Virtual migration cloud

Supporting Seamless Virtual Machine Migration Via Named
Data Networking In Cloud Data Center
RUITAOXIE,YONGGANG WEN, XIAOHUAJIAANDHAIYONGXIE
IEEE JOURNAL(DEC 2015)
Presented by:
Shalini Toluchuri
MTech CSE
150913025

Contents
1. Introduction
2. Related works
3. Named –service framework in DCN
4. Named-service routing protocol
5. Virtual machine migration policy
6. Performance optimization
7. Performance evaluation
8. Conclusion
9. References
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Introduction
 Virtualization technology: physical resources are partitioned and multiplexed, has been introduced to tackle the low-utilization
problem in datacenters.
 Virtual machine (VM), can be dedicated to a particular application, and virtual machine migration can be used to consolidate VMs
from under-utilized physical machines in order to reduce the energy cost of data centers.
 Live migration: a VM is migrated while its service is running resulting in service interruptions.
 Offline migration: a VM is migrated after it is shut down and assigned with a new IP address.
 NAMED DATA NETWORKING (NDN): Identify the communication with a VM via the name of the service running on it rather
than its network address. The routing is directed via the service name supporting an interruption-free VM migration.
1. propose a named service routing protocol.
2. propose a VM migration policy to support interruption-free service access.
3. conduct analyses and simulations to verify the benefits.
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Related works
1. Adapts the existing mobile IP solution, to VM migrations in which all traffic to and from the migrated VM must
traverse a home agent in the source subnet but it introduces packet delivery delay and also results in excessive
network traffic.
2. Uses two addresses to solve the problem: an IP address used for identifying a VM and a location-specific address
used for routing to a VM. It also takes some time to update the binding information in the central proxy .During
the updating time, the traffic may be routed with outdated binding information.
3. Adopts service names to access applications in DCN(Dynamic Circuit Network). This approach needs to maintain
a binding between a service name and a list of network addresses of servers in a dedicated server. Here,
a) first packet of each flow is sent to a service router to resolve the service name,
b) following packets are routed via the resolved network address.
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3. Named –service framework in DCN
• 3.1 Named Data Networking: A Prime
NDN packets: interest and data.
NDN routing protocol. Each routing node maintains three data structures: the forwarding information
base (FIB), the pending interest table (PIT) and the content store.
Procedure:
1. Checks whether there is a matching data in its content store.
2. If there is a matching PIT entry, then the incoming interface of current request will be added to the
list of incoming interfaces in this PIT entry.
3. If there is a matching FIB entry, then the node forwards the interest packet to the interface
determined by a particular forwarding policy.
4. If there is no matching for this interest packet, then it is discarded.
5. Data packet is returned to consumers following the reverse path of the corresponding interest packet.
When a routing node receives a data packet, it looks up its PIT with the data name.
6. If a matching PIT entry is found, the node sends the data packet to a list of interfaces in the entry.
Otherwise, the data packet is discarded.
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• 3.2 Design Rationale
 Applications in DCN require efficient managements, such as VM migration, load balancing and
caching. NDN can provide a systematic solution to address these issues.
 DCN allows efficient network operations, due to its regular topology
NDN enables maintaining communication in dynamic environments, so the authors propose a named-
service framework for DCN. This service is identified by a location-independent name and is accessed
via its name instead of the network address of its host VM. Therefore, clients can access the service
regardless of where VMs are hosted or migrated.
NDN framework can provide robust security and performance improvement by leveraging the features
of data-based security and data caching.
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• 3.3 Named-Service Framework in DCN
Framework has two components:
• i) Data center: comprises a named-service routing protocol rendering the service to the requests and a
VM migration policy supporting the VM migrations
• ii) Service gateways: Translates the IP-based external traffic into the named-service framework.

Two types of traffic in DCN:
1) Traffic flowing between an
external client and an internal VM,
2) Traffic flowing between two
internal VMs
Fig. 1. Named-Service Framework in DCN.
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• 3.4 Design Challenges
• an efficient and robust routing protocol,
• a flexible migration policy - link and node failures,
• performance optimization-to avoid link congestions
• Solution: propose a distributed load balancing algorithm to distribute requests across
multiple VMs and multiple paths.
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4.Named-service routing protocol
• Control message protocol to maintain routing information at routing nodes to improve
the robustness of the routing protocol under link and node failures.
Packet Format
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Routing Data Structures
• FIB consists of the service name and multiple outgoing interfaces for each service name. For each pair
interface, the FIB entry has a capacity value. It is used for a distributed load balancing algorithm.
• PRT is used to maintain an entry for every pending
request packet, so that every response packet can be returned to
the client in a reverse path.
• The Cache Store is used to cache the response data.
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Control Message and FIB Update
• Via the control messages, a VM can report service starting, service stopping and service capacity
updating.
• Once a switch receives a control message, it proceeds two steps:
1) updates the FIB;
2) updates and forwards the message.
• It looks up a FIB entry by matching the entry’s service name with the one carried in the message and
matching the entry’s interface with the one from which the message is received, respectively.
• If any entry is not found, then a new FIB entry is created and added into FIB.
• Switch calculates the total capacity of the VMs that have this service name and are reachable through this
switch. It sums up all capacity values of this service name in its FIB.
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Forwarding Process
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Fig. 4. The flowchart of handling a request packet
Fig. 5. The flowchart of handling a response packet

Mechanism of Route Learning
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Fig. 7. The flowchart of handling a request NACK packet.
Fig:6 An example of routing a request when a link fails

5.Virtual machine migration policy
VM Migration Phases
• Three sequential phases:
• 1) Push phase.
• The source VM continues running while certain pages are pushed across the network to the destination.
2) Stop-and-copy phase.
The source VM is stopped, pages are copied to the destination VM, then the new VM is started.
• 3) Pull phase.
• The new VM executes and, if it accesses a page that has not yet been copied, this
• page is pulled across the network from the source VM.
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 VM Migration Policy
• Rules:
1) At the beginning of the push phase, the source VM sends a service stopping message to stop
receiving requests.
2) The source VM does not stop, that is, does not start the stop-and-copy phase, until it responses all
waiting requests in its queue .
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Fig. 8. The VM migration policy in named-service framework

 Performance Analysis
treq denote the time when an external request is dispatched by a gateway.
tmig denote the time when the migrated VM sends the service stopping message.
d denote the single-hop transmission delay
• the first condition requires that treq + 3d ≥ tmig+d and the second condition requires that treq+2d< tmig+2d and
request incurs a request NACK at a VM if
and a request incurs a request NACK at an aggregation switch if
• Thus, the requests dispatched during the period [tmig-4d; tmig+2d] with a length of 6d may incur the request
NACKs.
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Fig.9. An example of a request incurring a request
NACK at the layer of switch
Fig. 11. The arriving time of a request (Req) and a
service stopping message (StopMsg) at each layer of
nodes.

 Performance in IP-Based Networks
• The IP address is used for identifying a VM, while the location-specific address is used for routing to a
VM.
• In IP-based networks, the route is predefined so when a request arrives at the old location of a migrated
VM, if this VM has stopped receiving new requests, then the request could neither be responded by the
migrated VM nor be routed to another serviceable VM.
• The performance gain of our method is significant when the request load is heavy. It is particularly true
when VM migrations occur across subnets.
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6. Performance optimization
• Algorithm is based on the field of capacity maintained in FIB. In a FIB entry <service name, interface,
capacity>
• The load-balancing decision for a service at a switch can be formulated as an optimization problem.
• Let l =the request load (the average number of requests arriving per time unit) Suppose there are n
candidate interfaces to distribute the load, and each interface has an average capacity, that is, the ith
interface has capacity ci.
• To distribute the load to the candidate interfaces such that the maximum utilization on the interfaces
(denoted by u) is minimized:
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7.Performance evaluation
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 Simulation Settings(NS3 Simulator)
• Each switch has a buffer size of 20 packets.
• Each link has a bandwidth of 100 Mbps and a transmission delay of 1 ms, Request packet and the
Response packet to 30 and 1,024 bytes.
• The maximum length of the queue is set to 500, to avoid the request loss due to the queue overflow in
the simulations.
Fig. 11. The simulation topology

 Adaptive Named-Service Routing
• Proposed framework adapts to the system dynamics Average utilization of the VMs is close to
optimum(0.5)
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Fig. 13. The average utilization of the VMs via the load balancing
algorithm
Fig:12 The allocated load of individual VMs via the load balancing algorithm

 VM Migration Policy
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Fig. 15. The hop counts of individual request-response
pairs.
Fig. 14. The allocated load of individual VMs as the VMs
are migrated from group 1 to group 3

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Fig 16. The number of the requests that incur NACKs and the resulted extra hop count on average, as the amount of the load
dispatched by the gateway or the single-hop transmission delay varies.

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 Mechanism of Route Learning
Fig. 16. The simulation topology for the
mechanism of route learning

 Scalability
• Topology that consists of k-port switches has k3 /4 physical machines ,these three topologies have 16,
128 and 432 physical machines.
• Let each PM host a VM, and set each VM’s
capacity to 80 req/s.
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Fig. 17. The average utilization of the VMs in various scale of networks, where the bars
demonstrate standard deviation.

8.Conclusion
NDN is a clean-slate design in that it is a completely new architecture and has no dependency on IP.
 Traditional packets cannot be identified in transit; only the sender and recipient know which data needs
to be reconstructed. This provides an additional layer of security over other methods, such as
encryption.
Propose an emerging named service framework to support seamless VM migrations.
Advantages:
1) the VM migration is interruption free;
2) the overhead to maintain the routing information is less than that caused by classic NDN;
3) the routing protocol is robust to both link and node failures;
4) the framework inherently supports the implementation of a distributed load balancing algorithm, via
which requests are distributed to VMs in balance.
The analysis and simulation results verify these benefits.
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References
• P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R.Neugebauer, I. Pratt, and A.
Warfield, “Xen and the art of virtualization, ”SIGOPS Oper. Syst. Rev., vol. 37, no. 5, pp. 164–177,
Oct. 2003.
• Y. Wen, X. Zhu, J. Rodrigues, and C. W. Chen, “Cloud mobile media: Reflections and
outlook,”IEEE Trans. Multimedia, vol. 16,no. 4, pp. 885–902, Jun. 2014.
• M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A.
Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing,” Commun. ACM, vol. 53, no. 4,pp.
50–58, Apr. 2010.
• A. Singh, M. Korupolu, and D. Mohapatra, “Server-storage virtualization: Integration and load
balancing in data centers,” inProc.ACM/IEEE Conf. Supercomput., 2008, pp. 53:1–53:12.
• E. Silvera, G. Sharaby, D. Lorenz, and I. Shapira, “IP mobility to support live migration of virtual
machines across subnets,” in Proc. The Israeli Exp. Syst. Conf., 2009, pp. 13:1–13:10.
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Thank You!!!!!

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