A Proxy-Based Integrated Cache Consistency and Mobility Management Scheme for Mobile IP Systems

Weiping He, Ing-Ray Chen,and Baoshan GuDepartment of Computer Science, Virginia Tech

Presented by: Jing (Julia) Xu

Apr 11, 2007

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Outline Introduction System Infrastructure Cache Consistency Mobility Management Performance Analysis: SPN Experiment Results Conclusion and Future Work

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Introduction Support mobile client-

server applications. Query dynamic data Reduce access cost Improve response time

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Introduction (Cont’d) Challenge: Maintain service continuity with

disconnection tolerance. Disconnection:

Voluntary: connection cost, power consumption. Involuntary: handoff, wireless link failure.

Service continuity: be able to reuse valid previous data when mobile host (MH) reconnects.

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System Infrastructure

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Cache Consistency Overview:

MH can cache data objects locally.

Proxy-based cache: invalidation message.

Up-to-date data in MHCache reduce query traffic and cost.

ProxyCache

MHCache

disconnectreconnect

querydatainvalidation

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Mobility Management To further reduce the network traffic: mobility

management by the proxy. The proxy also serves as the Gateway Foreign Agent

(GFA) to maintain the location information of the MH. When the MH moves across a subnet boundary within

the service (GFA) area, it obtains a new care of address (CoA). The proxy is informed of CoA change, but not HA or CNs.

When MH moves across a service (GFA) area, a new GFA becomes proxy and obtains ProxyCache. HA and CNs are informed.

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A Trade-off A large service area:

The proxy will not move often. The query and cache invalidation cost is high because

of the larger distance. A small service area:

The proxy moves often: moving proxy cache informing HA and CNs

The query and cache invalidation cost are lower because of the shorter distance.

Therefore an optimal service area size exists.

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Performance Analysis A performance model based on Stochastic Petri

Nets. Objective: to derive an equation to calculate the

overall network traffic cost as a function of the number of subnets covered in a service area.

The MH can determine the dynamic optimal service area size at runtime.

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Performance Analysis (Cont’d)

Xs: # of subnets crossed by the MH since the MH enters a new service area

Compute the optimal number of subnets by varying K.

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Performance Analysis (Cont’d) Transition rates:

Moving = Wake2Sleep = ww Sleep2Wake = ws MovingProxy = MH2Proxy = InquiryProxy =

K: subnet crossingsF(k): number of hops:one-hop communication delay per packet in the wired network: ratio of the communication delay in the wireless to the wired: average distance between proxy and HA: average distance between proxy and a CNN: # of CNs the MH engagesnCT: # of packets during a proxy transfer

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Performance Analysis (Cont’d) Cost functions:

a

Ci,query =

Ci,mobility =

Ci,invalidation =

K: subnet crossingsF(k): number of hops:one-hop communication delay per packet in the wired network: ratio of the communication delay in the wireless to the wired: average distance between proxy and HA: average distance between proxy and a CNN: # of CNs the MH engagesnCT: # of packets during a proxy transfernD: # of packets to hold a data object

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Experiment Results

There exists an optimal proxy service area size Kopt

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Experiments (Cont’d)

Kopt exists for all q, i

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Experiments (Cont’d)

Kopt increases as increases

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Experiments (Cont’d)

Kopt decreases as i increases

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Experiments (Cont’d)

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Experiments (Cont’d)

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Experiments (Cont’d)

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Experiments (Cont’d)

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Experiments (Cont’d)

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Conclusion and Future Work This scheme allows MH to dynamically

determine the best service area size to minimize the overall network traffic generated.

Per MH savings can have significant impacts on all mobile users over a long time period.

Future work: To investigate applications to which this scheme can

apply. To investigate conditions under which it’s more

beneficial for CN to send data instead of invalidation.

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Thank you! Questions?