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Project topic: Adaptive cloud based services for mobile users Paper to present: Competitive Analysis for Service Migration in VNets. Zahra Abbasi. Introduction to the project. Assumptions: Providing service for mobile users through clouds Cloud based services:

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Project topic: Adaptive cloud based services for mobile usersPaper to present: Competitive Analysis for Service Migration in VNets

Zahra Abbasi

introduction to the project
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
competitive analysis for service migration in vnets

Competitive Analysis for Service Migration in VNets

MarcinBienkowskiAnjaFeldmann Dan Jurca

Wolfgang KellererGregorSchaffrath Stefan Schmid and JoergWidmer

University of Wrocław, Poland, docomolab-euro.com And

T-Labs / TU Berlin Berlin, Germany

ACM SIGCOMM 2010

introduction motivation
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
introduction motivation1
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?
overview on contributions and results
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
system model and assumptions
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

system model and assumptions1
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
online algorithm strike balance between cost acc and cost mig
Online algorithmStrike 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
online alg example
Online Alg. Example

Phase

7(A)

7+10+4=21(C)

21+2=23(C)

23(C)

optimal versus online example
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

competitive analysis
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
conclusion extending the modeling to our problem
ConclusionExtending 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
the case for vm based cloudlets in mobile computing

The Case for VM-based Cloudlets in Mobile Computing

MahadevSatyanarayanan, ParamvirBahl

Ramon Caceres, Nigel Davies

introduction
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
cloud service for mobiles
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
future of cloud computing for mobiles
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
cloudlet tiny cloud nearby
Cloudlet: Tiny cloud nearby
  • On-hop wireless LAN, morebandwidth
  • 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

Data Center in a Box

cloudlet customization
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
dynamic vm synthesis state diagram
Dynamic VM Synthesis State Diagram

Base VM

Install the

Overlay VM

Lunch VM

Overlay VM

VM Residue

Done

cloudlet challenges
Cloudlet Challenges
  • Initiation Delay
  • Business Model
  • Size
  • Trust & Security
  • Migration & Handout
conclusion
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
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