G
" solved by variant of Dijkstra
shortest path algorithm
overlay
A D
B C
G=(V,E)
underlay
14
Richer Optimality Criteria?
! Tie in the width of relay paths
" slowest overlay link dominates path width
! Additional metric—path length
" underlay hop count: underlay resource
" overlay hop count: relay overhead
! Multi-metric routing problem
" Trade off between path width and length
" Shortest Widest Path
" Widest Path with Hop Constraint
15
Shortest Widest Relay Path
! Shortest-widest relay path: shortest
among all widest relay paths
" find one widest path,
T: width of widest path
" prune overlay links where TCP
throughout < T
" find shortest path in pruned graph
C
B
D
E
A F
108
6
4
10
16
Widest Relay Path with Hop Constraint
! Limit number of relay hops:
" find widest relay path from source s
to any other node in G with at most m
hops
! Solve with variant of Bellman-Ford
algorithm
" assume knowledge of TCP throughput
between adjacent relay nodes, find
widest m-hop relay paths in m
iterations
" at iteration k (<=m), find widest k-hop
relay paths from s to all other nodes
in G
C
B
D
E
A F
108
6
4
10
m=0
m=1
m=2
m=3,4
17
Shortest Path Satisfying Width
Requirement
! Balance between bandwidth and
length
" link/path bandwidth varies over
time, difference between two
relay paths may be small
" threshold based searching:
shortest relay path satisfying
width requirement
" width threshold can be calculated
from widest path search, use
threshold for prune-search
procedure
C
B
D
E
A F
10
98
4
10
?
18
Evaluation: widest relay path with hop
constraint! Underlay: GT-ITM topology, 50 nodes, 217 edges,
random link loss between 0 and 0.02
! Overlay: randomly picked 20 overlay nodes
! Variant of Bellman-Ford algorithm
relay hops
rela
y th
rupt
. (kb
ps)
balancedrelay path
19
Evaluation: shortest relay path satisfying
width requirement! Previous topology
! Find shortest-widest path
! Gradually relax width requirement, find shortest
width-constrained path
Path Width (kbps)
Path
Len
gth
1
2
34
5
balanced
relay path
20
Conclusions & Open Issues
! TCP Pipelining improves throughput of long-haul data
transport, more responsive congestion control
! Optimal relay path established by multi-metric
application-level routing, trade off b.w. and resource
! Future directions
" implementation in overlay networks
• collect information about underlay networks
• routing calculation/update/maintenance
" experiments in real network environment (PlanetLab)
" other applications: wireless/sensors networks
21
On the Interaction Between Overlay
Routing and Traffic Engineering
Yong Liu, Honggang Zhang,
Weibo Gong and Don Towsley
22
! Underlay Routing" determine routes for all source-destination pairs
" minimize network wide delay, congestion, etc.
Routing in Underlay Network
pair 1: A->B
pair 2: A->C
pair 3: C->BA
C
E
B
D
23
! Overlay Routing" choose routes at appl. level
" generates demands forunderlay to carry
" individually vs. cooperatively
! Advantages" better path: delay, loss,
thrupt.
" more responsive
" get around inter-domainrouting policies
Routing in Overlay Network
A
C
EB
D
A
C
B
24
! Overlay Routing" choose routes at appl. level
" generates demands forunderlay to carry
" individually vs. cooperatively
! Advantages" better path: delay, loss,
thrupt.
" more responsive
" get around inter-domainrouting policies
Routing in Overlay Network
Net1Net1
Net2Net2
Net3Net3
A
C
B
! Selfish overlay behavior " impact on overall network performance?
" impact on underlay traffic performance?
25
Related Work
! “On Selfish Routing in Internet-like Environments”,
L. Qiu, Y. R. Yang, Y. Zhang, and S. Shenker, ACM/SIGCOMM,
August 2003
! "Can ISPs Take the Heat from Overlay Networks?”,
R. Keralapura, N. Taft, C. N. Chuah, and G. Iannaccone,
ACM/HotNets-III, November 2004
26
Interactions Between
Overlay Routing and Underlay Routing
Overlay Routing Optimization
minimize overlay cost
Underlay Routing Optimization
minimize underlay cost
overlay
routes
overlay
traffic
underlay
routes
non.over.
traffic
iterations
! equilibrium: existence? uniqueness?
! convergence? oscillations?
! performance of overlay and underlay traffic?
27
Routing Optimization at Two Levels
X: overlay routes Y: underlay routes
! Optimal Overlay Routing
" performance of overlay users
" delay, loss, and congestion etc.
" determined by routes at two levels
" routes satisfying overlay demands
" overlay level flow conservation
" physically carried by underlay
! Optimal Underlay Routing
" performance of all users
" delay, loss, and congestion etc.
" determined by routes at two levels
" routes satisfying all demands
" underlay level flow conservation
" constrained by link capacities
28
Simulation Study! 14 node tier-1 POP network,
! 3 overlay nodes,
! bimodal traffic demand between node pairs
! both overlay and underlay minimize delay
! use LP-Solve to solve for overlay and underlay routes
29
Simulation Study
iteration iteration
average delay of all users average delay of overlay users
traffic demand 1, with 8.1% overlay traffic
after computing underlay routesafter computing overlay routes
perc
enta
ge %
perc
enta
ge %underlay performance
degraded
overlay performance
improved
30
Simulation Study
iteration iteration
traffic demand 2, with 10.8% overlay traffic
perc
enta
ge %
perc
enta
ge %
after computing underlay routesafter computing overlay routes
underlay performance
degraded
overlay performance
degraded
average delay of all users average delay of overlay users
31
Underlay Perf. Degrad. as Func. of
Fraction of Overlay Traffic
!overlay triggers largest oscillations when it
takes about half of total traffic
user
del
ay inc
reas
e
percentage of overlay traffic32
Game Theoretic Study
!Two players non-zero sum gameOverlay
v.s.Underlay
! Repeated Nash game
! Nash Equilibrium Point (NEP)
33
Overlay Routing Model: selfish routing
A B
C! Overlay user individually finds
minimum delay path
" in equilibrium, equal user delays onactive paths
! Underlay minimizes delay of allnetwork users
" in optimum, equal link delayderivatives
! Equilibrium impossible?
34
Overlay Routing Model: selfish routing
A B
C
routing game converges to INEFFICIENT equilibrium!!
! Overlay user individuallyfinds minimum delay path" in equilibrium, equal user
delays on active paths
! Underlay minimizes delay ofall network users" in optimum, equal link delay
derivatives
! Equilibrium exists!
unique equilibrium
mappings from overlay routes to underlay routes resolve conflict
35
Overlay Routing Model: coordinated
routing
! One entity calculates routes for all overlay users
! It knows underlay topology and background traffic
! Given current underlay routing, it solves for
overlay routes explicitly
A B
C
X(k)?
x(k): overlay’s flow on path ACB after round k
36
! There exists unique NEP x*,
! NEP globally stable: x(k) !x*, from any initial x(0)
! Overlay performance degrades for some x(0)
Convergence of Coordinated Overlay
Routing
iteration k iteration k
Overlay Routing Evolution Overlay Delay Evolution
x(k)
x*x(k)<x(k+1)<x*
dela
y Underlay’s turn
Overlay’s turn
37
! There exists unique NEP x*,
! NEP globally stable: x(k) !x*, from any initial x(0)
! Overlay performance degrades for some x(0)
Convergence of Coordinated Overlay
Routing
Round k Round k
x(k)
x*
Underlay’s turn
Overlay’s turn
BAD INTERACTIO
N!
x(k)>x(k+1)>x*
x(k)<x(k+1)<x*
Overlay Delay Evolution
dela
y
Overlay Routing Evolution“best”
strategy
38
Will More Information Help Overlay?
! Overlay knows underlay network topology and its routingstrategy;
! Stackelberg game strategy for overlay routing
" evaluates each overlay routing by predicting underlaynetwork response;
" chooses the one to minimize overlay cost
! Advantage
" one shot game, no oscillation
" best performance for overlay
! Bi-level programming
" NP-hard
" gradient projection search with random start
39
Conclusions & Open Issues
! Selfish overlay routing degrades performance of
network as a whole
! Interactions between blind optimizations at two
levels may converge to lose-lose situation
! Future work:
" larger topology: analysis/experimentation
" overlay routing and inter-domain routing
" interactions between multiple overlays
" implications on design overlay routing
" regulation between overlay and underlay
40
Overlay: Good or Bad Patch to Internet?
! overlays are selfish" overlay routing degrades perf. of whole network
• unfairness to regular users?
" interactions between blind optimizations at two levels mayconverge to lose-lose situation
• overlay friendly underlay?
! overlays are adaptive" overlays respond fast to congestion/anomaly
• win-win situation?
" overlays make underlay less fragile• conjecture: if applications are able to adapt their routes
through the network, the underlay can be less careful inchoosing “optimal” routes
41
We Covered …! Traffic Analysis
" traffic statistics: packets arrive according to Poisson?
#failure of Poisson (LAN,WAN,WWW): LRD, Self-similarity
" how user behavior affect traffic?
#users rule: arrival, thinking time, pkt. inter-arrival
! End-end path characterization
" estimate e2e delay, loss, throughput
#loss not i.i.d; delay: heavy-tail; wireless loss: multi-path
! Network Tomography
" from edge-based traffic measurements, infer internal link-level loss,delay and utilization
# dispersion: link capacity/available bw/bottle-neck
# correlation: link loss/delay, topology
42
We Covered …
! Anomaly Detection" DDos attacks/worm spreading/link failures
# network telescope, signal analysis, reverse eng.
! P2P Measurement" P2P topology/user behavior/workload
# p2p content distribution, traffic locality, ISP, users
! Traffic Matrix (TM) Estimation" existent and new approaches
# under-determined, estimation, new information
43
We Covered …! Optimal Routing
" optimize routes for single TM
# traffic engineering, OSPF weights
" optimal routing in a changing world
$ papers available…
! Congestion Control
" TCP dynamic models, Active Queue Management (AQM)
# TCPs solve a distributed optimization problem
" closed loop analysis
# network modeled by coupled differential equations
% Overlay Networks
" good patches to Internet?
# improved perf.; underlay less fragile
" bad patches to Internet?
# selfish users; bad interaction44
What is next?
! Student presentation
" 12/06/2005
" 12/13/2005
" ?
! Continuing Study
" independent study/project
" papers
! Feedbacks
" how you like it? how I did?