1. Routing & Architecture
Comparison about:
DCell , PortLand , VL2 ,
BCube , MDCube
Point of views:
Goals , artecheture ,
routing algorithm , fault tolerance ,
broadcast and multicast ,
evaluation and compare,

2. Goals
Comparison about:
DCell , PortLand , VL2 ,
BCube , MDCube

3. Goals DCell PortLand VL2 Scalable + incremental expansion VM migration
Support high huge data centers with uniform high capacity between servers
Fault-tolerance
Adminstrator
not need to configure any switch
Performances isolation between services
High network capacity
Any end host should efficiently communicate with others.
Ethernet layer-2 semantic
No forwarding loop
Failure detection

4. Goals
BCube
MDCube
An architecture model for modular data center (MDC).
Solve the scalability problem on BCube with small cost by increasing the diameter and some change of routing algorithm.
High performance.
For the same number of nodes, cost is significantly lower than BCube.
Robust, graceful performance degradation for both switch/server faults

5. Artecheture
Comparison about:
DCell , PortLand , VL2 ,
BCube , MDCube

6. artecheture
DCell

7. artecheture
PortLand

8. artecheture
VL2

9. artecheture DCell PortLand VL2 artecheture cost high wiring cost
(compare the expensive core switch)
---
diameter
2^(k+1) – 1 6
artecheture

10. artecheture
BCube
Recursively define architecture

11. artecheture
MDCube
Base on the architecture of BCube and some high speed fiber link. Each container is a BCube, and connect them with fiber. Usually one or two dimensions.

12. artecheture
MDCube

13. artecheture BCube MDCube artecheture cost Only need cheap switches,
but need a lot of switches when the number of nodes is very huge.
With the help of fiber, the number of switches is much lower than BCube. If the level of BCube is not high( 2 or 3 ), then the cost will be low even compare to other architecture (FatTree, DCell, etc.)
diameter
2* log p n
p = number of ports in a switch
n = number of nodes
n= p^(k+1)
k = level of Bcube
4k+3+D(2k+3)
k is the level of Bcube
D is the level of MDCube.
artecheture

14. artecheture Diameter Compare Architecture Diameter Balance Tree 2k
Fat-Tree 6
DCell
2^(k+1) – 1
BCube
K + 1

15. Routing Algorithm Comparison about: DCell , PortLand , VL2 ,
BCube , MDCube

16. routing algorithm DCell PortLand VL2 Divide-and-conquer
Two nodes src and dst that are in the same DCell(k) but in two different DCell(k-1)s.
When computing the path from src to dst in a DCell k,
we first calculate the intermediate link (n1; n2) that interconnects the two DCell(k-1)s.
Just as TCP
Agent add the header
routing algorithm

17. DCell routing algorithm Divide-and-conquer
PortLand
VL2
Divide-and-conquer
Two nodes src and dst that are in the same DCell(k) but in two different DCell(k-1)s.
When computing the path from src to dst in a DCell k,
we first calculate the intermediate link (n1; n2) that interconnects the two DCell(k-1)s.
routing algorithm

18. DCell
PortLand
VL2
Just as TCP
routing algorithm

19. DCell
PortLand
VL2
Agent add the header
routing algorithm

20. routing algorithm BCube MDCube
Each packet header contains the routing path of the packet, the relay node don’t have to decide the next node.
One-to-one:
One-to-many:
All-to-all:
One-to-all:

21. BCube routing algorithm MDCube
Each packet header contains the routing path of the packet, the relay node don’t have to decide the next node.
One-to-one:
For node A = (a0,…,ak), B = (b0,…,bk), we can route A to B by changing one bit of the ID each time. Since the ID of the node is at most k+1, the length of the routing path is at most 2( k+1).
There are k+1 parallel path.
One-to-many:
If node A want to send the data to x nodes, and x <= number of ports p, then we can construct a complete graph on these x+1 (including A) nodes by another x nodes as relays.
One-to-all:
Can build (k+1) edge disjoint trees, and use them to broadcast
All-to-all:
Can reach a good Aggregate Bottleneck Throughput (ABT) which is Θ(n)
routing algorithm

22. MDCube routing algorithm BCube One-to-one:
In the container, the routing algorithm is the same as BCube.
When the path cross the container, correct the container ID one-by-one. The hops needed to intermediate the containers are 2D(k+1) + (D+1), D+1 is for the high speed link. This number plus the hop need in the two ends, which is 2*2(k+1), is the maximum hop needed in one routing path.
There are k+1 parallel path.
All-to-all:
Similar to BCube, MDCube has ABT =Θ(n)
routing algorithm

23. Fault Tolerance Comparison about: DCell , PortLand , VL2 ,
BCube , MDCube

24. fault tolerance
DCell
Local-reroute and Proxy, Local Link-state, Jump-up for Rack Failure
PortLand
Multi-rooted tree
VL2
Completely bipartite
BCube
Yes, and has a good result on both switch and server fault.
MDCube
Good because of BCube.

25. fault tolerance - BCube

26. fault tolerance - BCube

27. Broadcast & Multicast Comparison about: DCell , PortLand , VL2 ,
BCube , MDCube

28. broadcast and multicast
DCell :
a sender delivers the broadcast packet to all its k + 1 neighbors when broadcasting a packet in a DCell(k).
PortLand :
nothing special
VL2 :
not mentioned
BCube:
Both can be reached.
Do broadcast by constructing edge disjoint trees.
Do multicast by using some relay nodes.
MDCube:
Similar to BCube.

29. Evalution & Compare Comparison about: DCell , PortLand , VL2 ,
BCube , MDCube

30. evalution and compare DCell :
1. The link failure incurs only 1-second throughput degradation, while the node failure incurs a 5- second throughput outage that corresponds to our link-state timeout value.
2. The aggregate throughput of DCell was about 2 times faster than Tree.

31. evalution and compare PortLand : Convergence time : 70ms (TCP : 200ms)
Scalability : 100ARPs/sec/host nodes  control traffic 400Mbps; Core required : 70
VM migration : throughput drops to zero in ms, fully recovered after 32s

32. evalution and compare VL2 : Uniform high capacity VLB fairness
Performance Isolation
Directory-system performance

33. evalution and compare
BCube:

34. evalution and compare
BCube:

35. evalution and compare
MDCube:

36. evalution and compare
MDCube:

37. evalution and compare
MDCube: