Improving the Scalability of Data
Center Networks
with Traffic-aware Virtual Machine
Placement
Authors:Xiaoqiao Meng, Vasileios
Pappas, Li Zhang
Presented By:Manoj Raj Penmetcha
Introduction
• The paper presents novel approaches to reduce the
latencies and increase
the efficiency of networks by viewing the placement of
VMs within the
topology of the datacenter
• Apart from the standard improvisations on
the network routing algorithms and network topology,
the paper present
approaches to increase the effective bandwidth
between VM pairs with
high data transfer and reduce the latency between
such pairs
Introduction
• Here it uses a 2 Tier approach Algorithm
• First it clusters the slots available on the
physical machines using the switch distance as
the clustering measure and then
cluster the VMs using the cost matrix as the
clustering measure.
• Then the algorithm tries to match the clusters
first and eventually the members within the
matched clusters.
Advantages
• Approach is toward the placement of the VMs
and not towards the scaling of the network
hardware. This is useful where the network
hardware is not being currently used to the full
potential due to bottlenecks.
• The beneficial topology conditions and other
network parameters which would lead to useful
application of the optimization problem are also
studied.
Advantages
• Apart from the solution to the optimization
problem, the effect of traffic models, topology
models such as the Global Traffic Model,
Partitioned Traffic Model are also presented.
Disadvantages
• The paper completely ignore the effect of
network related optimization on the result of
the optimization of placement of VMs.
• The min cut algorithm used for clustering the
slots available on the physical machines is of
high polynomial complexity (O(n^4)) , which is
not ideal for large datacenters.
Disadvantages
• It has been proved that the TVMPP has
polynomial time solutions only for the global
traffic model, but the real traffic model in a
datacenter is a hybrid model varying from the
global traffic model, appropriate optimizations
for a real scenario have not been aptly
discussed
Reference
• Improving the Scalability of Data Center
Networks with Traffic-aware Virtual Machine
Placement.
by
Xiaoqiao Meng, Vasileios Pappas, Li Zhang
IBM T.J. Watson Research Center
19 Skyline Drive, Hawthorne, NY 10532