1. Project topic: Adaptive cloud based services for mobile users Paper to present: Competitive Analysis for Service Migration in VNets
Zahra Abbasi

2. Introduction to the project
Assumptions:
Providing service for mobile users through clouds
Cloud based services:
Couple of DCs that are networked
Infrastructure of the network and DC are hidden from service provider and users
Service can be hosted in any DC of the cloud
The access point of mobile users changes over time
Adaptive cloud based services
Dynamically changing the number and the locations of virtual servers to:
Minimizing energy consumption
Maximizing quality of service for mobile users
Modeling the problem as an optimization problem
Simulation based evaluation

3. Competitive Analysis for Service Migration in VNets
Marcin Bienkowski Anja Feldmann Dan Jurca
Wolfgang Kellerer Gregor Schaffrath Stefan Schmid and Joerg Widmer
University of Wrocław, Poland, docomolab-euro.com And
T-Labs / TU Berlin Berlin, Germany
ACM SIGCOMM 2010

4. Introduction-Motivation
Virtualized network/Cloud computing
The detail of infrastructure is hidden for service providers and users
Applications can be hosted in any node in a dynamic fashion

5. Introduction-Motivation
Virtualized network/Cloud computing
The detail of infrastructure is hidden for service providers and users
Applications can be hosted in any node in a dynamic fashion
Potential advantageous for mobile users
Improving the quality of service by dynamic service migration
Service migration management
Migration cost: Service outage, migration cost
Service cost: Delay of requests
Research question:
To migrate or not to migrate? (online)
How to compare with the offline optimal solution?

6. Overview on contributions and results
Proposing an online service migration for mobile based services
Competitive analysis and deriving the competitive ratio (log n)
Online vs. offline
Offline: All access point information of users is known in advance
Online: The past and current information is available

7. System model and assumptions
Virtualized network
G=(V,E)
A bandwidth is associated with any edge of the set E
Service can be hosted in any node of the set V
Access cost of users
Number of hops in the shortest path from the access point to the server
Migration cost
Costacc(A)=2 A
Bw=10
Bw=10
Costmig(S2,S3,size(s)=100)=10

8. System model and assumptions
The system makes decision for the migration on time slots called rounds
Requests access points changes at rounds
Access points: t0={A,B}, t1={C,D} where {A,B,C,D} are nodes of the set V.
There is only one service

9. Online algorithm Strike balance between Costacc and Costmig
Given
an initial physical location of the server V0 ∈ V
An initial access point set of requests ⊆ V
Phase: multiple of rounds
Step 1:
Migrate to v’ if Lv >= β, where v’ is randomly chosen among nodes whose Lv’ >= β
Reset Lv if all Lv >= β
End of phase

10. Online Alg. Example Phase L(A) L(B) L(C) L(D) L(E) β Tcost 0+5=5 2+3=5
acc(B)+acc(D)
=1+6=7
0+5=5
2+3=5
5+0=5
7+2=9
100/10=10
7(A)
7+4+8=19
5+3+7=15
5+0+4=9
5+2+2=9
9+4=13 10
7+10+4=21(C)
21+2=23(C)
19+4+6=29
15+3+5=23
9+0+2=11
9+2+0=11
13+4+2=19 10 10
23(C)

11. Optimal versus online -example
BW: 10, Latency: 11, size(s)=100
t0: {C}, v0=B
t1:{B}
Total cost for online alg: 20
Total cost for optimal: 11 B C A

12. Competitive analysis For a given phase: Cost(OPT) >= β
Case1:If the optimal solution does a migration then:
Cost(OPT) >= β
Case 2: If it does not migration
OPT pays L(v) for a fixed v during a phase , where L(v) >= β
Expected number of migration for the ALG is at most Hn (nth harmonic number, O(Hn)=logn)
{V}: the descending ordered set of vertices whose L(v) reaches β
Prev Ex: v1=A, v2=B, v3=E, v4=C, v5=D
Ti: expected # of migration given Vi as the initial point:
Recursive relationship for any vi and vj j>=i: Ti=1+Tj where j>i

13. Conclusion Extending the modeling to our problem
Simplification of assumption to derive the competitive ratio
Extension of the model for the cloud based mobile services
Energy cost of centers are taken into account
Servers are allowed to be duplicated

14. The Case for VM-based Cloudlets in Mobile Computing
Mahadev Satyanarayanan, Paramvir Bahl
Ramon Caceres, Nigel Davies
Since battery life, size and weight has more priority, mobiles can not provide the desired computational power needed for resource-intensive applications such as applications for augmenting human cognition. Both computation and energy is the intrinsic limitation of mobiles for state of the art environment interpretation applications. Far more advanced than logical localization That can be done using mobile resources.

15. Introduction
Cloud computing is a solution for resource- poverty of mobiles.
Architecture for Virtual Machine Provisioning
Customized Service nearby
Cloud Computing Limitations
Cloudlet Approach
Proof-Of-Concept
Challenges
Web-based application services over the Internet
These applications that run poorly in mobiles, need cloud
Mobile device can execute a resource-intensive applications on a distant high performance computer server or computer cluster.

16. Cloud Service for Mobiles
Battery, Weight, and Size are the most priority of mobile manufacturers
Virtualization to face resource poverty is needed
Human cognitive applications
Facial/speech recognition
Scene interpretation
Voice synthesis/translation
Computational intensive applications
Internet Delay and Jitter are harmful for interactive/real-time applications
Helps elder or disable
Needs High performance computation on a large amount of data

17. Cloud Computing Limitations
Delay can damage acuteness of graphic rendering interactive applications. To face delay applications reduce the resolution or frame rate
This slide shows the user perception quality is variable and depends on the end-to-end latency.
In a tested photo editing application the response for more than 150 ms is noticeable and annoying
Even if the response time is 100ms, 30% of interaction are noticeable to the user.

18. Future of Cloud Computing for Mobiles
Using Wireless LAN
More Bandwidth
Less Delay/Latency, Less Jitter
No rely on distant cloud
Local Data Centers
Cloudlets
Wireless access point
PC / Computer Cluster
Internet Access
We can benefit cloud computing without WAN limited, rather than relying on distant cloud.
The resource poverty can be addressed by using a nearby resource-rich cloudlet

19. Cloudlet: Tiny cloud nearby
On-hop wireless LAN, more bandwidth
Provide real-time response time , low delay
Consume less energy, more green
Wide spread, decentralized, more ubiquitous
Self-managed, easily setup, more chip
Can work connection less, independent from Internet
1- Provide
Better for local Services
One-hop wireless access to the cloudlet
Physical proximity of cloudlet meets the fast response time
Data Center in a Box

20. Cloudlet State Diagram
The first step of using cloudlet is to search the cloudlet in the local access point.
If there is a cloudlet, mobile will interact with it.
If there is not any cloud let with proximity, mobile searches for the distant cloud over the internet.
The worst case will occur when the mobile has to use its own resources

21. Cloudlet customization
Customized VM transiently by mobiles
Mobile Clients:
Pre-use customization
Use service
Post-use cleanup
Dynamic Virtual Machine Synthesis
VM base in cloudlet
VM overlay as service application
Lunch VM on cloudlet
To support the widespread of cloudlets, Cloudlets should support widest possible mobile user with any OS or any applications. Therefore the best way is to use them as a VM infrastructure.
Mobiles should customize them transiently for their specific application
Post-use cleanup is really needed to

22. Dynamic VM Synthesis State Diagram
Base VM
Install the
Overlay VM
Lunch VM
Overlay VM
In Dynamic VM synthesis, a small overlay delivered by a mobile to cloudlet infrastructure
Base virtual machine
VM Residue
Done

23. Proof-of-Concept (Kimberly)
Kimberly uses virtual box, which is a VMM on a Linux Ubuntu
VM base is a minimally configured guest OS which is compatible with mobile devices.
1- Lunch VM base on virtual box (kimberlize)
2- Guest executes install-script to install overlay VM
3- Executes resume-script to lunch VM over the cloudlet
4- The control manager of the transient binding between mobile device and the cloudlet is a process which is called Kimberly Control Manager (They abstract Service discovery and Network Management)
Avahi is linux-based tool for DNS, Service discovery, and Network Management
Communication will be based on secure TCP tunnel using SSL between KCM instances.
Dekimberlize will fetch, decrypts, decompress and apply overlay to base VM

24. KCM VM Synthesis Delay
Mobile users will face extended delays for service instantiations
Kimberly is an unoptimized initial prototype
Synthesizing a VM in seconds.

25. Cloudlet Challenges Initiation Delay Business Model Size
Trust & Security
Migration & Handout
1- Since the mobile should install the overlay on the cloudlet cloudlets may have initiation problems
2- The second challenge is whether the business owners provide cloudlet or service providers use share the profits with the retail business.
3- Whether to use PC, server or cluster in the local areas.
4- To prevent malicious applications, users, VMM, there are 2 approaches:
trust establishment, that users should perform some pre-use action before service
reputation-based trust which is based on the identity of business
5- Which is to locate the service based on the user mobility

26. Conclusion New approach of Cloud Computing for Mobiles
Nearby resource-rich computers
High Bandwidth and Low Latency
Good for Local Applications
Investment & Infrastructure
Business & Marketing
Mobiles utilize the nearby resource-rich computers
Cloudlets are good for applications that use local data
Cloudlets need marketing to convince local business
Using Cloudlet on a campus does not need any investment

27. Thank YOU