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Topology-Aware Overlay Construction and Server
Selection
Sylvia RatnasamyMark HandleyRichard Karp
Scott Shenker
Infocom 2002
Connections of a node
Introduction
Problem: Inefficient routing in large-scale networks In large-scale overlay networks, each node is logically
connected to a small subset of other participants. Due to the lack of effort to ensure that application-level
connectivity is congruent with underlying IP-level network topology
Basic Idea: Optimize routing paths in network Define a binning scheme whereby nodes partition
themselves into bins Nodes that fall within a given bin are relatively close to one
another in terms of network latency
Outline
Introduction Distributed Binning Topologically-aware construction of overlay
networks Topologically-aware server selection Conclusion
Extracting proximity information Measuments that can be used to derive topological information:
traceroute: intended for network diagnostic purposes, too heavy-weight, excessive load on the network, disabled ICMP at some sites for security
BGP routing table: not directly available for end users, requires privilege or third party service
Network latency: often a direct indicator of network performance, light-weight, end-to-end measurement, non-intrusive manner
s
a
b
c
t
2 sec
7 sec
5 sec
Distributed Binning Goal:
Have a set of nodes independently partition themselves into disjoint “bins”
Nodes within a single bin are relatively closer to one another than to nodes not in their bin
Scheme: A well-known set of machines that act as landmarks on the
Internet Form a distributed binning of nodes based-on their relative
distances A node measures round-trip-time (RTT) to each landmark
and orders landmarks in order of increasing RTT Every node has an associated ordering of landmarks(or
bin)
Distributed Binning Scheme: (Cont.)
After finding ordering, we calculate absolute values of each RTT in ordering as follows We divide the range of possible latency values into a number of
levels. Convert RTT values into level number and obtain a level vector Example:
Level 0 0-100 msLevel 1 100-200 msLevel 2 > 200ms
Node A’s bin becomes “l2l3l1:0 1 2”
Topologically close nodes likely to have same ordering and belong to same bin
l3
l1l2
A
232 ms
117 ms
57 ms
Distributed Binning
Distributed Binning Scheme
Performance of Distributed Binning Even though it is clearly scalable, does it do a reasonable
job? Metric used:
average inter-bin latency = average latency from a given node to all nodes not in its bin average intra-bin latency = average latency from a given node to all nodes in its bin
A higher gain ratio indicates a higger reduction in latency, hence more desirable
tencytra-bin laAverage In
ybin latencterAverage InGain Ratio
Performance of Distributed Binning Datasets or test topologies:
TS-10K and TS-1K: Transit-Stub topologies with 10000 and 1000 nodes respectively. 2-level hierarchy
PLRG1 and PLRG2: Power-Law Random graph with 1166 and 1779 nodes Edge latencies assigned randomly
NLANR: Distributed network of over 100 active monitors Systematically perform scheduled measurement between
each other
Performance of Distributed Binning Other binning algorithms used in experiments:
Random Binning: Each nodes selects a bin at random acts as a lower bound for the gain ratio
Nearest Neighbor clustering: Each node is initially assigned to a cluster itself. At each iteration, two closest clusters are merged into a
single cluster. The algorithm terminated when the required number of
clusters is obtained
_
Performance of Distributed Binning
Experiments:
Effect of number of landmarks (#level=1) Effect of number of levels (#landmarks=12)
Performance of Distributed Binning
Experiments:
Comparison of different binning techniques(#levels=1)
Topologically-aware construction of overlay networks
Two types of overlay networks Structured:
Nodes are interconnected in some well-defined manner(Application-level)
Unstructured: Much less structured like Gnutella,Freenet
Metric for evaluation:
Network Underlying
NetworkOverlay
Latency node-Inter Average
Latency node-Inter AverageretchLatency St
Topologically-sensitive CAN construction
Content-Addressable Network Scalable indexing system for large-scale decentralized
storage applications on the Internet Built around a virtual multi-dimensional Cartesian
coordinate space Entire coordinate space is dynamically partitioned among
all the peers, i.e. every peer possesses its individual, distinct zone within the overall space
A CAN peer maintains a routing table that holds the IP address and virtual coordinate zone of each of its neighbor coordinates
2D CAN Example
x
State of the system at time t
Peer
Resource
Zone
In this 2 dimensional space, a key is mapped to a point (x,y)
Routing in CAN
y
Peer
Q(x,y)
(x,y)
• d-dimensional space with n zones
•Routing path of length:
•Algorithm:Choose the neighbor nearest to the destination
Q(x,y) Query/Resource
key
1/d(d/4)n
Contribution to CAN Construct CAN topologies that are congruent with underlying IP
topology Scheme:
With m landmarks, m! such ordering is possible For example, if m=2, then possible orderings are “ab” and “ba”
We partion the coordinate space into m! equal sized portions, each corresponding to a single ordering Divide the space along first dimension into m portions Each portion is then sub-divided along the second dimension into m-
1 portions Each of these are divided into m-2 portion and so on…
When a node joins CAN at a random point, the node determines its associated bin based-on delay measurement
According to its landmark ordering, it takes place in the correspanding portion of CAN
Gain in CAN using Distributed Binning
Stretch for a 2D CAN; topology TS-1K;#levels=1 Stretch for a 2D CAN; topology PLRG2;#levels=1
Topologically-aware construction of unstructured overlays
Aims much less structured overlay such as Gnutella, Freenet
Focusing on the following general problem in unstructured overlays:
Optimal overlay is NP-hard, so used some heuristic called Short-Long
“Given a set of n nodes on the Internet, have each node picks any k neighbor nodes from this set so that the average routing latency on the resultant overlay is low”
Topologically-aware construction of unstructured overlays
Short-Long Heuristic A node picks its k neighbors by picking k/2 nodes closest to itself
and then picks another k/2 nodes at random Well-connected pocket of closest nodes and inter-connections to
far pockets with random picks
BinShort-Long (Contribution) : A node picks k/2 neighbors at random from its bin and picks
remaining k/2 at random
Current NodeNearby NodesDistant NodesOther Nodes
Gain in Unstructured Overlay using Distributed Binning
Unstructured overlays; TS-10K;#levels=1;#landmarks=12
Topology-aware server selection
Replication of content over Internet gives rise to the problem of server selection Parameter: Server load and distance(in term of Network
Latency)
_Replication Server
Client
Topology-aware server selection Server selection process with distributed binning works as follows:
If there exist one or more servers within same bin as client, then client is redirected to a random server from its own bin
If no server exists within same bin as client, then an existing server whose bin is most similar to client’s bin is selected at random
Compared performance to 3 schemes: Random: Client selects server at random Hotz Metric: Uses RTT measure from a node to well known landmarks to
estimate internode distance (Triangle inequality) Cartesian Distance: Calculates Euclidean distance using level vector of node
and selects the server with minimum distance
Measurement for evaluation:
rverOptimal Se
erverSelected S
Latency
LatencyrecthLatency St
Topology-aware server selection
Comparison of different schemes under following conditions:• 12 landmarks and 3 levels• 1000 servers for TS-10K, 100 servers for TS-1K, PLRG1 and
PLRG2 and 10 for NLANR
Topology-aware server selection-Node Perspective
CDF of latency stretch for NLANR dataCDF of latency stretch for TS-10K data
Conclusion Described a simple,scalable,binning scheme that can be used to
infer network proximity information Nature of the underlying network topology affects behavior of the
scheme It is applied to the problem of topologically-aware overlay
construction and server selection domains Three applications of distributed binning is given:
Structured Overlay Unstructured Overlay Server selection
A small number of landmarks yields significant improvements. Can be referred as network-level GPS system
_
Happy end! Thank you for your patience!