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Project topic: Adaptive cloud based services for mobile users Paper to present: Competitive Analysis for Service Migration in VNets PowerPoint PPT Presentation


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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 users Paper to present: Competitive Analysis for Service Migration in VNets

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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

  • 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

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

  • 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-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

  • 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

  • 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 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 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

Phase

7(A)

7+10+4=21(C)

21+2=23(C)

23(C)


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

  • 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


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

MahadevSatyanarayanan, ParamvirBahl

Ramon Caceres, Nigel Davies


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

  • 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


  • Cloud Computing Limitations


    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

    • 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 State Diagram


    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

    Base VM

    Install the

    Overlay VM

    Lunch VM

    Overlay VM

    VM Residue

    Done


    Proof-of-Concept (Kimberly)


    KCM VM Synthesis Delay


    Cloudlet Challenges

    • Initiation Delay

    • Business Model

    • Size

    • Trust & Security

    • Migration & Handout


    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


    Thank YOU


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